my own ecological model essay

Bronfenbrenner’s Ecological Systems Theory

Olivia Guy-Evans, MSc

Associate Editor for Simply Psychology

BSc (Hons) Psychology, MSc Psychology of Education

Olivia Guy-Evans is a writer and associate editor for Simply Psychology. She has previously worked in healthcare and educational sectors.

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Saul Mcleod, PhD

Editor-in-Chief for Simply Psychology

BSc (Hons) Psychology, MRes, PhD, University of Manchester

Saul Mcleod, PhD., is a qualified psychology teacher with over 18 years of experience in further and higher education. He has been published in peer-reviewed journals, including the Journal of Clinical Psychology.

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Bronfenbrenner’s ecological systems theory posits that an individual’s development is influenced by a series of interconnected environmental systems, ranging from the immediate surroundings (e.g., family) to broad societal structures (e.g., culture).

These systems include the microsystem, mesosystem, exosystem, macrosystem, and chronosystem, each representing different levels of environmental influences on an individual’s growth and behavior.

Key Takeaways

• Bronfenbrenner’s ecological systems theory views child development as a complex system of relationships affected by multiple levels of the surrounding environment, from immediate family and school settings to broad cultural values, laws, and customs.
• To study a child’s development, we must look at the child and their immediate environment and the interaction of the larger environment.
• Bronfenbrenner divided the person’s environment into five different systems: the microsystem, the mesosystem, the exosystem, the macrosystem, and the chronosystem.
• The microsystem is the most influential level of the ecological systems theory. This is the most immediate environmental setting containing the developing child, such as family and school.
• Bronfenbrenner’s ecological systems theory has implications for educational practice.

The Five Ecological Systems

Bronfenbrenner (1977) suggested that the child’s environment is a nested arrangement of structures, each contained within the next. He organized them in order of how much of an impact they have on a child.

He named these structures the microsystem, mesosystem, exosystem, macrosystem and the chronosystem.

Because the five systems are interrelated, the influence of one system on a child’s development depends on its relationship with the others.

1. The Microsystem

The microsystem is the first level of Bronfenbrenner’s theory and is the things that have direct contact with the child in their immediate environment.

It includes the child’s most immediate relationships and environments. For example, a child’s parents, siblings, classmates, teachers, and neighbors would be part of their microsystem.

Relationships in a microsystem are bi-directional, meaning other people can influence the child in their environment and change other people’s beliefs and actions. The interactions the child has with these people and environments directly impact development.

For instance, supportive parents who read to their child and provide educational activities may positively influence cognitive and language skills. Or children with friends who bully them at school might develop self-esteem issues. The child is not just a passive recipient but an active contributor in these bidirectional interactions.

2. The Mesosystem

The mesosystem is where a person’s individual microsystems do not function independently but are interconnected and assert influence upon one another.

The mesosystem involves interactions between different microsystems in the child’s life. For example, open communication between a child’s parents and teachers provides consistency across both environments.

However, conflict between these microsystems, like parents and teachers blaming each other for a child’s poor grades, creates tension that negatively impacts the child.

The mesosystem can also involve interactions between peers and family. If a child’s friends use drugs, this may introduce substance use into the family microsystem. Or if siblings do not get along, this can spill over to peer relationships.

3. The Exosystem

The exosystem is a component of the ecological systems theory developed by Urie Bronfenbrenner in the 1970s.

It incorporates other formal and informal social structures. While not directly interacting with the child, the exosystem still influences the microsystems. 

For instance, a parent’s stressful job and work schedule affects their availability, resources, and mood at home with their child. Local school board decisions about funding and programs impact the quality of education the child receives.

Even broader influences like government policies, mass media, and community resources shape the child’s microsystems.

For example, cuts to arts funding at school could limit a child’s exposure to music and art enrichment. Or a library bond could improve educational resources in the child’s community. The child does not directly interact with these structures, but they shape their microsystems.

4. The Macrosystem

The macrosystem focuses on how cultural elements affect a child’s development, consisting of cultural ideologies, attitudes, and social conditions that children are immersed in.

The macrosystem differs from the previous ecosystems as it does not refer to the specific environments of one developing child but the already established society and culture in which the child is developing.

Beliefs about gender roles, individualism, family structures, and social issues establish norms and values that permeate a child’s microsystems. For example, boys raised in patriarchal cultures might be socialized to assume domineering masculine roles.

Socioeconomic status also exerts macro-level influence – children from affluent families will likely have more educational advantages versus children raised in poverty.

Even within a common macrosystem, interpretations of norms differ – not all families from the same culture hold the same values or norms.

5. The Chronosystem

The fifth and final level of Bronfenbrenner’s ecological systems theory is known as the chronosystem.

The chronosystem relates to shifts and transitions over the child’s lifetime. These environmental changes can be predicted, like starting school, or unpredicted, like parental divorce or changing schools when parents relocate for work, which may cause stress.

Historical events also fall within the chronosystem, like how growing up during a recession may limit family resources or growing up during war versus peacetime also fall in this system.

As children get older and enter new environments, both physical and cognitive changes interact with shifting social expectations. For example, the challenges of puberty combined with transition to middle school impact self-esteem and academic performance.

Aging itself interacts with shifting social expectations over the lifespan within the chronosystem.

How children respond to expected and unexpected life transitions depends on the support of their ecological systems.

The Bioecological Model

It is important to note that Bronfenbrenner (1994) later revised his theory and instead named it the ‘Bioecological model’.

Bronfenbrenner became more concerned with the proximal development processes, meaning the enduring and persistent forms of interaction in the immediate environment.

His focus shifted from environmental influences to developmental processes individuals experience over time.

‘…development takes place through the process of progressively more complex reciprocal interactions between an active, evolving biopsychological human organism and the persons, objects, and symbols in its immediate external environment.’ (Bronfenbrenner, 1995).

Bronfenbrenner also suggested that to understand the effect of these proximal processes on development, we have to focus on the person, context, and developmental outcome, as these processes vary and affect people differently (Bronfenbrenner & Evans, 2000).

While his original ecological systems theory emphasized the role of environmental systems, his later bioecological model focused more closely on micro-level interactions.

The bioecological shift highlighted reciprocal processes between the actively evolving individual and their immediate settings. This represented an evolution in Bronfenbrenner’s thinking toward a more dynamic developmental process view.

However, the bioecological model still acknowledged the broader environmental systems from his original theory as an important contextual influence on proximal processes.

The bioecological focus on evolving person-environment interactions built upon the foundation of his ecological systems theory while bringing developmental processes to the forefront.

Classroom Application

The Ecological Systems Theory has been used to link psychological and educational theory to early educational curriculums and practice. The developing child is at the center of the theory, and all that occurs within and between the five ecological systems are done to benefit the child in the classroom.

• According to the theory, teachers and parents should maintain good communication with each other and work together to benefit the child and strengthen the development of the ecological systems in educational practice.
• Teachers should also be understanding of the situations their student’s families may be experiencing, including social and economic factors that are part of the various systems.
• According to the theory, if parents and teachers have a good relationship, this should positively shape the child’s development.
• Likewise, the child must be active in their learning, both academically and socially. They must collaborate with their peers and participate in meaningful learning experiences to enable positive development (Evans, 2012).

There are lots of studies that have investigated the effects of the school environment on students. Below are some examples:

Lippard, LA Paro, Rouse, and Crosby (2017) conducted a study to test Bronfenbrenner’s theory. They investigated the teacher-child relationships through teacher reports and classroom observations.

They found that these relationships were significantly related to children’s academic achievement and classroom behavior, suggesting that these relationships are important for children’s development and supports the Ecological Systems Theory.

Wilson et al. (2002) found that creating a positive school environment through a school ethos valuing diversity has a positive effect on students’ relationships within the school. Incorporating this kind of school ethos influences those within the developing child’s ecological systems.

Langford et al. (2014) found that whole-school approaches to the health curriculum can positively improve educational achievement and student well-being. Thus, the development of the students is being affected by the microsystems.

Critical Evaluation

Bronfenbrenner’s model quickly became very appealing and accepted as a useful framework for psychologists, sociologists, and teachers studying child development.

The Ecological Systems Theory provides a holistic approach that is inclusive of all the systems children and their families are involved in, accurately reflecting the dynamic nature of actual family relationships (Hayes & O’Toole, 2017).

Paat (2013) considers how Bronfenbrenner’s theory is useful when it comes to the development of immigrant children. They suggest that immigrant children’s experiences in the various ecological systems are likely to be shaped by their cultural differences. Understanding these children’s ecology can aid in strengthening social work service delivery for these children.

Limitations

A limitation of the Ecological Systems Theory is that there is limited research examining the mesosystems, mainly the interactions between neighborhoods and the family of the child (Leventhal & Brooks-Gunn, 2000). Therefore, the extent to which these systems can shape child development is unclear.

Another limitation of Bronfenbrenner’s theory is that it is difficult to empirically test the theory. The studies investigating the ecological systems may establish an effect, but they cannot establish whether the systems directly cause such effects.

Furthermore, this theory can lead to assumptions that those who do not have strong and positive ecological systems lack in development. Whilst this may be true in some cases, many people can still develop into well-rounded individuals without positive influences from their ecological systems.

For instance, it is not true to say that all people who grow up in poverty-stricken areas of the world will develop negatively. Similarly, if a child’s teachers and parents do not get along, some children may not experience any negative effects if it does not concern them.

As a result, people need to avoid making broad assumptions about individuals using this theory.

How Relevant is Bronfenbrenner’s Theory in the 21st Century?

The world has greatly changed since this theory was introduced, so it’s important to consider whether Bronfenbrenner’s theory is still relevant today. 

Kelly and Coughlan (2019) used constructivist grounded theory analysis to develop a theoretical framework for youth mental health recovery and found that there were many links to Bronfenbrenner’s ecological systems theory in their own more recent theory.

Their theory suggested that the components of mental health recovery are embedded in the ‘ecological context of influential relationships,’ which fits in with Bronfenbrenner’s theory that the ecological systems of the young person, such as peers, family, and school, all help mental health development.

We should also consider whether Bronfenbrenner’s theory fits in with advanced technological advancements in the 21st century. It could be that the ecological systems are still valid but may expand over time to include new modern developments.

The exosystem of a child, for instance, could be expanded to consider influences from social media, video gaming, and other modern-day interactions within the ecological system.

Neo-ecological theory

Navarro & Tudge (2022) proposed the neo-ecological theory, an adaptation of the bioecological theory. Below are their main ideas for updating Bronfenbrenner’s theory to the technological age:

• Virtual microsystems should be added as a new type of microsystem to account for online interactions and activities. Virtual microsystems have unique features compared to physical microsystems, like availability, publicness, and asychnronicity.
• The macrosystem (cultural beliefs, values) is an important influence, as digital technology has enabled youth to participate more in creating youth culture and norms.
• Proximal processes, the engines of development, can now happen through complex interactions with both people and objects/symbols online. So, proximal processes in virtual microsystems need to be considered.

Urie Bronfenbrenner was born in Moscow, Russia, in 1917 and experienced turmoil in his home country as a child before immigrating to the United States at age 6.

Witnessing the difficulties faced by children during the unrest and rapid social change in Russia shaped his ideas about how environmental factors can influence child development.

Bronfenbrenner went on to earn a Ph.D. in developmental psychology from the University of Michigan in 1942.

At the time, most child psychology research involved lab experiments with children briefly interacting with strangers.

Bronfenbrenner criticized this approach as lacking ecological validity compared to real-world settings where children live and grow. For example, he cited Mary Ainsworth’s 1970 “Strange Situation” study , which observed infants with caregivers in a laboratory.

Bronfenbrenner argued that these unilateral lab studies failed to account for reciprocal influence between variables or the impact of broader environmental forces.

His work challenged the prevailing views by proposing that multiple aspects of a child’s life interact to influence development.

In the 1970s, drawing on foundations from theories by Vygotsky, Bandura, and others acknowledging environmental impact, Bronfenbrenner articulated his groundbreaking Ecological Systems Theory.

This framework mapped children’s development across layered environmental systems ranging from immediate settings like family to broad cultural values and historical context.

Bronfenbrenner’s ecological perspective represented a major shift in developmental psychology by emphasizing the role of environmental systems and broader social structures in human development.

The theory sparked enduring influence across many fields, including psychology, education, and social policy.

Frequently Asked Questions

What is the main contribution of bronfenbrenner’s theory.

The Ecological Systems Theory has contributed to our understanding that multiple levels influence an individual’s development rather than just individual traits or characteristics.

Bronfenbrenner contributed to the understanding that parent-child relationships do not occur in a vacuum but are embedded in larger structures.

Ultimately, this theory has contributed to a more holistic understanding of human development, and has influenced fields such as psychology, sociology, and education.

What could happen if a child’s microsystem breaks down?

If a child experiences conflict or neglect within their family, or bullying or rejection by their peers, their microsystem may break down. This can lead to a range of negative outcomes, such as decreased academic achievement, social isolation, and mental health issues.

Additionally, if the microsystem is not providing the necessary support and resources for the child’s development, it can hinder their ability to thrive and reach their full potential.

How can the Ecological System’s Theory explain peer pressure?

The ecological systems theory explains peer pressure as a result of the microsystem (immediate environment) and mesosystem (connections between environments) levels.

Peers provide a sense of belonging and validation in the microsystem, and when they engage in certain behaviors or hold certain beliefs, they may exert pressure on the child to conform. The mesosystem can also influence peer pressure, as conflicting messages and expectations from different environments can create pressure to conform.

Bronfenbrenner, U. (1974). Developmental research, public policy, and the ecology of childhood . Child development, 45 (1), 1-5.

Bronfenbrenner, U. (1977). Toward an experimental ecology of human development . American psychologist, 32 (7), 513.

Bronfenbrenner, U. (1995). Developmental ecology through space and time: A future perspective .

Bronfenbrenner, U., & Evans, G. W. (2000). Developmental science in the 21st century: Emerging questions, theoretical models, research designs and empirical findings . Social development, 9 (1), 115-125.

Bronfenbrenner, U., & Ceci, S. J. (1994). Nature-nurture reconceptualised: A bio-ecological model . Psychological Review, 10 (4), 568–586.

Hayes, N., O’Toole, L., & Halpenny, A. M. (2017). Introducing Bronfenbrenner: A guide for practitioners and students in early years education . Taylor & Francis.

Kelly, M., & Coughlan, B. (2019). A theory of youth mental health recovery from a parental perspective . Child and Adolescent Mental Health, 24 (2), 161-169.

Langford, R., Bonell, C. P., Jones, H. E., Pouliou, T., Murphy, S. M., Waters, E., Komro, A. A., Gibbs, L. F., Magnus, D. & Campbell, R. (2014). The WHO Health Promoting School framework for improving the health and well‐being of students and their academic achievement . Cochrane database of systematic reviews, (4) .

Leventhal, T., & Brooks-Gunn, J. (2000). The neighborhoods they live in: the effects of neighborhood residence on child and adolescent outcomes . Psychological Bulletin, 126 (2), 309.

Lippard, C. N., La Paro, K. M., Rouse, H. L., & Crosby, D. A. (2018, February). A closer look at teacher–child relationships and classroom emotional context in preschool . In Child & Youth Care Forum 47 (1), 1-21.

Navarro, J. L., & Tudge, J. R. (2022). Technologizing Bronfenbrenner: neo-ecological theory.  Current Psychology , 1-17.

Paat, Y. F. (2013). Working with immigrant children and their families: An application of Bronfenbrenner’s ecological systems theory . Journal of Human Behavior in the Social Environment, 23 (8), 954-966.

Rhodes, S. (2013).  Bronfenbrenner’s Ecological Theory  [PDF]. Retrieved from http://uoit.blackboard.com

Wilson, P., Atkinson, M., Hornby, G., Thompson, M., Cooper, M., Hooper, C. M., & Southall, A. (2002). Young minds in our schools-a guide for teachers and others working in schools . Year: YoungMinds (Jan 2004).

Further Information

Bronfenbrenner, U. (1974). Developmental research, public policy, and the ecology of childhood. Child Development, 45.

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Ecological Theory: Bronfenbrenner’s Five Systems

Categories Development , Theories

Ecological theory suggests that human development is influenced by several interrelated environmental systems. Introduced by psychologist Urie Bronfenbrenner, ecological theory emphasizes the importance of understanding how various systems and environments interact with and influence people throughout life. 

Key Takeaways

• Ecological theory examines how individuals are shaped by their interactions with various environments.
• Bronfenbrenner’s model categorizes these environments into microsystems, mesosystems, exosystems, macrosystems, and chronosystems.
• The theory highlights the importance of considering environmental context in understanding human development.
• While offering valuable insights, ecological theory also poses challenges, such as complexity and limitations in generalization.

Table of Contents

What Is Ecological Theory?

Bronfenfrenner’s ecological theory suggests that the interaction between and individual and their environment influences the developmental process. Bronfenbrenner organized these environmental factors into different systems or layers–each one interacting with each other as well as the individual.

In order to understand how humans develop throughout life, it is important to examine the multiple connections and influences of such systems. These influences include the immediate environment, including family and peers, as well as the much broader society and culture in which the individual and these other systems exist.

The Five Systems in Ecological Theory

Ecological theory describes five layered systems or levels that influence human behavior and development. These levels are often portrayed as a series of concentric circles. At the center of the system is the individual. The first layer is the one that they have the most immediate contact with, with each circle expanding outward and encompassing all of the inner layers.

The five levels of ecological theory are the microsystem, mesosystem, exosystem, macrosystem, and chronosystem.

1. Microsystem

The microsystem refers to the immediate environments where individuals directly interact, such as family, school, peer groups, and religious institutions. These settings have a profound impact on a person’s development, as they provide the most immediate and intimate social experiences. 

For example, within the family microsystem, children learn essential skills, values, and behaviors through interactions with parents, siblings, and caregivers. Similarly, the school microsystem shapes cognitive development, social skills, and peer relationships. 

These microsystemic interactions are crucial as they lay the foundation for future relationships and societal engagement.

2. Mesosystem

The mesosystem encompasses the interconnections between various microsystems in an individual’s life. It focuses on how different settings interact and influence each other, ultimately impacting the individual’s development. 

For instance, the relationship between family and school is a significant aspect of the mesosystem. A child’s experiences at home can affect their performance and behavior at school, and conversely, school experiences can influence family dynamics. 

Understanding these interactions is essential for comprehending the holistic nature of human development and the interconnectedness of different environments.

3. Exosystem

The exosystem comprises external settings that indirectly impact an individual’s development, even though they do not directly participate in those settings. Examples include the parents’ workplace, community services, and mass media. 

These environments may influence the individual through the experiences of people close to them or through policies and societal norms. 

For instance, a parent’s job stability or workplace stress can affect family dynamics and, subsequently, a child’s well-being. Similarly, community resources and media portrayals can influence individuals indirectly and influence societal perceptions and values.

4. Macrosystem

The macrosystem encompasses the broader cultural, societal, and political contexts that influence development. It includes cultural norms, economic systems, ideologies, and government policies. These elements shape the values, beliefs, and opportunities available to individuals within a society. 

For example, cultural attitudes toward education, gender roles, and socioeconomic inequality significantly impact individuals’ life paths and opportunities. Understanding the macrosystem is crucial for recognizing the broader structural forces that shape human development and behavior.

5. Chronosystem

The chronosystem incorporates the dimension of time into Bronfenbrenner’s ecological theory, emphasizing how individual and environmental factors change over time and influence development. This system recognizes the importance of historical events, life transitions, and personal experiences at different developmental stages. 

For example, changes in family structure, societal norms, and technological advancements can profoundly affect individuals’ development across the lifespan. By considering these temporal factors, ecological theory provides a dynamic framework for understanding human development throughout the entire lifespan.

History of Ecological Systems Theory

Urie Bronfenbrenner was a renowned developmental psychologist. He introduced the ecological systems theory to provide a comprehensive framework for understanding human development. 

Born in 1917 in Russia, Bronfenbrenner immigrated to the United States with his family during the Russian Revolution. His early experiences as an immigrant deeply influenced his perspective on human development, leading him to explore the complex interactions between individuals and their environments.

Bronfenbrenner’s interest in understanding how various environmental factors shape development stemmed from his observations as a psychologist working with children and families. He sought to move beyond traditional theories that focused solely on individual traits or familial influences and instead emphasized the importance of considering the broader ecological contexts in which individuals live.

Bronfenbrenner developed his ecological systems theory throughout the latter half of the 20th century, drawing from interdisciplinary research in psychology, sociology, anthropology, and biology. He published his seminal work, “The Ecology of Human Development: Experiments by Nature and Design,” in 1979, where he presented his theory in detail.

Central to Bronfenbrenner’s theory is the notion that human development occurs within a series of nested environmental systems, each exerting varying degrees of influence on the individual.

Bronfenbrenner’s ecological systems theory has had a profound impact on the field of developmental psychology . It emphasizes the importance of considering the dynamic interplay between individuals and their environments. 

His work has influenced research, policy-making, and intervention strategies aimed at promoting healthy development across the lifespan. Urie Bronfenbrenner’s legacy continues to shape our understanding of human development and the complex ecological contexts in which it occurs.

Examples of Environmental Influences in Ecological Theory

To understand ecological theory, it can be helpful to take a closer look at some of the influences that people experience at each level:

Microsystem

• Family : Parenting styles , sibling relationships, household routines.
• School : Teacher-student interactions, peer relationships, classroom environment.
• Peer groups : Friendship dynamics, social support networks, peer pressure.
• Religious institutions : Belief systems, community engagement, moral teachings .
• Family-school : Parent-teacher communication, involvement in school activities.
• School-peer groups : Peer influence on academic performance, social dynamics within school settings.
• Family-religious institutions : Religious practices within the family, involvement in religious community activities.
• Peer groups-community services : Peer support for accessing community resources, involvement in community service projects.
• Parent’s workplace : Work hours, job stability, workplace culture.
• Community services : Access to healthcare, availability of recreational facilities, quality of public transportation.
• Mass media : Portrayal of societal norms, the influence of media on attitudes and behaviors.
• Extended family : Support from extended family members, family gatherings, and traditions.

Macrosystem

• Cultural norms : Attitudes toward education, gender roles, and family structure.
• Socioeconomic systems : Economic inequality, access to resources and opportunities.
• Political ideologies : Government healthcare, education, and social welfare policies.
• Historical context : Societal changes over time, impact of historical events on cultural values.

Chronosystem

• Family changes : Divorce, remarriage, birth of siblings.
• Socioeconomic transitions : Job loss, career advancement, changes in income level.
• Technological advancements : Impact of technology on communication patterns, learning opportunities, and social interactions.
• Historical events : Wars, economic recessions, civil rights movements.

These examples illustrate the diverse aspects within each system of ecological theory and highlight the interconnectedness of different environmental influences on human development.

How These Systems Interact

These systems within Bronfenbrenner’s ecological theory interact dynamically, influencing each other and ultimately shaping individual development. Here are a couple of examples to illustrate this interaction:

Microsystem-Mesosystem Interaction

Parental involvement in school activities can positively impact a child’s academic performance. When parents communicate with teachers (microsystem) and participate in school events (mesosystem), they reinforce the importance of education and create a supportive learning environment for the child.

Exosystem-Macrosystem Interaction

Government policies regarding parental leave can affect both family dynamics and workplace culture. When a country implements policies that support parental leave (macrosystem), it enables parents to spend more time with their children during critical developmental stages. 

This can lead to positive outcomes for children’s socioemotional well-being and family cohesion (exosystem). Additionally, such policies may contribute to broader societal changes by promoting gender equality in the workforce.

Practical Applications for Ecological Theory

Ecological theory offers valuable insights that have been applied across various fields, including psychology, education, social work, and public policy. Some key applications include:

Education and School Systems

• Understanding how different factors within and outside the classroom influence students’ academic achievement and socioemotional well-being.
• Designing interventions and programs to create supportive learning environments.
• Enhancing teacher-student relationships and peer dynamics.

Family Interventions and Counseling

• Assessing family dynamics and interactions using a holistic approach.
• Identifying areas for intervention to strengthen family functioning and relationships.
• Exploring connections between the family and other settings, such as school or community services.

Community Development and Social Services

• Addressing systemic barriers to opportunity and promoting community resilience.
• Designing culturally responsive interventions that meet the diverse needs of communities.
• Advocating for policies that promote social justice and equity.

Policy-Making and Advocacy

• Creating inclusive policies that support the well-being of all individuals and communities.
• Adapting policies to evolving societal needs and challenges.
• Recognizing the impact of institutional factors such as racism and economic inequality.

Research and Evaluation

• Studying the complex interactions between individuals and their environments.
• Identifying risk and protective factors that influence human development.
• Assessing interventions’ impact on multiple levels of the ecological hierarchy.

Ecological theory informs various fields, providing a comprehensive framework for understanding and promoting human development in many different contexts. Health practitioners, mental health professionals, policymakers, and researchers can utilize this framework collaboratively to create supportive environments and foster positive outcomes for all.

Strengths and Limitations of Ecological Theory

Bronfenbrenner’s ecological systems theory is one way of thinking about human development . Like other theories, it has both strengths and shortcomings.

• Comprehensive approach : Ecological theory provides a comprehensive framework for understanding human development by considering the complex interactions between individuals and their environments.
• Holistic approach : It emphasizes the importance of examining multiple levels of environmental influence, from immediate settings to broader societal contexts, to gain a holistic understanding of development.
• Applicability : The theory has practical applications across various fields, including education, social work, and policy-making, guiding interventions and programs aimed at promoting positive outcomes for individuals and communities.
• Emphasis on context : By highlighting the significance of environmental context, ecological theory acknowledges the diversity of human experiences and the impact of cultural, socioeconomic, and historical factors on development.

Limitations

• Complexity : The interconnected nature of ecological systems can make it challenging to disentangle the specific influences on individual development, leading to complexity in research and intervention efforts.
• Overlooks internal factors : Ecological theory primarily focuses on environmental influences on development, sometimes overlooking the role of individual agency and internal factors in shaping behavior and outcomes.
• Difficulty in generalization : Contextual factors vary widely across individuals and communities, making it difficult to generalize findings or interventions derived from ecological theory to different cultural or socioeconomic contexts.
• Potential for oversimplification : In attempting to capture the complexity of human development within a hierarchical framework, there is a risk of oversimplification, overlooking nuances and interconnections between systems.

While ecological theory offers valuable insights into the dynamic interplay between individuals and their environments, researchers and practitioners must be mindful of its limitations and consider them when applying the theory to real-world contexts.

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Bronfenbrenner’s Bioecological System Theory Essay

Introduction, microsystem, macrosystem.

Bronfenbrenner’s bioecological systems theory postulates that human development is the sum of factors of bioecological systems that are in an environment that one lives. The theory elucidates how bioecological systems influence human development throughout one’s lifespan, as it is extensively applicable in developmental psychology. Developmental psychology majorly entails the study of children’s behavior under strange circumstances and their interaction with adults. The theory views human development in the context of relationships that exist in bioecological systems of one’s environment. Bronfenbrenner (1994) argues that, human development occurs progressively through complex and reciprocal interactions between an individual and people, and objects and symbols that are in a given immediate environment (p.37). For interactions to be effective, they must be enduring and should occur in the immediate environment to form proximal processes that significantly influence human development. The proximal process exists in bioecological systems made of five spheres, namely microsystem, mesosystem, exosystem, macrosystem, and chronosystem. This essay describes four spheres of bioecological systems viz. microsystem, mesosystem, exosystem, and macrosystem, and analyzes the past and present biopsychosocial factors that influence human development.

Microsystem is the closest bioecological environment that directly influences human development. Microsystem consists of structures such as family, childcare, neighborhood, school, and workplace, which mainly form part of immediate bioecological environment. In microsystem, an individual experience regular interactions through relationships, routine activities, and social roles that elicit progressive and sustained interactions, which bring about human development. According to Bronfenbrenner (1994), proximal processes operate optimally in microsystem because it forms an immediate environment that elicit and sustain human development (p.39). Under microsystem level, family is a dominant structure that does not only influence child development but also development in adults. At microsystem level, relationships have a reciprocal influence that shape development of individuals in a given social structure. For instance, parents have the capacity to influence beliefs, behavior, and values of a child, and vice versa. Bioecological systems theory states that, reciprocal interactions are strongest at microsystem level, and they have the greatest impact on human development due to the proximity of bioecological factors.

Family, as a social structure, significantly influenced my development during childhood because family members advised me on how to go about in life and become a successful person. For example, my mother loved me immensely in that she used to advise me regularly on how to have a decent discipline and work hard in my studies. Since I perceived that she loved me and wanted the best of me, I became determined not to let my mother down and thus I obeyed her advices to the letter. Then, I became an exceptionally courteous and industrious student in my class, which earned me warm reputation not only at school but also at home. Our relationship with my mother strengthened to the extent that, she would not deny me anything that I asked and on my part, I was so afraid to do anything that would disgrace her. Thus, reciprocal interaction between my mother and I significantly influenced my beliefs, values and behavior.

Present interaction with my spouse has tremendously influenced my social skills since I have learned that different individuals have diverse beliefs, values, and behaviors that complicate formation of relationships. When I first met my spouse, we differed in most aspects of social interest, but with time, through effective interactions, we managed to make numerous compromises to accommodate our differences. From experiences of disagreements, I learned that an individual is an entity with unique values, beliefs, and behavior that need tolerance for a healthy relationship that would stand the test to develop. Thus, my interaction with my spouse has shaped my perception of individuals as unique members of society who have different interests and, therefore, they need tolerance and forbearance from their interacting partners.

Mesosystem comprises interaction of various microsystems that are in bioecological environment where one lives. For instance, interaction of microsystem structures such as family, childcare, neighborhood, school and workplace, determines overall human development in the society. Mesosystem has increased societal forces that influence human development, unlike microsystem that only depends on individual interaction. Johnson (2008) argues that, interaction between family and school is particularly crucial in shaping the development of elementary school pupils because it provides a platform for teachers and parents to interact effectively in educating the pupils (p.3). Therefore, it implies that interactions of microsystems enhance concerted efforts of societal forces that are crucial in shaping human development. Thus, the more the interacting microsystems, the significant are the societal forces that influence an individual.

Family and school are social structures that significantly influenced my development during my childhood. Both structures influenced my behavior because they taught me to be a hardworking and discipline student so that I could achieve extraordinary dreams. For example, during my childhood, my mother and my teacher were friends, for they interacted more often. Since my mother wanted the best out of me, she constantly consulted the teacher to hear about my progress and in turn sought advices on how to enhance my academic performance. With time, I realized that my teacher cared so much like my mother in that she would always ensure that I have done my assignments and encouraged me to work hard lest I disgraced my mother. Hence, relationships between my mother and my teacher compelled me to work hard in my studies because I had no way of evading my duties because both school and family constantly monitored my progress.

Currently, interaction between my mother and my spouse has significantly shaped relationships in my family. Before I got married, my mother has been advising me on how to become a responsible father in a family so that when time comes I assume my responsibility well. Throughout my life, I have liked the way my mother treated us as a family, and I terribly longed to marry a spouse with qualities that resembled those of my mother. At first, we differed on many issues with my spouse, but when she interacted with my mother, she changed appreciably and we lived happily. Current interaction of my mother and my spouse has saved my family a fantastic deal of conflicts that usually did arise due to poor relationships.

Exosystem consists of interaction of diverse microsystems with at least one social structure that has indirect influence on an individual. At exosystem level, social structures that do not exist in microsystem sphere of an individual have indirect influence on human development, for they contribute to direct influences from immediate social structures. For example, interaction of family and parent’s workplace or school and neighborhood influence development of children in the society. Boyd, Bee, and Johnson (2008) argue that, although children in the family may not have direct contact with social structures workplace and neighborhood, they experience both negative and positive impacts from remote interactions that influence their own microsystem (p.52). Three microsystems, family, school and peer group, which form part of exosystem, indirectly affect development of children in the society.

During my childhood, my parents used to spent a considerable deal of time in their workplaces leaving us alone as children to stay alone. My father would come home rarely, for he worked in a different state from where we lived. Although my mother worked within the state where we lived, she would usually leave early in the morning and arrive late in the evening. Thus, their constant absence in the family made me take responsibility of taking care of my siblings as I learned that my parents were busy working hard in their respective workplaces so that they could provide for us. Therefore, interaction of our family with workplaces through my parents taught me to take responsibility in the family, which has made me develop leadership qualities.

Currently, since children are susceptible to various diseases, I have been taking my children to hospital for treatment and medical checkup quite often. Since my family interacts with hospital quite often, I have been able to learn a lot from Canadian health care system regarding prevention, treatment, and management of common infections that affect children and other family members, as well. If it were not for my children, I would not have bothered to learn health issues that affect families; thus, my children interaction with hospital gave me an insight of not only Canadian health care system but understanding of general human health.

Macrosystem is a complex of social structures such as microsystem, mesosystem, and exosystem, which are under the influence of customs, norms, values, and laws that govern societal culture. According to Johnson (2008), macrosystem is the outermost sphere that has a cascading effect on development of children through interaction of various spheres, which consequently determines values, beliefs, norms, customs and laws that influence children’s microsystem (p.3). Biopsychosocial factors that exist in the community, society, and culture interact with diverse microsystems, mesosystems, and exosystems, thus forming a complex of macrosystem, which entirely determines human development in the society. It means that macrosystem is the blueprint of societal culture since it consists of diverse beliefs, values, norms, laws, and customs that dominate society and thus significantly influence human development.

During my childhood, Canadian customs and values significantly influenced me to adopt British and French culture since I attended a school, which had both British and French students. History shows that Canadian culture emanated from interaction of British and French culture; therefore, it enabled me to interact effectively with other students while at school. Since Canadian culture had elements of British and French culture, I developed interests in learning music and literature, which enabled me to adopt and develop their culture during my childhood. Hence, Canadian customs and values made me appreciate and learn other cultures at school for I perceived that we had common elements in our different cultures.

Currently, government policies have dictated my career development as a nurse. Government polices stipulate that I must undergo a recommendable nursing course for me to qualify and obtain practicing license. Furthermore, government polices do not only dictate that I must have certain qualification, but also expect that I must comply with nursing codes of ethics so that I can practice nursing. Hence, government policies have influenced my nursing course, schooling years and ultimately my career development. For one to qualify as a nurse, it depends on compliance with government policies and laws that govern nursing profession. In my case, since government regard nurses by paying them well, I opted to choose nursing as my career.

Bronfenbrenner’s bioecological systems theory has taught me that human development occurs due to interplay of many factors in bioecological environment, which act in hierarchical levels of life; microsystem, mesosystem, exosystem and macrosystem. These hierarchical levels of systems have proximal processes that directly or indirectly affect human development in a complex society. As a nurse, I have learned that educating people on health issues requires one to target the microsystem, mesosystem, exosystem, and macrosystem spheres to have comprehensive impact on population.

Boyd, D., Bee, H., & Johnson, P. (2008). Lifespan Development, Third Canadian Edition. Canada: Pearson Education.

Bronfenbrenner, U. (1994). Ecological Models of Human Development. In International Encyclopedia of Education , 3, 2nd. Ed. Oxford: Elsevier.

Reprinted in: Guavain, M., & Cole, M. (Eds.). (1993). Readings on the Development of Children (2nd Ed.) New York: Freeman.

Johnson, E. (2008). Ecological Systems and Complexity Theory: Toward an Alternative Model of Accountability in Education. An International Journal of Complexity and Education , 6, 1-10.

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2.17: Assignment- Bioecological Model Journal

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STEP 1 : Think of yourself at a particular time in your childhood (e.g., age 10). Use the following prompts to help you write a journal entry about your childhood experiences as seen through Urie Bronfenbrenner’s bioecological model. Write you answers as a personal reflection paper, in paragraph form, between 400-600 words.

Microsystem

• your parents:
• your siblings:
• your peers:
• your school and teacher:
• how your parents interacted with your school and helped with schoolwork:
• how your parents interacted with your peers:
• how your community interacted with your family/peers:
• how your religious background influenced your family:
• your parents’ jobs and socioeconomic status:
• how your family explored or interacted with the world beyond your community (e.g., vacations, travel sports, mission trips, etc.):
• popular media—television, music, movies, social media:
• any interactions with social services:
• the economic condition of your community:
• the history and values of your community:

Macrosystem

• what was going on in the world at the time (e.g., Hurricane Katrina, who was president, etc.):
• technological advancements:
• national or international cultural values (e.g., racial diversity, gender equality, etc.):

Chronosystem

• major life transitions (such as the birth or death of a sibling):
• major world events that changed history at that time (e.g., terrorist attacks, presidential elections, wars, etc.):
• more gradual historical changes (the history of transgender people in the United States or the change in the number of women in the workplace):

STEP 2 : Submit your paper.

Contributors and Attributions

• Authored by : Nancee Ott. License : CC BY: Attribution
• Modification, adaptation, and original content. Authored by : Sonja Ann Miller for Lumen Learning. Provided by : Lumen Learning. License : CC BY: Attribution

Bronfenbrenner's Ecological Model

In a world of efficiency and generalization, individuality often becomes overlooked when forming human development theories. Russian American psychologist Urie Bronfenbrenner recognized this flaw and created the Ecological Model to explain how a person’s development is influenced by and influential to the environment in which they live. His model is made up of four main domains; the microsystem, mesosystem, exosystem and macrosystem, in the later years he added the chronosystem. The closest system to a person is called the microsystem, it includes all areas in which a person directly interacts. Second is the exosystem which consists of areas that affect a person without direct interaction. The mesosystem is not a sphere, rather it is designed …show more content…

I came to realize that although I had some hardships growing up, I was and still am extremely privileged. Although having scoliosis can be seen as being underprivileged, as I cannot function the same as others physically often leaving me out of activities, and resulting in a career switch, I am lucky enough to live in a country with a wonderful healthcare system. The healthcare Canadians receive allowed me to undergo the treatment and care I required in order to fix my scoliosis and prevent future health complications. Through creating a profile I was able to see that I was fortunate enough to go to preschool all the way through to high school and some of post-secondary without having to pay out of my own pocket due to government funding. I have come to the conclusion that without the love and support of my parents, none of what I have accomplished today would be possible, which I see as an amazing privilege to be brought up in such a caring home. On my journey of creating my own ecological profile, I have come to think about the individuality of each person and how knowing more about other’s profiles may help my …show more content…

Although all the children will have similar chronosystems and macrosystems, each child’s microsystem, mesosystem and exosystem will be exponentially diverse. Understanding each child’s individual profile would help me to better comprehend the child’s behaviours, quirks and personality. Knowing the child’s ecological profile could help me to better point out a child’s challenges and talents and the reasoning behind it. I have come to realize that each child reacts to me differently because of their history, meanwhile I react to each of them differently due to

Bronfenbrenner's Childhood In The Other Wes Moore

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Birth To 19 Years: A Narrative Analysis

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African American Single Mothers

This theory illustrates ? how the environment impacts human development" (Bronfenbrenner, 1986, p. 723) as a result of a number of influences such as social networks, poverty, oppression, and discrimination. Sontag (1996) stated that the Ecological Theory highlights the multiple influences on the development of the individual and family. The model includes four subsets: (1) Microsystem, (2) Mesosystem, (3) Exosystem, and (4) Macrosystem.

Urie Bronferbernner Ecological Model Essay

The five systems of Urie Bronferbernner’s ecological model play an important role in human development. It consists of microsystem, mesosystem, exosystem, macrosystem and chronosystem. According to Berk (2000), microsystem is meant by the environment a person is living is link bi-directly to them. This system involves interactions and relationship of an individual with their immediate surroundings such as family, peers, school and neighborhood (Berk, 2000). As for mesosystem, it is a system that has a connection between microsystem which is can also be explain by having a parents and school context (Ryan, 2001).

Child Care Center Observation

Showing photographs of food that they have or have not seen before and reading stories about food can also create knowledge of new food in the children’s mind. As a result, the children learn that there are different types of food, their knowledge of food will enrich and new knowledge of food will begin to form. According to Bronfenbrenner, he developed the ecological theory explaining how everything in a child and the environment affects their growth and development. He divided the ecological theory into five systems and one of the systems is called the microsystem.

Personal Narrative: My Cheerleading Career

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Bronfenbrenner's Ecological Systems Theory Paper

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Bioecological Model Of Human Development

The bioecological model of human development is defined as “the phenomenon of continuity and change in the biopsychological characteristics of human beings, both as individuals and as a group” (Brofenbrenner and Morris, 2006). This model of development has four defining properties: 1) Process, 2) Person, 3) Context and 4) Time. Process is the core of the model and involves the interaction between the individual and the environment, termed proximal processes. These proximal processes primarily drive human development but its influence on human development varies, depending on the characteristics of the Person, the Context and Time

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Jean Piaget proposed the cognitive-stage theory which says that children learn about the world through their environment in developmental stages. Lev Vygotsky proposed the sociocultural theory which is similar to Piaget's, but says that children learn in stages through social interactions. The fourth perspective is the contextual perspective which includes Urie Bronfenbrenner's bioecological theory. The contextual perspective says that development is only understood in a social context (Martorell, Papalia, and Feldman, 2014, pg 36). The bioecological theory separates the environment into different systems that affect a child's

Sandra Scarr's Analysis

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Bronfenbrenner's Ecological Theory Essay

and it made me feel like a can make a difference in the world, even if it is only one child at a time. 6. Theory and Knowledge It is evident that the school environment and the educators has a major impact on learners development and their behavior throughout their schooling career, however most theorist agree that there are a lot of external factors and the learners environment that has the most impact on them. Bradbury (2007) links the family environment as well as the environment they find themselves in economically to be of utmost importance in the development of the child.

Lifespan Development And Bowlby's Attachment Theory

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Advantages And Disadvantages Of Bronfenbrenner's Ecological System Theory

This ecological systems theory shows that a child develops through his surroundings and his environment Bronfenbrenner’s theory states that there are many complex layers of environments which each have an effect on a child’s development. This ecological theory is also known as bioecological systems

John B. Watson's Theory Of Behaviorism

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Emily Greenfield's Social Theory

III - In Emily Greenfield’s, description of Ford and Lerner’s 1992 Developmental Systems Theory, she writes “While DST notes that social environments can fundamentally influence individuals’ behavior, at the same time, individuals-within existing environmental constraints and opportunities-can select and shape these very environments. In this way, DST conceptualizes individuals as both products and producers of their own development. (E. Greenfield p. 532) The person-environment relationship is symbiotic, they affect one another and cannot be viewed independent of each other. Using Levine’s Basic Problem Solving Process, if we define assessment, as leading “...to a definition of the problem, and it beginning to indicate resources for dealing

More about Bronfenbrenner's Ecological Model

What is Bronfenbrenner’s Ecological Systems Theory?

American psychologist Urie Bronfenbrenner formulated the Ecological Systems Theory to explain how social environments affect children’s development. This theory emphasizes the importance of studying children in multiple environments, known as ecological systems, in the attempt to understand their development.

According to Bronfenbrenner’s ecological systems theory, children typically find themselves enmeshed in various ecosystems, from the most intimate home ecological system to the larger school system, and then to the most expansive system which includes society and culture. Each of these ecological systems inevitably interact with and influence each other in all aspects of the children’s lives.

Bronfenbrenner’s ecological model organizes contexts of development into five nested levels of external influence: Microsystem , Mesosystem , Ecosystem , Macrosystem , and Chronosystem . These levels are categorized from the most intimate level to the broadest.

The Microsystem

The Bronfenbrenner theory suggests that the microsystem is the smallest and most immediate environment in which children live. As such, the microsystem comprises the home, school or daycare, peer group and community environment of the children.

Interactions within the microsystem typically involve personal relationships with family members, classmates, teachers and caregivers. How these groups or individuals interact with the children will affect how they develop. More nurturing and supportive interactions and relationships will likely to foster a better environment for development.

Bronfenbrenner proposed that many of these interactions are bi-directional: how children react to people in their microsystem will also affect how these people treat the children in return.

For example, a little boy playing alone in a room. This little boy suddenly bursts out crying for no apparent reason. His mother, who is making lunch in the kitchen, hears the boy crying. She comes into the room, picks the little boy up, and carries him to the living room.

In the above example, the little boy initiated the interaction (crying), and his mother responded. In a way, the little boy influenced his mother’s behavior.

One of the most significant findings that Urie Bronfenbrenner unearthed in his study of ecological systems is that it is possible for siblings who find themselves in the same ecological system to experience very different environments.

Therefore, given two siblings experiencing the same microsystem, it is not impossible for the development of them to progress in different manners. Each child’s particular personality traits, such as temperament, which is influenced by unique genetic and biological factors, ultimately have a hand in how he/she is treated by others.

The Mesosystem

The mesosystem encompasses the interaction of the different microsystems which children find themselves in. It is, in essence, a system of microsystems and as such, involves linkages between home and school, between peer group and family, and between family and community.

According to Bronfenbrenner’s ecological theory, if a child’s parents are actively involved in the friendships of their child, for example they invite their child’s friends over to their house from time to time and spend time with them, then the child’s development is affected positively through harmony and like-mindedness.

However, if the child’s parents dislike their child’s peers and openly criticize them, the child will experience disequilibrium and conflicting emotions, which will likely lead to negative development.

The Exosystem

The exosystem in Bronfenbrenner’s ecological model pertains to the linkages that may exist between two or more settings, one of which may not contain the developing children but affect them indirectly nonetheless.

Based on Bronfenbrenner’s findings, people and places that children may not directly interact with may still have an impact on their lives. Such places and people may include the parents’ workplaces, extended family members, and the neighborhood the children live in.

For example, a father who is continually passed up for promotion by an indifferent boss at the workplace may take it out on his children and mistreat them at home. This will have a negative impact on the child’s development.

The Macrosystem

The macrosystem in Bronfenbrenner’s ecological model is the largest and most distant collection of people and places to the children that still have significant influences on them. This ecological system is composed of the children’s cultural patterns and values, specifically their dominant beliefs and ideas, as well as political and economic systems.

For example, children in war-torn areas will experience a different kind of development than children in a peaceful environment.

The Chronosystem

The chronosystem adds the useful dimension of time to Bronfenbrenner’s ecological systems theory. It demonstrates the influence of both change and constancy in the children’s environments. The chronosystem may include a change in family structure, address, parents’ employment status, as well as immense society changes such as economic cycles and wars.

Application of Bronfenbrenner’s Ecological Systems Theory

Through the various ecological systems, Bronfenbrenner’s theory demonstrates the diversity of interrelated influences on child development. Awareness of the contexts that children are in can sensitize us to variations in the way children may act in different settings.

For example, a child who frequently bullies smaller children at school may portray the role of a terrified victim at home. Due to these variations, adults who are concerned with the care of a particular child should pay close attention to his/her behavior in different settings, as well as to the quality and type of connections that exist between these settings.

How to cite this post: What is Bronfenbrenner’s Ecological Systems Theory?. (2019, May 3). The Psychology Notes Headquarters. https://www.psychologynoteshq.com/bronfenbrenner-ecological-theory/

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Categories: Developmental Psychology

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Very useful overview of Bronfenbrenner, thank you

You’re very welcome.

How would I cite this information APA format?

Please refer to this website: http://www.bibme.org/citation-guide/apa/website

Hope this helps, A

What is the date of this pulblication

The post was originally published in November 2013.

Very educative indeed…

when was this article published and by who, need it for reference purposes

This does not help. Who is the author of these words?

The articles and diagrams on this website are written/created by our team of writers. If you use the content on this website, you MUST provide appropriate credit. Please see here on how to cite the content on this website.

Hi, just trying to find out who wrote this article (Author)?

Can you explain the important of studying bronfenbrenner ecology tk an ecd teacher

Use the site as the author e.g. for in-text citations (The Psychology Notes Headquarters, 2011). Seeing as this information isn’t peer-reviewed I probably wouldn’t cite it as anyone could have written it.

Good advice!

I have a couple of questions: – who is the author of this article? – I note you list copyright on the diagram demonstrating the model. Is this your original work? What Bronfenbrenner source did you use to create it?

Good morning,

I have to submit a task on Bronfenbrenner and appreciate your notes – it really helps. May I know who the author is for proper reference? Or will it be Psychology Notes HQ?

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Article Contents

The conceptual model, the role of quantitative models in ecological research, when should a quantitative model be developed, building quantitative ecological models, nuts and bolts of assembling a quantitative ecological model, deterministic or stochastic, a way forward, acknowledgments, references cited, common pitfalls and potential solutions, decisions about model implementations.

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An Introduction to the Practice of Ecological Modeling

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Leland J. Jackson, Anett S. Trebitz, Kathryn L. Cottingham, An Introduction to the Practice of Ecological Modeling, BioScience , Volume 50, Issue 8, August 2000, Pages 694–706, https://doi.org/10.1641/0006-3568(2000)050[0694:AITTPO]2.0.CO;2

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Modeling has become an important tool in the study of ecological systems, as a scan of the table of contents of any major ecological journal makes abundantly clear. A number of books have recently been published that provide excellent advice on model construction, building, and use (e.g., Gotelli 1995 , Gurney and Nisbet 1998 , Roughgarden 1998 ) and add to the classic literature on modeling ecological systems and their dynamics (e.g., Maynard Smith 1974 , Nisbet and Gurney 1982 ). Unfortunately, however, littleany—of this growing literature on ecological modeling addresses the motivation to model and the initial stages of the modeling process, information that beginning students would find useful.

Fast computers and graphical software packages have removed much of the drudgery of creating models with a programming language and opened new avenues of model construction, use, and even misuse. There are many reasons why a student might want to consider modeling as a component of his or her education. Models provide an opportunity to explore ideas regarding ecological systems that it may not be possible to field-test for logistical, political, or financial reasons. Often, learning occurs from apparently strange results and unexpected surprises. The process of formulating an ecological model is extremely helpful for organizing one's thinking, bringing hidden assumptions to light, and identifying data needs. More and more, students want to “do something” with modeling but are not sure how to get started.

The goals of this article are to outline issues concerning the value of ecological models and some possible motivations for modeling, and to provide an entry point to the established modeling literature so that those who are beginning to think about using models in their research can integrate modeling usefully. We therefore envision the typical reader to be an advanced undergraduate, a beginning graduate student, or a new modeler. We first consider some of the values of models and the motivation for modeling. We then discuss the steps involved in developing a model from an initial idea to something that is implemented on a computer, outlining some of the decisions that must be made along the way. Many excellent texts and journal articles deal with the technical details of models and model construction; we do not attempt to replace this literature, but rather try to make the reader aware of the issues that must be considered and point to some of the sources we have found particularly useful.

We begin with the assumption that the reader has decided that he or she would like to “do something” with modeling as part of his or her research (Figure 1) . It is important to recognize the difference between models and the modeling process. A model is a representation of a particular thing, idea, or condition. Models can be as simple as a verbal statement about a subject or two boxes connected by an arrow to represent some relationship. Alternatively, models can be extremely complex and detailed, such as a mathematical description of the pathways of nitrogen transformations within ecosystems. The modeling process is the series of steps taken to convert an idea first into a conceptual model and then into a quantitative model. Because part of what ecologists do is revise hypotheses and collect new data, the model and the view of nature that it represents often undergo many changes from the initial conception to what is deemed the final product.

The discussion that follows is organized to consider issues in a sequence similar to what a new modeler would encounter. Because individuals' backgrounds differ, the sequence is not fixed. We map one possible route through the sorts of decisions that will most likely need to be considered; this course is derived from our individual experiences plus the collective knowledge of our reviewers. We begin with conceptual models because many people, even self-labeled nonmodelers, formulate conceptual models.

The development of a conceptual model can be an integral part of designing and carrying out any research project. Conceptual models are generally written as diagrams with boxes and arrows, thereby providing a compact, visual statement of a research problem that helps determine the questions to ask and the part of the system to study. The boxes represent state variables , which describe the state or condition of the ecosystem components. The arrows illustrate relationships among state variables, such as the movement of materials and energy (called flows ) or ecological interactions (e.g., competition). Shoemaker (1977) provides an excellent discussion about how to develop conceptual models.

The development of a conceptual model is an iterative process. The skeleton of a conceptual model begins to take shape when a general research question is formulated. For example, suppose the goal of a research project is to determine the relationship between different strategies for stocking exotic salmon in the Great Lakes and the concentrations of potentially toxic contaminants in the salmon and their alewife prey. The initial conceptual model might consist of two linked boxes labeled “alewife” and “chinook salmon,” with an additional arrow labeled “stocking” pointing to the salmon's box (Figure 2a) . We have chosen to place two-way arrows between the boxes to reflect the flow of biomass and contaminants from alewife to salmon and the effect of salmon on the alewife; an alternative model might have used only one arrow, since the flow of material between boxes is the result of predation by salmon on alewife. Details would then be added to the conceptual model based on the answers to questions such as, Are there other important species besides alewife and chinook salmon? What mechanistic processes should be included? What environmental factors influence each species? What currency should be used to describe compartment interactions (e.g., elements, biomass, individuals, energy)?

After making refinements driven by such questions, the conceptual model might have alewife, chinook salmon, rainbow smelt, and lake trout (Figure 2b) , although the research interest might still be with the original two species. The next round of refinements to the conceptual model might be based on available data or consultation with ecologists who have studied the interactions of the four species shown in Figure 2b . For example, if contaminant concentrations are a function of prey body size, and if predators seek certain size classes of prey, then size structure might be added to the model to more accurately reflect these ecological features and to better simulate contaminant intake by predators (Figure 2c) . Depending on the nature of the research question, the addition of size structure might be made for just the alewife and chinook salmon. This simple example assumes that there are changes only in the state variables, but there could also be changes in the relationships among the state variables.

In general, a parsimonious approach is best for creating an appropriate conceptual model. The model should strike a balance between incorporating enough detail to capture the necessary ecological structure and processes and being simple enough to be useful in generating hypotheses and organizing one's thoughts. Creating a good conceptual model forces an ecologist to formulate hypotheses, determine what data are available and what data are needed, and assess the degree of understanding about key components of the system. Because outside viewpoints and questions often force clarification of biases and assumptions, discussing the evolving conceptual model with colleagues can be helpful. Group construction of a conceptual model can also be a useful consensus-building tool in collaborative research ( Walters 1986 , Carpenter 1992 ). Conceptual models should therefore be included in dissertation and grant proposals, especially in the early stages of project development. Revisions of the initial conceptual model then become focal points for discussion in subsequent meetings of the dissertation committee or research planning group.

A quantitative model is a set of mathematical expressions for which coefficients and data have been attached to the boxes and arrows of conceptual models; with those coefficients and data in place, predictions can be made for the value of state variables under particular circumstances. Ecologists use quantitative models for various purposes, including explaining existing data, formulating predictions, and guiding research. Simple quantitative models can be solved with pencil and paper (see mathematical ecology textbooks such as Pielou 1977 , Hallam and Levin 1986 , and Edelstein-Keshet 1988 ), but most ecological models are now implemented on a computer.

Quantitative ecological models can guide research in a number of ways. Constructing a quantitative model and running simulations may help in the design of experiments ( Carpenter 1989 , Hilborn and Mangel 1997 ), for example, to evaluate experimental power for different hypothesized effect sizes. Sensitivity analysis of a quantitative model can reveal which processes and coefficients have the most influence on observed results and therefore suggest how to prioritize sampling efforts. Quantitative models can even be used to generate “surrogate” data on which to test potential environmental indicators or evaluate potential sampling schemes. Most important, quantitative models translate ecological hypotheses into predictions that can be evaluated in light of existing or new data.

Ecologists often use quantitative models to formulate predictions about the systems they study. Some predictive models are empirical, meaning that they represent relationships determined strictly by data. Because empirical models are not based on a knowledge of underlying mechanisms, they are most useful within the bounds of the data with which they are developed ( Weiner 1995 ). A well-known empirical model from aquatic ecology predicts the level of summer chlorophyll from spring total phosphorus ( Dillon and Rigler 1974 ). Other predictive models are more mechanistic, based on hypotheses about the particular ecological processes that cause an observed pattern. The incorporation of key ecological features, such as size-selective predation and increasing contaminant concentrations with increasing prey body size (to use an example similar to that in Figure 2 ), leads to the prediction of a tradeoff between decreasing concentrations of PCBs in salmon and the probability of survival of salmon prey (Figure 3; Jackson 1997 ). In the absence of these mechanistic ecological details, lower contaminant concentrations are predicted in predators ( Jackson 1996a , 1996b ).

Predictive models can become quite complex, especially when their forecasts are used as the basis for resource management and policy decisions. Examples include global climate models, fisheries management models for setting catch and harvest quotas, watershed management models for nutrient control strategies, and risk assessment models for environmental engineering. Often, these complex predictive models are used to generate predictions for scenarios for which actual tests are difficult or impossible to run for ecological, social, or economic reasons.

Like a conceptual model, a quantitative model is rarely an end in itself. Often learning results from considering a changing suite of several quantitative models, or several formulations of processes within a particular model ( Pascual et al. 1997 ). The assessment of different models and processes allows an evaluation of the assumptions specific to those formulations and processes. In this context, it is useful to remember that models are only tools and not reality, and there is no “correct” model.

Models should follow from specific research questions rather than questions following from models. Thus, the decision to build a quantitative model from a conceptual model should occur only after a clear, focused research question has been distilled from initial ideas. A full-scale quantitative model should be created only when each of the following questions can be answered with a yes:

Will a quantitative model add to the scientific content of the study?

Is there sufficient motivation to devote the necessary time to develop a quantitative model?

Will the investment in modeling enhance the quality of knowledge produced?

There are clear advantages to the incorporation of quantitative modeling in a research program. We have already touched on some of these benefits, such as formulating predictions and identifying data needs or knowledge gaps. Models are also useful for organizing one's thinking about a problem. Once a conceptual model is converted to a quantitative model and used, new questions may arise as a result of interesting and unexpected results. However, the time it takes to build a useful quantitative model should not be underestimated. Model building becomes easier with practice, but modelers should expect to spend several weeks or months constructing, parameterizing, testing, and running a modestly complex model. (The time spent depends to some degree on the software used, which is discussed more below.)

Once an ecologist has decided to build a quantitative model, how should he or she choose the type of model to build? Some general classes of models used in ecology include energy and mass balance models (e.g., Hewett 1989 ), population genetics models (e.g., Roughgarden 1979 ), optimization and game theory models (e.g., Mangel and Clark 1988 ), individual-based population models (e.g., DeAngelis and Gross 1992 ), size- or age-structured population models (e.g., Caswell 1989 ), community and ecosystem models (e.g., Scavia and Robertson 1980 ), and landscape models (e.g., Baker 1989 ). Because the degree of detail varies widely within these broad categorizations (Table 1) , we recommend reading papers that discuss the merits of various modeling approaches (e.g., Levins 1966 , DeAngelis and Waterhouse 1987 , DeAngelis 1988 ). An overview of model types and formulations can also be obtained from a survey course in mathematical modeling, and we strongly recommend taking such a course as soon as the idea to “do something” with models arises. The specific types of models being considered may suggest further course work. For example, differential equations are used in many models, matrix algebra underlies size- and age-structured models, and geographical information systems (GIS) are needed to work with many spatial and metapopulation models.

The choice of model type and detail will depend on the system studied, the questions asked, and the data available. Quantitative models can quickly become complex and clear problem definition is essential to keeping the model focused. A good conceptual model is invaluable for deciding what ecological detail to include and what to ignore. For example, suppose an ecologist is studying two forest stands: One stand is intact, whereas a presumedly important seed disperser has been removed from the other. Has the removal of the seed-dispersing animal caused any changes in the population of a particular tree species in the experimental stand? There are several ways in which quantitative modeling can be used to address this question. A simple age-structured model (e.g., Caswell 1989 ) of the tree population may be useful if the ecologist wants to look for changes in age structure. Alternatively, a spatially explicit model might be needed if the ecologist wants to explore differences in spatial pattern. If the ultimate goal is to test the findings from the quantitative model in the field, then the model that is developed will dictate the types of data that will need to be collected from the two forest stands.

Once the general type of quantitative model has been chosen, the ecologist must determine the appropriate level of abstraction for the model. Consulting papers on the value of simple ( Fagerström 1987 , Scheffer and Beets 1993 ) versus complex ( Logan 1994 ) models may help guide this decision. Good models never include all possible compartments and interactions ( Fagerström 1987 , Starfield 1997 ), and the complexity of a model depends very much on the purpose and question addressed by the model. There are tradeoffs between the generality of a model and its practical utility for a particular situation ( Levins 1966 ). A highly abstract model with few parameters may be best to test general ecological hypotheses. However, for specific questions, such as whether changes in fire frequency have affected the spatial pattern of a species, a detailed spatial model coupled to GIS data may be required. Thus, a model's structure should be consistent with both the question(s) asked and the measurements made ( Costanza and Sklar 1985 , Ludwig and Walters 1985 , DeAngelis et al. 1990 ). Data for many populations are collected by size or developmental stage or at fixed time intervals, leading naturally to models with size or stage structure and certain time steps (see the box on page 700 for more on time steps). With too little detail in the model, the mechanisms driving the response of interest may not be captured. On the other hand, too much detail makes a model difficult to parameterize (determine coefficients for equations) and to validate ( Beck 1983 , Ludwig and Walters 1985 , DeAngelis et al. 1990 ). An active area of research therefore considers how to reduce model complexity while retaining essential system behavior ( Rastetter et al. 1992 , Cale 1995 ).

Once the decision to build a quantitative model has been made, and issues of model complexity and structure have been dealt with, it is necessary to develop algebraic formulations (equations) for model processes, to establish means for solving them, and to choose parameters for each equation before implementing the model on a computer. Thinking about these issues in advance may save a modeler from having to go back and redevelop portions of the model.

The importance of keeping good notes

The litmus test for a model description is that a relatively experienced modeler must be able to reproduce the model and its output, just as experiments should be capable of being replicated. Therefore, it is important to document decisions about equation forms, parameter values, and computational details, as well as any sources of information used to make these decisions. Good notes taken during model building will save hours combing the literature to rediscover the source of assumptions or parameter values.

Choosing equations

One of the initial steps in converting a conceptual model to a quantitative model involves quantifying the arrows between the state variables. This process actually involves two steps: choosing appropriate equations and determining the parameters for those equations. Equations represent mathematically the interactions among or transfers of energy or materials between state variables in a model. For example, equations 1 , 2 , and 3 represented different (hypothesized) ways to describe the process of predator consumption. Parameters are constants in the equations that make the algebraic expressions correspond to actual data.

Equations appropriate to a particular situation may be available in the literature. Certain constructs (e.g., feeding relationships, energetic equations) are common to many ecological models, although they may need to be reparameterized for different systems. Many relationships can be found in modeling textbooks, including Models in Ecology ( Maynard Smith 1974 ), Ecological Implications of Body Size ( Peters 1983 ), Handbook of Ecological Parameters and Ecotoxicology ( Jorgensen et al. 1991 ), Dynamics of Nutrient Cycling and Food Webs ( DeAngelis 1992 ), A Primer of Ecology ( Gotelli 1995 ), and Primer of Ecological Theory ( Roughgarden 1998 ). First principles (i.e., physical laws) can also provide useful relationships. Mathematically important differences among alternative formulations may or may not be important for a particular situation. If the particular form of an equation is of concern, the effects of each formulation on model results can be explored as part of the modeling exercise.

Computational issues associated with equations

Difference equations are simply solved by recursion; that is, later predictions depend on earlier predictions. Differential equations describe continuous processes, but must nevertheless be solved in discrete time steps on a computer. The two principal methods used to solve differential equations are the Euler and the Runge-Kutta methods. The Euler method steps through the differential equation as if it were a difference equation by using information at the beginning of each time interval to calculate values at the next time interval. The Euler method can be unstable when the interval between solutions (the step size) is small, because rapid accumulation of errors prevents convergence on the real solution. The Euler method may also be unstable at large step sizes because small changes in rates and local maxima and minima in the solution may be missed, which can be particularly problematic if the differential equations are nonlinear ( Press et al. 1992 ). Runge-Kutta algorithms also start with the information at the beginning of a time interval but then sample the solution at several points between the beginning and end of the interval. For most differential equation models, the Runge-Kutta is more accurate than the Euler method, and fourth-order Runge-Kutta is particularly recommended ( Press et al. 1992 ). Graphical and algebraic explanations of the Euler and Runge-Kutta algorithms appear in Press et al. (1992 ) and in textbooks on numeric methods in computing (e.g., Atkinson 1989 ). Variable step-size methods can be used to find the optimum balance between accuracy and computational speed by using small step sizes when variables are rapidly changing and long step sizes when variables are changing slowly.

A deterministic model has no random components; for the same initial conditions and time period projected, it always gives the same result. In contrast, a stochastic model incorporates at least one random factor, and thus the results are different every time the model is run. One type of stochastic model assumes that the values of some or all parameters vary through time or across individuals and are therefore described by probability distributions. Each time the model is run, the parameter values are drawn from their specified probability distributions. Other stochastic models add random errors following each calculation to simulate the effects of environmental variability. One reason to add stochasticity is to produce realistic variability in the trajectories of the state variables through time, either because the variance as well as the average value is of interest or because the effect of variability in one state variable on another state variable is of interest. Model results might be cast in terms of probabilities—for example, as the percentage of simulations in which a certain outcome (such as a catastrophic population crash) was attained. A stochastic model is not necessarily more “correct” than a deterministic model, and it is more work to create. It does provide additional information, but whether this information is of value depends on the purpose of the model. We recommend Nisbet and Gurney (1982) as the starting point for an introduction to deterministic and stochastic models.

Selecting modeling software

Implementation of a quantitative model on a computer requires the modeler (or the computer program) to keep track of many details. Some of these details, while necessary for the model to run, are irrelevant to the model predictions (e.g., allocating computer memory for arrays and matrices, creating a user interface, and writing output). Other details, such as how variables are initialized, how random numbers are generated, the order in which equations are solved, and the algorithm (computer instructions) used for solving them, do affect the predictions. We discuss some of these details further in the boxes on FPAGE 697 and 699.

The computer software selected should be determined by the degree to which the modeler wishes to control these details. At one extreme are general programming languages (e.g., C, Basic, Fortran, Pascal) that allow the modeler complete control over the model construction but also require the modeler to handle all of the sometimes tedious details. Model building gets easier with practice and by reusing bits of previously generated code, but it can still be quite time-consuming even for relatively experienced programmers. Prewritten routines for random numbers, matrix algebra, and other algorithms are available for most programming languages, reducing the need to reinvent some wheels (e.g., Numerical Recipes; Press et al. 1992 ). If this option is chosen, coursework in at least one programming language might be helpful; general programming concepts and skills translate across languages.

At the other extreme are graphical programs (e.g., STELLA, SimuLink, ModelMaker) that allow the user to create the computer program (the model) by choosing icons from a menu while the software handles the details. Models can be constructed quickly, but there are limits on what can be built and the implementation details are often hidden from the user. This final point is a significant weakness of graphical modeling packages, and we therefore tend to create our own models using programming languages. However, intelligent use of modeling packages can permit incorporation of modeling into a study with far less effort than building a model from scratch.

Between these two extremes are programming packages that include functions to handle many of the details but still leave some control to the modeler (e.g., Matlab; see Roughgarden 1998 ) and spreadsheets (e.g., Excel; see Weldon 1999 ). This intermediate approach may appeal to those who want to know how equations are being solved without becoming mired in the syntax of a programming language.

Parameter estimation and model calibration

Parameter estimation is the process of finding parameter values for each equation in the quantitative model. The source of parameter values depends on how the model is going to be used. If the model is being developed to explore the consequences of different parameter values, then the model will be run for a wide range of different parameters without reference to particular ecological systems. However, if a model is being developed to predict behavior in a particular system, then usually a single (mean) value will be chosen for each parameter. In this case, parameter values are estimated by fitting equations to the data from the system, or perhaps from data available in the literature. Sometimes data are not available, in which case a modeler might estimate parameters by an iterative process of matching model output to observed system behavior. This latter practice is referred to as tuning (calibration) by direct search, and the parameters are altered until the model produces a reasonable fit with observations of the state variables. Tuning can be done systematically or by trial and error. Either way, keeping good notes is essential. Parameters determined by direct search are best viewed as hypotheses to be tested as data become available.

When parameters are estimated from observed data, the modeler seeks the parameters that lead to the best fit between an equation and the observed data (e.g., Hilborn and Mangel 1997 ). The least-squares criterion and maximum likelihood estimation are the two most commonly employed methods for this kind of parameter estimation. Least-squares estimates of parameters minimize the value of the squared deviations between the simulated and observed data; these estimates can be used for just about any deterministic component of a model for which distributions are near normal and variance is constant throughout the range of an independent variable ( Brown and Rothery 1993 ). However, for models that are nonlinear in the parameters, least squares may produce biased parameter estimates; for these models, maximum likelihood may yield better parameter estimates. Maximum likelihood algorithms determine the parameter values that maximize the probability that the observations would have occurred if the parameters were correct ( Hilborn and Walters 1992 ). Unlike least squares, maximum likelihood does not require that error terms be normally distributed ( Hilborn and Mangel 1997 ). It is beyond the scope of this article to review parameter estimation techniques, but useful information on that subject can be found in Draper and Smith (1981) , Hilborn and Walters (1992) , and Hilborn and Mangel (1997) .

Debugging, sensitivity analysis, and validation

Once a quantitative model is assembled, it must be tested to ensure that it is functioning properly; that process is called “debugging.” We recommend that the equations be calculated by hand to ensure that the code is performing as it should—that is, arrays and matrices are properly indexed, equations are properly calculated, and so forth. Each module or subroutine of a model developed with a programming language should be tested separately before the completed model is run. Output should be tabulated, state variables graphed, and intermediate parameter and rate values monitored to ensure that they are realistic during simulations. One also should check that the model behaves as expected in situations for which the analytical solution is known.

Sensitivity analysis explores whether the conclusions would change if the parameters, initial values, or equations were different. Consequently, sensitivity analyses can be used to guide further research (for example, to identify those parameters that would be worth the investment of additional field measurements or experiments), to corroborate the model, and to improve parameter estimates. There are three basic approaches to sensitivity analysis: varying parameter values one at a time, systematic sampling, and random sampling ( Hamby 1994 ). Swartzman and Kaluzny (1987) provide an excellent discussion of the advantages and disadvantages of each of these approaches. The simplest sensitivity analysis examines the effect of each parameter on model dynamics individually ( Bartell et al. 1986 ). The model is typically deemed sensitive to a particular parameter if changing that parameter's value by 10% leads to more than a 10% change in the output from the baseline scenario. Because analysis of one parameter at a time will not identify sensitive interactions among parameters, it may also be worthwhile to explore the effects of variation in two or more parameters at the same time using either systematic or random sampling ( Swartzman and Kaluzny 1987 ). When many parameters may interact, random sampling may be the best approach. Random sampling is most often done with Monte Carlo techniques (e.g., Swartzman and Kaluzny 1987 , Bartell et al. 1988 ), whereby, during each of perhaps 1000 model runs, a value for each parameter is “sampled” from a range or probability distribution. Model runs then undergo partial correlation analyses, which yield estimates of the contribution of each parameter to the overall variance in the output. Parameters with high partial correlations have the most influence on results.

In addition to doing a sensitivity analysis on parameter values, the model should be checked for sensitivity to initial conditions and equations. For example, the model can be initialized with different species ratios or size structures to find out whether output is driven by these choices. Model sensitivity to alternative equations for relationships among state variables can also be checked by rerunning the model with different equations and seeing whether the conclusions change.

Once a model works, the modeler may need to ask whether it sufficiently resembles reality, but whether that question can be answered at all is a matter of considerable philosophical debate ( Mankin et al. 1975 , Oreskes et al. 1994 , Rastetter 1996 , Rykiel 1996 ). Nevertheless, at some point the researcher must decide that the model is good enough and no more tinkering is necessary. For many system-specific ecological models, this decision is made based on comparisons of simulated data with field or experimental data. If the simulated data are sufficiently similar to the observed data, then the model is judged to be validated or corroborated, and simulations with the model proceed. If the simulated data do not match the observed data, then further work is necessary. Objective criteria for model validation include the standard error of model predictions and the proportion of variance explained by the model ( Caswell 1976 , Power 1993 ). It is preferable to have independent data for model corroboration and calibration, although in practice independent data are often hard to find, particularly for whole ecosystems.

Modeling offers exciting possibilities for the exploration of ideas that are not easily pursued through field experimentation or laboratory studies. Ecologists, for example, use models to simulate the systems they study and to investigate general theories of the way those systems operate. Moreover, simulation of systems with models helps identify data needs and knowledge gaps.

Many research programs can benefit from the integration and development of conceptual and quantitative models. The process of creating a conceptual model begins with a question; from there, the researcher formulates hypotheses, evaluates available and needed data, and assesses the degree of understanding of the system under consideration. Then the conceptual model is converted to a quantitative model; that process is iterative, evolving as new data and ideas are discovered.

We cannot possibly cover every aspect of ecological modeling—which is both a skill and a process—in one short article. We do hope, however, that we have successfully raised the issues that a beginning modeler must consider, provided an entry point to the modeling literature, and discussed the role of modeling in ecological research.

We thank Steve Carpenter for numerous suggestions during the writing of the manuscript. We are grateful to many people at the Center for Limnology, University of Wisconsin–Madison, for support during our model building years there (especially David Christensen, Xi He, Daniel Schindler, Craig Stow, and Rusty Wright). We thank Steve Carpenter, George Gertner, Lloyd Goldwasser, Bruce Kendall, Russell Kreis, Bill Nelson, John Nichols, Daniel Schindler, and, in particular, Rebecca Chasan, Wayne Getz, and an anonymous reviewer for their thoughtful reviews of the manuscript. L. J. J.'s research with simulation models was funded by the Natural Sciences and Engineering Research Council of Canada and by the Wisconsin Sea Grant Institute under grants from the National Sea Grant College Program, National Oceanic and Atmospheric Administration, US Department of Commerce, and from the State of Wisconsin (Federal grant NA90AA-D-SG469, project R/MW-41). K. L. C.'s initial research with simulation models was funded by a predoctoral fellowship from the National Science Foundation. K. L. C. also thanks the National Center for Ecological Analysis and Synthesis, which is funded by NSF (DEB94-21535); the University of California at Santa Barbara; and the State of California for financial and logistical support while preparing this paper for publication.

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This troubleshooting box outlines some common mistakes made during model construction. It is not an exhaustive list. We hope that the novice modeler will profit from our experience in solving these problems, which arise largely from writing one's own code in a programming language.

Pay careful attention to units, scaling, and conversions. For example, translating prey eaten by one trophic level (units of mass) to a mortality rate for another (numbers) requires a conversion and change of units. We go through our equations and write the dimensions and units to ensure that we are making appropriate conversions. Units and dimensions for empirically derived relationships tend to be built into regression parameters (e.g., ungulate biomass [kg] derived from grass productivity [g · m −2 · d −1 of carbon]). Problems often arise when different state variables operate on different spatial scales, which is sometimes less obvious than when the variabes operate on different time scales. Fish, for example, occupy a volume (g · m −3 ) but may eat benthic invertebrates that occupy a surface (g · m −2 ), requiring rescaling when computing trophic transfers. Apparent conversion problems can also be caused by failure to properly share variables among subroutines.

Be careful with time steps and model stability, especially for models with differential equations. The modeler typically must choose a single step size (e.g., hourly, daily, monthly, yearly) over which to have the algorithm solve the equations, even though the time step appropriate for evaluating one process (e.g., hourly nutrient uptake by phytoplankton) may not be appropriate for evaluating another (e.g., annual growth of fishes). Equations whose dynamics suffer when independent variables change on widely disparate time scales are known as “stiff” equations. Problems often occur because small roundoff or truncation errors in one variable lead to enormously inflated errors in another; such problems can be diagnosed by evaluating output variables at a variety of step sizes. An alternative approach to manually manipulating step size is to use an algorithm with an adaptive step size ( Press et al. 1992 ), which gives smoother dynamics but takes more work to program. One can also explicitly divide the model into “fast” and “slow” components and then update the fast components much more frequently than the slow components.

Pay attention to setting and resetting values. Arrays and matrices are a common source of computer bugs, thus warranting extra attention to their dimensioning, initializing, and indexing. We assign values to parameters before they are used rather than relying on the software to initialize them. We also check that parameters and initial conditions obtained from an input file are properly read and assigned. After the lapse of important time periods, we check that variables have been zeroed or renewed as appropriate. For example, in a model in which seed germination for a plant proceeds only when certain environmental conditions are met, the value for seedlings should be set to zero each time germination fails rather than (unintentionally) taking the value from the previous year. Similarly, when all individuals in a particular size or age class die or are eaten, the variables tracking their characteristics must be properly reset to prevent carryover effects when a new cohort arrives. Populations modeled with real numbers will approach but not equal zero when subjected to a constant mortality rate, and should be set to zero after some minimum population size is attained. Inspecting graphs of state variables will elucidate what is happening.

Test random number generators before using them. Random number generators vary in quality and should be tested before use. A statistics package can be used to analyze the results of 10,000 or so sequential random numbers to ensure that the mean, standard deviation, and distribution are as specified and the shape is as expected. If qualitatively different results occur when initializing the random number generator at the beginning of the program versus the beginning of each replicate, we look for another random number generator. We recommend reading Press et al.'s (1992 ) discussion of random-number generating algorithms. One way to keep random numbers the same from run to run, which is useful when developing or debugging a model, is to start each simulation with the same “seed” (the initial number from which the random numbers are generated). When the time comes to use different seeds, the computer's clock can be used for the seed value.

Issues concerning how numbers are stored and updated, how calculations are sequenced, and how inputs and outputs are made may seem unimportant to the novice modeler, but our experience is that computational details merit attention early in the modeling process because they can have substantial implications for model use and behavior.

The nature of inputs and outputs determines how easily a model is used and analyzed. If inputs are part of the model code, the model must be recompiled (translated from text into instructions the computer executes) each time the inputs are changed. If inputs are read in as a separate file (which takes more work to program), the model can be run many times with different inputs without recompiling. It is worth formatting output with the planned analysis in mind—select formats amenable to processing with statistical or graphics software. Excessive output slows the simulation time, but representative subsets of intermediate calculations should be inspected to ensure that everything is reasonable.

The sequence in which events proceed can affect results. Events that happen simultaneously in nature must occur in sequence in computer models. For example, if the organism or size class that is first in numerical order in a vector of state variables is always the first for which foraging is evaluated, it may unintentionally be the one that gets the most food!

Separating old from new values allows sequential calculations of simultaneous events to proceed correctly. Newly calculated values should be assigned to temporary variables so that subsequent calculations are not based on a mixture of old and new state variables. The value of the state variables should be updated with the values in the temporary variables only after all calculations have been completed for that time step.

Decide whether to model populations as whole or real numbers. Neither choice is perfect. Using real numbers gives fractions of individuals, whereas using integers presents stochasticity and rounding problems. For example, if the number of survivors is calculated by multiplying the survival rate by the number of starting individuals and then rounding to the nearest integer, then a single individual with a survival rate of 0.8 will live forever! It would be better to use 0.8 as a probability and then do the equivalent of flipping a coin—that is, draw a random number.

Decide how many stability checks and assurances to build into a model. The inherent mathematical and architectural constraints of computers can lead to unexpected model behavior ( Acton 1996 ). It is important to anticipate both mathematically illegal operations (e.g., division by zero) that would cause the simulation to crash and circumstances that would cause the simulation to become invalid. For example, it might be appropriate to stop the simulation if one species in a multispecies model goes extinct, to build in a means for its reestablishment if it goes extinct, or to build in a refuge or alternate food supply so that extinction is prevented. These types of stability guarantees should be used prudently. Excessive stabilizing components can hide programming errors or even dominate model dynamics; on the other hand, if used sparingly, they can prevent the frustration of having a long simulation rendered useless by a circumstance for which a stability check could easily have been programmed.

Table 1. Ecological models for representing populations

Figure 1. Flow chart summarizing the process of creating an ecological simulation model. The model building process distills current knowledge into a conceptual framework, which forms the scaffolding for the model's construction. A number of steps involve iterations or refinements that follow from consulting data, experienced modelers, or other ecologists. Once there is output from the model, the original idea or state of knowledge may be modified and additional model refinements, data collection or experiments might be planned. Benefits of the modeling process include eliminating alternatives, identifying gaps in knowledge, identifying testable hypotheses, and indicating avenues for additional experimentation and data collection

Figure 2. Example of the iterative nature of building a conceptual model from an initial idea. The first iteration (a) describes a simple relationship between one predator and prey. One arrow identifies biomass and contaminants as the material flowing from alewife to chinook salmon, and the other arrow identifies predation as an important ecological process structuring the alewife population. In this example, interest is in how the rate at which salmon are stocked affects the relationship between salmon and alewife. Additional information at the second iteration might indicate that the dynamics of the salmon and alewife (a) are also affected by rainbow smelt and lake trout, which are subsequently incorporated into the conceptual model (b). Finally, information on contaminant concentrations as a function of body size and more detail on predator preference of prey might indicate that age or size structure should be included (c). Depending on the goal of the modeling exercise, detailed age structure might be examined for the original two species of interest. In b and c, the double-headed arrows indicate state variables that directly interact. In c, the wide gray arrows represent the movement of fish to older age classes. Box labels represent the age of fish; YOY are young-of-year. Two quantitative models might be constructed: one for conceptual model b and one for conceptual model c

Figure 3. PCB concentrations (solid line) of age class 4+ chinook salmon and the probability of an alewife population crash (dashed line) for chinook salmon stocking rates and a Shepherd stock-recruitment relationship. PCB concentrations are the result of 200 model runs to year 2015, at each stocking rate, based on bootstrapped estimates of the Shepherd stock-recruitment relationship from 14 years of data for Lake Ontario. The arrow indicates 1994 stocking rates. The dotted line around the chinook salmon PCB concentrations represents +/− 2 SE

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Bronfenbrenner’s Ecological Theory Essay Example

Bronfenbrenner’s ecological theory does not focus on stages of human development but instead focuses on influences from social environments. This theory focuses on five interrelated systems. These systems are the microsystem, mesosystem, exosystem, macrosystem, and chronosystem. (Bronfenbrenner, 2005). The microsystem is a human’s immediate environment. It is what makes up their everyday lives. This means a human’s family, friends, classmates, coworkers, and even teachers. The second system that influences a human’s development is called the mesosystem. This system is the interactions between microsystems. The way a child is being treated in one microsystem may influence how they act in another. The Exosystem is made up of social institutions. These institutions include schools, media, and religious institutions and have an indirect influence on development. The macrosystem is the system of cultural beliefs and values. This also includes government systems that are built on beliefs and values such as in the middle east. The last system in Bronfenbrenner’s theory is the chronosystem. This system is the changes that happen over time. This includes an individual’s development and historical changes. The biggest thing Bronfenbrenner emphasized about his theory of development is that humans are active participants in their development. This means that a person may affect other people’s behaviors and vice versa. (Bronfenbrenner & Morris, 1998).

Mackenna’s language development goes along with Bronfenbrenner’s ecological theory. Although Mackenna is only three years old and in the toddler development stage, this theory specifically the microsystem is already consistent with her development. Mackenna is mostly with adults. These adults include her parents, grandparents, aunts, uncles, and her parents’ friends. As mentioned previously mentioned in part two observation and analysis project, being around these adults, makes for a language-rich environment (Weislender & Fernald, 2013).  These adults do not water down grammar when they talk to Mackenna but instead talk in paragraphs. This has led to an advancement in Mackenna’s language as she already talks in paragraphs and knows how to use prepositions. She does sometimes overregulate but this can display just how much development Mackenna is going through (Arnett & Jensen, 2019). This is evident in the fact that Mackenna does not overregulate all her verbs. 

In the future, Mackenna’s language development according to this theory will reflect the systems she is associated with. As she goes to school (this deals with the mesosystem and exosystems) she will learn different ways people talk. The first is other children may teach her different ways to say a verb. An example of this may be a child using African American Vernacular English who may say, “I ain’t doing anything.” Mackenna may pick up this phrase. She will be taught grammar rules by her teachers. This will influence the grammar that will be displayed in her speech. Specifically, it will most likely make overregulation extinct in her speech.  Her language will also be influenced by media, including books. This will also expand her language (Fitneva & Matsui, 2015)

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Resources: Discussions and Assignments

Module 2 assignment: bioecological model journal.

STEP 1 : Think of yourself at a particular time in your childhood (e.g., age 10). Use the following prompts to help you write a journal entry about your childhood experiences as seen through Urie Bronfenbrenner’s bioecological model. Write you answers as a personal reflection paper, in paragraph form, between 400-600 words.

Microsystem

• your parents:
• your siblings:
• your peers:
• your school and teacher:
• how your parents interacted with your school and helped with schoolwork:
• how your parents interacted with your peers:
• how your community interacted with your family/peers:
• how your religious background influenced your family:
• your parents’ jobs and socioeconomic status:
• how your family explored or interacted with the world beyond your community (e.g., vacations, travel sports, mission trips, etc.):
• popular media—television, music, movies, social media:
• any interactions with social services:
• the economic condition of your community:
• the history and values of your community:

Macrosystem

• what was going on in the world at the time (e.g., Hurricane Katrina, who was president, etc.):
• technological advancements:
• national or international cultural values (e.g., racial diversity, gender equality, etc.):

Chronosystem

• major life transitions (such as the birth or death of a sibling):
• major world events that changed history at that time (e.g., terrorist attacks, presidential elections, wars, etc.):
• more gradual historical changes (the history of transgender people in the United States or the change in the number of women in the workplace):

STEP 2 : Submit your paper.

• Authored by : Nancee Ott. License : CC BY: Attribution
• Modification, adaptation, and original content. Authored by : Sonja Ann Miller for Lumen Learning. Provided by : Lumen Learning. License : CC BY: Attribution

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The Bioecological Model

Exploring how children’s relationships and environment interact to help them thrive., what is the bioecological model.

The bioecological model is based on the idea that the relationships children have with parents and caregivers impacts their development – and that these relationships are affected by their work, school, and community settings, which are in turn affected by broader social, cultural, and policy conditions. These many layers of relationships and environments interact with each other – ultimately influencing how children develop and become resilient. This theory of human development was originally proposed by Urie Bronfenbrenner and Stephen J. Ceci in 1994.

How we use the model at CCFW

The “bioecological” or “whole child” model sits at the core of our approach. We recognize the roles that individuals, families, communities and society play in influencing children’s development, and engage the whole community to support their resilience. Grounded in research, our programs share  social-emotional skills, mindfulness, and compassion practices with parents, caregivers, educators, and practitioners – to support well-being for all.

Child & Youth Well-Being and Resilience

Through our research, we examine interdependent systems that support child and youth well-being, including mental and physical health, social and emotional adjustment, physiological stress responses and academic achievement. 

Parent & Family Well-Being

We know that parents and families play a critical role in supporting children’s social, emotional and behavioral well-being, and their ability to develop resilience. We support these relationships by studying and sharing effective parenting practices based in mindfulness and self-compassion.  

Supportive school, work and family environments

We’ve observed how families become resilient when they can draw on support from extended family, teachers, employers and care providers. We engage this network of supportive individuals and systems by sharing evidence-based trainings, workshops and tools.

Neighborhoods and communities

Through our research, we examine the effects of different kinds of adversities (such as social inequity, crime, economic status, and pollution) on neighborhoods and communities, and how these factors impact children’s well-being. Our findings are translated into culturally-informed programs and resources co-created with communities that experience inequity and adversity.

Social, economic and cultural contexts and policies

To thrive, all children and families need stable housing, food security, economic opportunity, freedom from violence and hate, health and mental health care, high-quality child-care and education. While our work focuses on supporting the social-emotional well-being of children and the adults in their lives, we situate our work in a recognition of and advocacy for safe, stable, nurturing relationships and contexts. We aim to inform policy by responsibly sharing current research in a variety of ways and convening “Research to Real World” forums that align policymakers, philanthropists, and practitioners around shared evidence-based efforts.

Essay about Bronfenbrenner’s Ecological Systems Theory

A child’s development is affected by their social relationships and the world around them. The ecological systems theory introduced by Urie Brofenbrenner (1979) focuses on the development of a person within the ecological environment, outlining and explaining the complex relationship and exchange between the infant, the family and society, and how these exchanges impact upon child development.

Bronfenbrenner challenges previous understandings on how children develop and within his model, identifies a hierarchy of influence levels that impact on child development including the Microsystem, the Mesosystem, the Exosystem and the Macrosystem. This essay provides an introduction to and explanatory on Brofenbrenners theory whilst referencing the author’s own childhood development in the context of opportunities and risks. “A child’s well-being is an essential foundation for early learning, and all subsequent learning” (NCCA 2004).

Development occurs through the process of progressively more complex exchanges between a child and its environment, with Bronfenbrenner describing the ecological environment as a “set of nested structures, each inside the next like a set of Russian dolls” (Bronfenbrenner 1979). The ecological theory explains that an individual will encounter different environments throughout their lifespan, and that it is the interrelationship between the child and the environment that may influence their behavior to varying degrees.

An example of this is a child’s parents affecting their beliefs and behaviours whilst at the same time, the child affecting the parents’ in return. As such, each child’s ecological model is unique and has different environmental influences. The first system within the theory is the Microsystem. This is widely considered the most influential level of the Ecological Systems Theory and is the setting in which an individual lives and where most of their direct interactions occur. As the child ages, the Microsystem becomes more complex and involves a greater number of people such as childcare centers or pre-school.

The Microsystem comprises ‘a pattern of activities, roles and interpersonal relations experienced by the developing person in a given setting with particular physical and material characteristics’ (Bronfenbrenner 1979). Family, peers and school are all examples of the type of interactions that populate this system. Bronfenbrenner’s theory explains that an individual is not a passive recipient of experiences in these settings, with relationships being bidirectional. A child’s interactions with them determine what is possible and what is not.

Their responses to the environment they create, personal preferences and genetics dictate the possibilities of what a child might become as “microsystems evolve and develop much as adolescents themselves do from forces within and without” (Garbarino 1985). The importance of a baby’s attachments to their parents (mothers and fathers) has long been acknowledged (Bowlby, 1988), with the experience young babies have of forming relationships crucial in that it can influence all future relationships (Perry, 1995; Karr-Morse and Wiley, 1997).

As adoptive children may experience difficulties with behavioral and emotional control, the establishment of positive family relationships can be challenging (Brodzinsky & Pinderhughes 2002). Parental responses are linked to their own experiences from childhood and can determine the quality of current parent-child relationships and parenting styles (Howard, 2011; Newland, Freeman, & Coyle, 2011). Garbarino states that to develop a sense of self”adolescents need warm, responsive and active ‘partners”(Garbarino 1985).

As an adopted child who was emotionally reactive to the adoptive process, and having been placed in a family who were emotionally unable or unwilling, due to limited experience and understanding, to interact in a way that fostered a positive parent rapport and therefore develop a healthy relationship, this had a negative affect on my development as it lead to increased emotional unresponsiveness in my broader relationships, and negative self-evaluation (Garbarino 1985).

However, the development of independence from my family structure in response to the situation, led to an increase in my resilience which was developmentally positive as “resilient children are better equipped to resist stress and adversity, cope with change and uncertainty, and to recover faster and more completed from traumatic event or episodes” (Newman and Blackburn (2002). The next level of the ecological theory is the Mesosystem.

The Mesosystem consists of the interactions between the different parts of a child’s Microsystem, and therefore essentially represents the connections between the Microsystems. Keenan and Evans (2009) state “one could think about the mesosystem as the connections which bring together the different contexts in which a child develops”. Therefore, whilst the “proximal processes within the family are considered within ecological theory to be the primary mechanism of development, links between contexts in which the child participates also affect development trajectories” (Schweiger & O’Brien 2005).

The examination of the Mesosystem can be viewed as important to the understanding of family relationships, as a child’s experience in other contexts away from the family structure can alter their perceptions and ultimately influence the way that they interact with their parent and siblings (Schweiger & O’Brien 2005). A positive effect a Mesosystem can have on a child can be seen through the opportunities it creates to provide social support and consistency in its daily activities.

My adoptive father was a sergeant in the army. A common way for army families to bond and socialise when the regiment was on base outside of training periods, was for communal barbeques and parties to be held. This allowed me to come into contact with different mesosystems in new settings, and showed then when together, my adopted parents were united in raising me. However, Mesosystems also have the potential to cause stress for the child.

As an adopted child who has had access to and contact with my biological family, including siblings and other relatives, these interactions have been difficult and have affected my relationship with my adoptive parents even though they did not actively participate in the interactions. An example of this is the abandonment feelings that surface when interacting with my biological family and the expressions of anger and resentment that impacts on my adoptive parents through my negative behavior and emotional state which was sometimes directed at them.

This is the direct result of two microsystems coming together, and my feelings of being placed in a situation where | felt I had to play multiple roles at once. Beyond the Microsystem and Mesosystem, Bronfenbrenners system is expanded to include environmental factors that are less direct in a child’s life. The Exosystem is a setting that does not involve the child as an active participant, but structures existing within it can be see to indirectly impact upon them. As an adopted child, it is arguable that these outer systems are more important and influential than the microsystem.

The affects on an adopted child can be seen in greater detail through social services interventions in their life. Adoption is the choice of an individual/s to parent children who are biologically unrelated to them. The system of social services is engaged when establishing a legal parent-child relationship, and the ecological theory highlights the importance of the experiences between social workers and therapists in terms of how the experiences might affect the child (Schweiger & O’Brien 2005).

My adoptive parents’ experiences with social services were quite negative and challenging. When choosing to foster additional children this caused them to relive previous experiences and emotions and caused tension in the household. As a result this caused negative affects between me and my adopted parents as my views as a child hearing various comments and witnessing their behavior both pre and post social services meetings was that the adoption and fostering processes was a burden, and that I as the central factor was the cause of their problems.

It has also impacted on my beliefs and attitudes towards adoption and fostering as a whole, and my beliefs and attitudes towards them. The Macrosystem includes the belief systems or ideologies that inform cultures or sub-cultures. It is the overall culture that the child is involved in, and can include Australian culture. The ecological systems theory “emphasizes the impact that the wider society has on how families function and view themselves” (Schweiger & O’Brien 2005).

Traditional family preservation views and the stigma that is arguably still attached to the concept of adoption are all pressures and messages from the outer systems that influence a child’s own perception on who they are and what there identity is. All the levels in Bronfenbrenners Ecological Systems Theory play an important roll in the wellbeing of children and families. In concluding I have evidenced the complexity of Bronfenbrenners Ecological theory, whilst highlighting that

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Child Development: An Active Learning Approach

Student resources, discussion questions.

• Think about your own development of self-concept. Use Bronfenbrenner’s Ecological Theory to discuss the influences of each level on your development of self-concept.  
• Do you have experience around young children?  What behaviors have you witnessed that exemplify content from chapter 11?  
• Think about your experience as an adolescent.  Did you go through many identities? What was your experience? Relate it to chapter 11’s content.  
• Did you experience a rite of passage? Discuss.  
• Provide an example description of a child in each of Marcia’s identity statuses.  
• In your own words, discuss the difference between self-esteem and self-concept.  Provide an example of each.  
• Think about your own self-esteem.  What factors in your life have influenced your self-esteem?  Relate your answer to Bronfenbrenner’s Ecological Theory.  
• Which theory of gender development do you believe best explains gender development? Why do you agree with this theory?  
• A teenager comes to you and confides that she thinks she is a lesbian.  What advice would you give to her? Would you suggest that she confides in others? What challenges will she face?  
• In your opinion, which theory best explains homosexuality? Why?  
• Do you remember the moment you realized your ethnic identity? What was that like? What happened? Describe how your ethnic identity has developed.  
• Chapter 11 discusses moral development. Theories of Kohlberg and Gilligan are introduced.  Read the moral dilemmas presented in your textbook.
• What would you do if you were Heinz? Would you steal the drug? Why or why not?
• How would you handle the situation with the porcupine and moles?  Discuss your reasoning. 
• What do you believe explains the difference between moral thought and moral action?

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Why I Attend Central Lakes College Essay

Career goals and education at this point is getting my generals done and transferring to a university. My career goals are pretty open, with thoughts toward two complete different fields: business management or early childhood development. A lot of challenges have come from my education. Yes, I went to school my whole life but I changed school around seven different times before settling in one location. My family often moved around a lot because my parents work required us to be close to the surrounding area. Education with my family really pushed me to graduate because not a single member of my family has graduated from high school. For me education

Optical Assistant Personal Statement Essay

Personal Statement I’ve always kept an eye on social tensions around the world and although at a younger age I didn’t always fully understand the social injustices that were going and as I began to grow in age, my knowledge and understanding of what was going on around me not only in my community but also around the world also grew. I am a hard-working person,I'm friendly, kind, and can cope with social issues whatever the situation. I'm a team player but can also work independently and lead a team. I am able to bring a range of ideas when it come to teamwork or team leadership. I am able to display a calm, friendly attitude whatever the situation.

Personal Statement: Standing Up For Myself

In the next five years i will be a outgoing and caring person willing to stand up for someone. As a tiger I am fearless of what the future brings and are willing to fight for what's right. I want to be calm, social and vibrant in color like the rain forests. I want to be fearless because I don't want to be afraid to stand up for myself or other people. I want to be trustworthy because i want to be more honest to my friends and family. I want to be outgoing because i want to be able to be myself and make new friends without hesitation.I want to act calm and just take it step by step and go slow so i don't overwhelm myself.

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I hope that I will be able to work with large marine mammals, like sea turtles, dolphins and manatees. I hope that through Stetson, I will be able to work with professionals and do hands on work. Through the Bonner program, I aspire to raise awareness about the human effects on the environment and also would like to teach children about the environment they live in.

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My goals in life are to get a first enlist in the Navy, hope to get a job as a diver in the special operations program. After my first enlistment is up, I want to be a diver at an aquarium where I can feed the animals; Meanwhile, I would like to attend Rosenstiel School of Marine and Atmospheric Science at The University of Miami and earn a doctorate degree in Marine Biology to become a Marine Biologist. I've always been fascinated with animals, especially aquatic life. Although, I wasn't dead-set on becoming one at first, over spring break I made my final decision. We went to an aquarium and I just loved every bit of it; the animal’s interactions, the knowledge behind all of it, and the joy I saw between the employees and the animals. I’m very interested in not just the study of organisms in the ocean or other marine bodies of water, but also marine conservation and ecology. Thinking about the studies of protecting and preserving of the ecosystems in oceans and seas and interactions among organisms and their environment just gets my full attention. I could sit for hours and hours and listen to anybody talk about these subjects and they would have my full attention, one-hundred percent. This subject has never, and never will lose my interest.

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A photograph of Earth reveals a great deal, but it does not convey the complexity of our environment. Our environment (a term that comes from the French environner, “to surround”) is more than water, land, and air; it is the sum total of our surroundings. It includes all of the biotic factors, or living things, with which we interact. It also includes the abiotic factors, or nonliving things, with which we interact. Our environment includes the continents, oceans, clouds, and ice caps you can see in the photo of Earth from space, as well as the animals, plants, forests, and farms that comprise the landscapes around us. In a more inclusive sense, it also encompasses our built

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FigJam Dissect every layer of influence with a Bronfenbrenner diagram

Look at how sizable systems—from micro to macro—impact singular subjects through the lens of famed psychologist Urie Bronfenbrenner.

Bronfenbrenner diagram template

Come together to create your own socio-ecological model examples on an interactive shared whiteboard.

Evaluate environments with ease

Explore any idea or object in great detail by examining its immediate and much-further-afield surroundings, then make decisive changes based on your findings.

Take an all-inclusive approach: Think through any concept or initiative as thoroughly as possible.

Act accordingly: Lean on your learnings and identify actionable inputs.

Apply it anywhere: Use the Bronfenbrenner social-ecological model template in personal, professional, and pedagogical situations.

FigJam Dig deep with the whole team

With FigJam, everyone can contribute—no matter how large your circle of collaborators is. Investigate ideas anywhere in a virtual space, share feedback via chats and Anonymous Thoughts, and show support with custom stamps and emotes.

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Kinship diagram

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Influence diagram

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What is Bronfenbrenner’s main theory?

Urie Bronfenbrenner’s main idea was simple: each individual is affected by a set of external factors, which are in turn affected by external factors, which are in turn affected by… You can see where this is going.

Bronfenbrenner’s original diagram of concentric circles was called “the Ecological Systems Theory,” and revolved—quite literally—around the child, with influences such as parents, peers, teachers, community members, and the greater societal values and views. However, we can apply this American psychologist’s socio-ecological framework to any person, object, or idea by placing it in the center of the diagram.

What are the 5 systems of Bronfenbrenner’s theory?

Bronfenbrenner’s theory places a central figure inside five circles known as “systems.” From smallest to largest, these circles represent:

- The microsystem – The microsystem is the immediate environment. To give an example that stays true to Bronfenbrenner’s original theory, a child’s microsystem would include their parents, family members, peers, and teachers.

- The mesosystem – The mesosystem describes the way multiple microsystems interact. So, what is an example of Bronfenbrenner’s mesosystem? Following the example above, this could be the relationship between the child’s parents and teachers.

- The exosystem – Indirect connections make up the exosystem. Examples could include the neighborhood, the social environment, the child’s parent’s friends, and other groups with a direct impact on the child’s direct relationships.

- The macrosystem – The macrosystem is society at large, representing current cultural values and norms.

- The chronosystem – The fifth and final circle denotes the way things change over time.

How do I fill out a Bronfenbrenner diagram?

Most of Bronfenbrenner’s ecological model examples follow the same approach: start by placing your concept of interest in the center, then expand outward, identifying and adding new elements to each circle.

With that in mind, the easiest way to fill out a Bronfenbrenner diagram is to start with the circles already in place. With pre-made social-ecological model examples from FigJam, you can easily rearrange your ideas and add your own flair with colored markers, icons, stamps, widgets, and so much more.

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