the 3 basic methods of ecological research

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• Ecology: Definition, Types, Importance & Examples

Ecological Research Methods: Observing, Experimenting & Modeling

Ecology is the study of the relationship between organisms and their environment on earth. Several ecological methods are used to study this relationship, including experimenting and modeling.

Manipulative, natural or observational experiments may be used. Modeling helps analyze the collected data.

What Is Ecology?

Ecology , the study of how organisms interact with their environment and each other, draws upon several other disciplines. The environmental science of ecology incorporates biology, chemistry, botany, zoology, mathematics and other fields.

Ecology examines species interactions, population size, ecological niches, food webs, energy flow and environmental factors. In order to do this, ecologists rely on careful methods to collect the most accurate data they can. Once data is collected, ecologists then analyze it for their research.

The information gained from these research methods can then help ecologists find impacts caused by humans or natural factors. This information can then be used to help manage and conserve impacted areas or species.

Observation and Field Work

Every experiment requires observation. Ecologists must observe the environment, the species within it and how those species interact, grow and change. Different research projects require different types of assessments and observations.

Ecologists sometimes use a desk-based assessment , or DBA, to collect and summarize information about specific areas of interest. In this scenario, ecologists are using information already collected from other sources.

Oftentimes, however, ecologists rely on observation and field work . This entails actually going into the habitat of the subject of interest to observe it in its natural state. By doing field surveys, ecologists can track population growth of species, observe community ecology in action and study the impact of any new species or other introduced phenomena in the environment.

Each field site will differ in nature, in shape or in other ways. Ecological methods allow for such differences so that different tools can be used for observations and sampling. It is crucial that sampling be done in a random fashion to combat bias.

Types of Data Obtained

Data obtained from observation and field work can be either qualitative or quantitative. These two classifications of data vary in distinct ways.

Qualitative data : Qualitative data refers to a quality of the subject or conditions . It is therefore a more descriptive form of data. It is not easily measured, and it is collected by observation.

Because qualitative data is descriptive, it might include aspects such as color, shape, whether the sky is cloudy or sunny, or other aspects for how an observation site might look. Qualitative data is not numerical like quantitative data. It is therefore considered less reliable than quantitative data.

Quantitative data: Quantitative data refers to numerical values or quantities . These kinds of data can be measured and are usually in number form. Examples of quantitative data might include pH levels in soil, the number of mice in a field site, sample data, salinity levels and other information in numeric form.

Ecologists use statistics to analyze quantitative data. It is therefore considered a more reliable form of data than qualitative data.

Types of Field Work Surveys

Direct survey: Scientists can directly observe animals and plants in their environment. This is called a direct survey. Even in places as remote as a seafloor, ecologist can study the underwater environment. A direct survey in this case would entail photographing or filming such an environment.

Some sampling methods used to record images of sea life on the seafloor include video sledges, water curtain cameras and Ham-Cams. Ham-Cams are attached to a Hamon Grab, a sample bucket device used to collect samples. This is one effective way to study animal populations.

The Hamon Grab is a method of collecting sediment from the seafloor, and the sediment is taken onto a boat for ecologists to sort through and photograph. These animals will be identified in a laboratory elsewhere.

In addition to a Hamon Grab, undersea collection devices include a beam trawl, which is used to obtain larger sea animals. This entails attaching a net to a steel beam and trawling from the back of a boat. The samples are brought on board the boat and photographed and counted.

Indirect survey: It is not always practical or desirable to observe organisms directly. In this situation, ecological methods entail observing the traces those species leave behind. These could include animal scat, footprints and other indicators of their presence.

Ecological Experiments

The overarching purpose of ecological methods for research is to get high-quality data. In order to do this, experiments must be carefully planned.

Hypothesis : The first step in any experimental design is to come up with a hypothesis or scientific question. Then, researchers can come up with a detailed plan for sampling.

Factors that affect field work experiments include the size and shape of an area that needs to be sampled. Field site sizes range from small to very large, depending on what ecological communities are being studied. Experiments in animal ecology must take into account potential movement and size of animals.

For example, spiders would not require a large field site for study. The same would be true when studying soil chemistry or soil invertebrates. You could use a size of 15 meters by 15 meters.

Herbaceous plants and small mammals might require field sites of up to 30 square meters. Trees and birds might need a couple of hectares. If you are studying large, mobile animals, such as deer or bears, this could mean needing a quite large area of several hectares.

Deciding upon the number of sites is also crucial. Some field studies might require only one site. But if two or more habitats are included in the study, two or more field sites are necessary.

Tools: Tools used for field sites include transects, sampling plots, plotless sampling, the point method, the transect-intercept method and the point-quarter method. The goal is to get unbiased samples of a high-enough quantity that statistical analyses will be sounder. Recording information on field data sheets aids in the data collection.

A well-designed ecological experiment will have a clear statement of purpose or question. Researchers should take extraordinary care to remove bias by providing both replication and randomization. Knowledge of the species being studied as well as the organisms within them is paramount.

Results: Upon completion, collected ecological data should be analyzed with a computer. There are three types of ecological experiments that can be made: manipulative, natural and observational.

Manipulative Experiments

Manipulative experiments are those in which the researcher alters a factor to see how it affects an ecosystem. It is possible to do this in the field or in a laboratory.

These kinds of experiments provide interference in a controlled manner. They work in cases in which field work cannot occur over an entire area, for various reasons.

The downside of manipulative experiments is they are not always representative of what would happen in the natural ecosystem. Additionally, manipulative experiments might not reveal the mechanism behind any patterns observed. It is also not easy to change variables in a manipulative experiment.

Example : If you wanted to learn about lizard predation of spiders, you could alter the number of lizards in enclosures and study how many spiders resulted from this effect.

A larger and current example of a manipulation experiment is the reintroduction of wolves into Yellowstone National Park. This reintroduction allows for ecologists to observe the effect of wolves returning to what was once their normal range.

Already, researchers have learned that an immediate change in the ecosystem occurred once wolves were reintroduced. Elk herd behaviors changed. Increased elk mortality led to a more stable food supply for both wolves and carrion eaters.

Natural Experiments

Natural experiments, as their name implies, are not directed by humans. These are manipulations of an ecosystem caused by nature. For example, in the wake of a natural disaster, climate change or invasive species introduction, the ecosystem itself represents an experiment.

Of course, real-world interactions such as these are not truly experiments. These scenarios do provide ecologists with opportunities to study the effects natural events have on species in an ecosystem.

Example: Ecologists could take a census of animals on an island to study their population density.

The main difference between manipulative and natural experiments from a data perspective is that natural experiments do not have controls. Therefore it is sometimes harder to determine cause and effect.

Nevertheless, there is useful information to be gained from natural experiments. Environmental variables like moisture levels and density of animals can still be used for data purposes. Additionally, natural experiments can occur across large areas or vast stretches of time. This further distinguishes them from manipulative experiments.

Unfortunately, humanity has caused catastrophic natural experiments across the globe. Some examples of these include habitat degradation, climate change, introduction of invasive species and removal of native species.

Observational Experiments

Observational experiments require adequate replications for high-quality data. The “rule of 10” applies here; researchers should collect 10 observations for each category required. Outside influences can still hamper efforts to collect data, such as weather and other disturbances. However, using 10 replicating observations can prove helpful for obtaining statistically significant data.

It is important to perform randomization, preferably prior to performing observational experiments. This can be done with a spreadsheet on a computer. Randomization strengthens data collection because it reduces bias.

Randomization and replication should be used together to be effective. Sites, samples and treatments should all be randomly assigned to avoid confounded results.

Ecological methods rely heavily on statistical and mathematical models. These provide ecologists with a way to predict how an ecosystem will change over time or react to changing conditions in the environment.

Modeling also provides another way to decipher ecological information when field work is not practical. In fact, there are several drawbacks to relying solely on field work.Because of the typically large scale of field work, it is not possible to replicate experiments exactly. Sometimes even the lifespan of organisms is a rate-limiting factor for field work. Other challenges include time, labor and space.

Modeling, therefore, provides a method in which to streamline information in a more efficient manner.

Examples of modeling include equations, simulations, graphs and statistical analyses. Ecologists use modeling for producing helpful maps as well. Modeling allows for calculations of data to fill in gaps from sampling. Without modeling, ecologists would be hampered by the sheer amount of data that needs to be analyzed and communicated. Computer modeling allows for comparatively rapid analysis of data.

A simulation model, for example, enables the description of systems that would otherwise be extremely difficult and too complex for traditional calculus. Modeling allows scientists to study coexistence, population dynamics and many other aspects of ecology. Modeling can help predict patterns for crucial planning purposes, such as for climate change.

Humanity’s impact upon the environment will continue. It therefore becomes ever more crucial for ecologists to use ecological research methods to find ways to mitigate the effects on the environment.

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About the Author

J. Dianne Dotson is a science writer with a degree in zoology/ecology and evolutionary biology. She spent nine years working in laboratory and clinical research. A lifelong writer, Dianne is also a content manager and science fiction and fantasy novelist. Dianne features science as well as writing topics on her website, jdiannedotson.com.

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Open Access

Peer-reviewed

Research Article

Trends in Ecological Research during the Last Three Decades – A Systematic Review

Affiliation Faculty of Civil and Environmental Engineering, Technion – Israel Institute of Technology, Haifa, Israel

* E-mail: [email protected]

Affiliation Department of Plant Sciences, University of Cambridge, Cambridge, United Kingdom

Affiliation Department of Biology and Environment, University of Haifa at Oranim, Kiryat Tivon, Israel

Affiliation Institute of Evolution, University of Haifa, Haifa, Israel

• Yohay Carmel, 
• Rafi Kent, 
• Avi Bar-Massada, 
• Lior Blank, 
• Jonathan Liberzon, 
• Oded Nezer, 
• Gill Sapir, 
• Roy Federman

• Published: April 24, 2013
• https://doi.org/10.1371/journal.pone.0059813
• Reader Comments

It is thought that the science of ecology has experienced conceptual shifts in recent decades, chiefly from viewing nature as static and balanced to a conception of constantly changing, unpredictable, complex ecosystems. Here, we ask if these changes are reflected in actual ecological research over the last 30 years. We surveyed 750 articles from the entire pool of ecological literature and 750 articles from eight leading journals. Each article was characterized according to its type, ecological domain, and applicability, and major topics. We found that, in contrast to its common image, ecology is still mostly a study of single species (70% of the studies); while ecosystem and community studies together comprise only a quarter of ecological research. Ecological science is somewhat conservative in its topics of research (about a third of all topics changed significantly through time), as well as in its basic methodologies and approaches. However, the growing proportion of problem-solving studies (from 9% in the 1980s to 20% in the 2000 s) may represent a major transition in ecological science in the long run.

Citation: Carmel Y, Kent R, Bar-Massada A, Blank L, Liberzon J, Nezer O, et al. (2013) Trends in Ecological Research during the Last Three Decades – A Systematic Review. PLoS ONE 8(4): e59813. https://doi.org/10.1371/journal.pone.0059813

Editor: Luís A. Nunes Amaral, Northwestern University, United States of America

Received: September 16, 2012; Accepted: February 19, 2013; Published: April 24, 2013

Copyright: © 2013 Carmel et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Funding: This study was funded by the Israel Science Foundation (grant number 486-2010). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.

Introduction

Ecologists often describe ecological science as dynamic. ‘Ecology is a science in transition’ [1] . This transition is characterized by several significant shifts in emphasis and perspective [2] . During most of the 20 th century, the majority of ecologists conceptualized ecological systems as balanced and stable, typically at equilibrium, or as returning to such equilibrium deterministically following rare disturbances [3] . In recent decades, there has been a shift towards an understanding of ecological systems as nonlinear, constantly changing, and unpredictable in time and space [4] , [5] . The concept of equilibrium was replaced by other concepts, for example, the concept of non-equilibrium change, in which the system is often described as rotating between alternative states [6] .

Ecologists are split on the question of whether the changes in ecological science represent a Kuhnian ‘paradigm shift’ [5] , [7] , [8] , [9] , or, alternatively, a gradual accumulation of modifications, better characterized as ‘evolution’ rather than ‘revolution’ [2] , [10] . In contrast, other ecologists maintained that progress in ecology is lacking [11] or limited [12] .

Here, we ask if the topics and methodologies of ecological research as reflected in the literature of the last 30 years provide evidence to support notions of dramatic shifts, or of gradual change. We characterize various aspects of ecological research, using an extensive survey of ecological literature. In particular, we ask three questions regarding general aspects of ecology, and look for possible changes in these aspects over the last 30 years:

• Domains of ecological research : What proportion of research is devoted to the various domains in ecology (population, species, community, and ecosystem)? What are the major topics of ecological study? Has there been a change in the frequency of investigation of any of these topics and, if so, which ones?
• Types of research : Is ecology an experimental science, or a science of observation and measurement? How often are models used in ecological research? To what degree do ecologists use meta-analysis of data from previous studies (vs. collecting new data in each research)?
• Basic science or problem-solving oriented discipline : Is ecology becoming a problem-solving science? In other words, how often does ecology relate to actual, specific environmental problems, in an attempt to provide solutions (or at least new insights on how to make progress towards solutions)?

Preliminary expectations

A. domains of ecological research..

The concepts of ecosystem and community have become increasingly dominant in ecological thinking. In a survey conducted among members of the British Ecological Society, ecosystem was identified as the single most important concept in ecology [13] . More recently, the Ecological Visions Committee of the Ecological Society of America issued a report that listed eight critical environmental issues for prioritizing ecological research [14] . Only two of those topics related to populations and species, while five topics were clearly within the domains of ecosystems and communities . We expected an increase in research conducted at the ecosystem level, and at the community level, accompanied by a proportional decrease in studies of single species. We also expected specific topics to become more frequent subjects of ecological study (such as biodiversity, climate change, biogeochemistry, and scale).

B. Types of research.

Observations and experiments are known to be the two dominant tools of ecological research . In this research, we expected to identify an increase in the frequency of models, for two reasons: (1) the ecosystem has increasingly been described as ‘complex’, and models are often the only tools available for the study of complex systems, and (2) due to the substantial increase in the availability of modelling tools during the last three decades. We also expected an increase in the proportion of meta-analysis studies, for two major reasons: (1) a growing awareness of the incapacity of single studies of specific systems, conducted under narrow ranges of conditions, to provide insights on broader ecological issues [15] , and (2) the increased access to information and data in the age of the Internet.

C. Is ecology a problem-solving science?

In the past, ecologists have been reluctant to engage in applied research [16] . Applied science was considered inferior to basic, ‘pure’ science [17] . Some applied ecological issues, such as conservation, are emotionally charged [2] , and perceived by some ecologists as ‘advocacy’ [18] . More recently, ecologists have become increasingly concerned about the implications of their work to society's problems [15] , [17] , while environmental agencies have expressed an increased demand for ecological solutions to environmental problems [19] . For these reasons, we expected to find an increase in the proportion of applied studies over the last three decades.

In order to attempt to answer these questions, a quantitative survey of ecological research is required. Surprisingly, few attempts have been made to systematically quantify trends in ecological research. Typically, these studies have used an automated count of words in titles and abstracts to assess trends in ecology [20] , [21] , [22] , [23] . Shorrocks [24] used an alternative method to survey trends in ‘the Journal of animal ecology’ –he actually sampled 13 volumes of the journal between 1932 and 1992. Here, we followed that method: we inspected a large sample of the ecological literature, classifying it according to its content. This process is time-consuming, but the resulting analysis is probably more reliable than an automated word count.

Two surveys

One major consideration was our choice of target population within the ecological literature. Two plausible alternatives existed: we could either sample the entire pool of ecological research, or sample only leading journals. There are pros and cons to each choice. Including the entire range of ecological literature may introduce research of varying quality into the analysis. On the other hand, niche journals (the vanguard of novel research) may serve as early indicators of transitions and trends. We therefore decided to conduct two parallel surveys, using identical methods. In survey 1, we included all 136 journals that concern ecology, while in survey 2 we sampled eight ‘core journals’ that were published throughout the entire study period. A brief description of the data collection approach can be found in the Prisma 2009 flow diagram and checklist.

Journal selection

For survey 1, we selected all relevant journals that appeared during at least parts of the study period 1981–2010. This pool consisted of 136 journals. From the entire collection of articles published in these journals during this period, we limited the selection to research articles in English, and received a total of 110,965 articles (see Appendix S1 for a full list of journals sampled for this survey).

For survey 2, we selected eight prominent journals, using the following criteria: (a) high-impact factor (among the top 30 ecological journals, using ISI Web of Science Impact Factor), (b) generality (cover the entire scope of ecological research), and (c) consistency (were published throughout the study period). Not a single journal satisfied all three criteria. We therefore selected eight journals belonging to three major ecological societies that issue their own journals; thus, each group, as such, satisfies all three criteria. The eight journals were those issued by the Ecological Society of America ( Ecological Applications , Ecological Monographs , and Ecology ); the British Ecological Society (Journal of Ecology, Journal of Animal Ecology, and Journal of Applied Ecology), and the Nordic Ecological Society ( Oikos and Ecography ). Ecological Applications , first published in 1991, was an offshoot of Ecology, and Ecography , first published in 1991, was an offshoot of Oikos ; we assumed that the range of topics covered by each of the pairs was similar to that of the parent journal prior to the split. The pool of all research articles published in these journals in the period 1981–2010 consisted of 22,788 articles).

For each of the two surveys, we used a random selection scheme to select 25 articles from each year, totalling 750 articles in each survey. The classification (domain, topics, research type, applied or basic science) was performed by the authors of the current study, based on the articles. In many cases, reading the abstract provided sufficient information for classifying the article. In order to ensure a high degree of consistency between the classifiers, we carried out a pilot exercise, in which the degree of agreement between the classifiers was assessed prior to the research study. A set of 29 articles was classified independently by all classifiers. Classifications were then discussed until consensus was reached for each classification. For each topic and for each classifier, the level of agreement between initial classification and final ‘consensus’ was recorded.

Article characterization

A. ecological domains..

We predefined 20 topics that describe major research fields in ecology, and grouped these 20 topics into five broad ecological domains: (1) Single Species (demography, physiology, distribution, behaviour, evolution, genetics); (2) Species Interactions (grazing, predation, mutualism, parasitism, competition); (3) Community (biodiversity, community structure); (4) Ecosystem (food web, climate change, vegetation dynamics, biomass and productivity, biogeochemistry); and (5) Other topics (scale, statistics). We limited topic-based characterization to three topics per article.

B. Type of research.

We classified the type of ecological research according to four general categories: experiment, observation, model, and data analysis. An article was classified as ‘experiment’ if an actual experiment was conducted in the laboratory, or if a field study included some sort of treatment or manipulation of the natural environment. Where research included both observation and field experiment, the article was labelled ‘experiment’. ‘Observation’ was a study where the major activity was any sort of measurement of ecological phenomena. An article was labelled ‘model’ if its sole activity or the major endeavor was to construct a model. In cases where a model was only a minor part of the research, the article was labelled ‘experiment’ or ‘observation’. Articles that did not present any new data, but used data collected in previous studies, often conducting meta-analysis, were labelled ‘data analysis’. Articles that did not include any of the above types of research, but discussed ecological issues qualitatively were omitted from the survey (and a replacement was added).

C. Problem-solving.

Our goal here was to determine the degree to which ecology is oriented towards problem-solving. We assigned the category of ‘application’ to all articles that either searched for solutions to problems associated with anthropogenic activities, or proposed tools for practical problems (such as practices for conservation, global change mitigation etc.).

Statistical analyses

The number of articles assigned to each ecological topic, label, and variable was recorded for each survey. The differences between surveys in terms of the frequency of each term were analyzed using Chi square test. To evaluate change in the frequency of these variables over time, we used logistic regression [25] , with publication year as a continuous variable and survey type as a fixed variable. In order to account for multiple comparisons, we applied the Bonferroni correction. Fifty comparisons (25 comparisons in each survey) yielded a threshold of p<0.001 . The Bonferroni correction becomes very conservative when the number of comparisons becomes large, as it controls the probability of false positives only, at the cost of increasing the probability of false negatives [26] . We therefore report the results using Bonferroni correction, as well as for less conservative thresholds.

Classification consistency

Classifiers' results were in good agreement with the consensus of the test articles, with an overall average agreement rate of 90%. The average accuracy of parameter classification was high in all cases, ranging from 86% for ‘topics’ and ‘problem solving’, to 93% and 94% for ‘research type’ and ‘domain’, respectively. In what follows, wherever we report two figures, the first figure refers to the ‘all journals’ survey, and the second figure refers to the ‘core journals’ survey.

Domains of ecological research

(1) Single Species was the most frequent domain of study in this survey of ecological research, with 71% (66%) of all the studies involving topics within this domain ( Table 1 ). In both surveys, the four most common topics related to this domain: demography, physiology, behaviour and distribution. Taken together, these topics appeared in 64% (63%) of all articles. Only 4% (3%) of all articles studied evolution. (2) In the Species Interactions domain, predation and competition were the frequent terms, recorded in 5–9% of the articles, while mutualism and parasitism were recorded in 2–4% of the articles. (3) Community-related topics (biodiversity and community structure) appeared in 17% of the studies in both surveys, and (4) Ecosystem-related topics appeared in nearly a quarter of the articles. Among ecosystem topics, biogeochemistry accounted for 11% (8%) of ecological research and 2% of the research concerned climate change studies ( Table 1 ).

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https://doi.org/10.1371/journal.pone.0059813.t001

The frequency of community studies increased significantly (nearly significantly in the ‘core journals’) during the studied period, while the other three domains remained quite constant over time ( Table 2 , Figure 1 ).

White bars denote ‘all journals’ and gray bars denote ‘core journals’. Temporal trend was significant for community studies only (a logistic model, see Table 2 ).

https://doi.org/10.1371/journal.pone.0059813.g001

https://doi.org/10.1371/journal.pone.0059813.t002

There were significant changes in the frequency of several topics over time. The frequency of two topics climate change and biodiversity, increased significantly with time in both surveys ( Table 2 , Figure 2 ). The frequency of three additional topics changed significantly in the ‘all journals’ survey only: physiology and behaviour decreased, while genetics increased. An increase in the frequency of scale was the single significant change that appeared in the ‘core journals’ only. Additionally, five topics revealed a nearly significant frequency change through time in that survey (p<0.05): demography , grazing , and vegetation dynamics decreased, while evolution and parasitism increased in frequency with time ( Table 2 ).

White bars denote ‘all journals’ and gray bars denote ‘core journals’. *** Temporal trend was significant (a logistic model, see Table 2 ), p<0.001. ** p<0.01. * p<0.05.

https://doi.org/10.1371/journal.pone.0059813.g002

Differences between the two surveys

The results of both surveys were quite similar for 14 of the 20 topics, while significant differences between the two surveys were found for six topics: physiology , behaviour and genetics were much more frequent in the ‘all journals’ survey, while demography , grazing , and vegetation dynamics were much more frequent in the ‘core journals’ survey ( Table 1 ). Most domains appeared at similar frequencies in the two surveys, except Species Interactions, which was nearly twice as frequent in the ‘core journals’ survey compared to its frequency in the ‘all journals’ survey ( Table 1 ).

Type of research

Observations constitutes the major type of ecological research (59%, 45%), followed by experiments (28%, 36%), while models (12%, 12%) and data-analysis (9%, 6%) were less frequent ( Table 3 ).

https://doi.org/10.1371/journal.pone.0059813.t003

The proportion of data-analysis studies increased significantly with time in the ‘all journals’ survey. The use of models as a primary research tool slightly decreased in ‘all journals’ and slightly increased (nearly significant) in the ‘core journals’ survey ( Table 4 ).

https://doi.org/10.1371/journal.pone.0059813.t004

Observation studies were significantly more frequent in the ‘all journals’ survey, while experiments were somewhat more frequent in the ‘core journals’ survey.

Is ecology a problem-solving science?

Overall, 17% (15%) of the articles were labelled ‘problem solving’ ( Table 3 ). In both surveys, their proportion increased significantly over time, from 9% (7%) in the 1980s to 21% (21%) in the 2000 s ( Table 4 , Figure 2 ).

Few systematic surveys of ecological literature have been conducted to date, and most have been restricted to a single theme or a narrow branch of ecological science [20] , [21] , [22] , [23] . For example, [22] evaluated relations between the size of the organism and its relative representation in ecological research. Swihart [12] quantified the rates of appearance of new ecological terms and disappearance of old terms. Shorrocks [24] was perhaps the only investigator to quantify various trends in ecological science, using articles published in The Journal of Animal Ecology between 1932 and 1992. To the best of our knowledge, the present study is the first attempt to systematically survey the entire breadth of ecological literature, in order to quantify various characteristics of the science of ecology, as well as their temporal trends. The results suggest that ecology may be substantially less dynamic than is generally acknowledged.

Ecology is mostly a study of single species. Most of the ecological research focused on the demography, physiology and distribution of single species. The proportion of single-species studies has slightly decreased in the past three decades, but still consists of more than 60% of the studies. In comparison, community and ecosystem studies represented a minor fraction of ecological research. This surprising finding seems at odds with the strong emphasis on the community and the ecosystem as major concepts in ecology [27] , [28] . Also surprising was the scarcity of a few topics which are thought to be central in ecology. Two notable examples are evolution, and food-web, each of which appeared as a research topic in 2–4% of the articles. Most of the increase in community studies occurred in the 2000s, probably reflecting the renewed interest in this field, after the neutral theory challenged the prevalence of the niche concept.

The analysis of changes in the frequency of research topics over time provided inconclusive results. Only two topics, climate change and biodiversity, showed a significant change in both surveys. The increase in both topics probably relates to the fact that both were non-issues at the beginning of the period under study. Four other topics changed significantly, and seven other topics changed nearly significantly, in only one of the surveys. Overall, there does not seem to be a drastic transformation in the relative importance of domains and topics in the field of ecology, but the apparent change in topics and research types signifies that ecological science is not entirely stagnant.

The frequency of more than half of the topics and domains was very similar in both surveys, but nearly a third of the topics differed significantly between the surveys. Interestingly, the topics that were significantly more frequent in the ‘all journals’ survey related to the basic and static aspects of a species (genetics and physiology), and the ecosystem (biomass and productivity). In contrast, the topics that were significantly more frequent in the ‘core journals’ related to dynamic processes (demography, vegetation dynamics, and grazing).

Observation and experiment were by far the predominant tools of ecological study, together accounting for 80% of the research; these proportions did not change over time. Interestingly, modelling (∼12% of all studies), is no more common today than it was thirty years ago, despite a drastic increase in the availability of modelling tools during this period. Data-analysis became a more common research tool. Many of the studies in this category were, in fact, meta-analyses (analyses of data from several sources). The major increase in data-analysis studies was in the mid-90s, suggesting that the increased availability of information in the age of the Internet had an important role in this trend.

Comparing the two surveys in terms of type of research revealed a fundamental difference: the ratio of experiments to observations in the ‘all journals’ survey was 1:2, while in the ‘core journals’ survey it was 7:9. The prevalent consensus that ecology has changed during the 20 th century, from an observational to an experimental science, may be somewhat overstated; nevertheless, such a change appeared more prominently in the ‘core journals’ survey.

Ecological research is mostly a basic science, with only a small proportion of ‘problem solving’ studies. Yet, in both surveys we found a significant and consistent increase in the number of ‘problem solving’ articles published during the survey period. If this trend continues in future decades, it may prove to be a major shift in the orientation of ecology.

Is ecology a dynamic science?

Prominent ecologists have claimed that ecology has undergone transitions [29] , and even paradigm shifts [5] in recent decades, and is now a mature and competent science [30] . Our survey reveals that these claims perhaps overstate the case. The science of ecology appears to be changing slowly, in the sense that major research subjects and principal methodologies have not changed dramatically for at least 30 years. In particular, the popular image of ecology as a science in transition [7] , dealing chiefly with ecosystems and communities [1] seems at odds with the major proportion of single species studies reported here.

A contrasting view, put forward by O'Connor [11] , claimed that ecology lags after other life sciences, and makes very little progress. O'Conner's study ignited a debate, wherein various arguments were employed to disprove this claim [31] , [23] , or put it in a balanced perspective [12] . This debate is still ongoing, and is probably driven by emotions no less than by objective evaluations. The current study does not substantiate O'Connor's claim, and it was not meant to evaluate progress. However, it is safe to assume that a major advance in ecology would be accompanied by a major change in the frequency of domains, topics, and types of research; yet, as shown here, these have changed only moderately in the course of three decades.

A major aspect of progress in science is the rate at which basic questions in ecology are being answered [12] , which we have not evaluated, and is very difficult to evaluate quantitatively. Also, we could not detect conceptual shifts, such as network thinking, that do not connect to particular terms or topics. Swihart et al. [12] provide an interesting attempt to quantify progress based on ‘birth rate’ and ‘death rate’ of ecological terms, and claim to show viable progress in ecology. In contrast, the list of 100 fundamental questions in ecology [32] reports profound knowledge gaps regarding the central mechanisms driving ecosystems, communities, and even population dynamics.

Our approach could not, and was not meant to detect changes in particular methods and technologies applied within each research domain or topic. The availability of advanced molecular and genetic tools and the increase in computing power have allowed analyses to become more complex and sophisticated. However, the use of these new technologies and processing power does not imply enhanced knowledge or understanding. Also, such surveys may not detect conceptual shifts, such as network thinking, which do not connect to particular terms or topics.

Perhaps the single and most important change in the study of ecology is the growing proportion of ecological research directed towards problem solving. This trend by itself, if continued, may represent a major transition in ecology in the long run.

Our results may be disturbing to some researchers, insofar as they portray an ecological discipline which is considerably less dynamic than ecologists would like to believe. The value of this research is precisely in reviving the debate and presenting an opportunity for self-assessment to those who strive to advance the discipline, all of which can serve to stimulate the investigation of new and groundbreaking tools, paradigms and perspectives. Only through meta-scale monitoring of the scope of research can we understand, and hope to influence, the trajectory of ecological research in the years to come.

Supporting Information

Appendix s1..

A full list of journals sampled for survey 1.

https://doi.org/10.1371/journal.pone.0059813.s001

Flow Diagram S1.

https://doi.org/10.1371/journal.pone.0059813.s002

Checklist S1.

https://doi.org/10.1371/journal.pone.0059813.s003

Acknowledgments

Curtis Flather, Mark Burgman, Leon Blaustein, Yaacov Garb, Yaron Ziv and Daniel Statman have provided valuable comments on a draft of this manuscript.

Author Contributions

Conceived and designed the experiments: YC AB LB RF. Performed the experiments: YC RK AB LB JL ON RF GS. Analyzed the data: RF YC GS. Wrote the paper: YC RK AB LB RF JL ON.

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• 29. Pickett STA, White PS (1985) Patch dynamics: A synthesis. In: Pickett STA, White RS, editors. The ecology of natural disturbance and patch dynamics. London: Academic Press. pp.371–384.

Module 14: Ecology of Living Things

Levels of ecological research, learning outcomes.

• Define ecology and the four levels of ecological research

When a discipline such as biology is studied, it is often helpful to subdivide it into smaller, related areas. For instance, cell biologists interested in cell signaling need to understand the chemistry of the signal molecules (which are usually proteins) as well as the result of cell signaling. The same subdivisions occur in ecology. Ecologists interested in the factors that influence the survival of an endangered species might use mathematical models to predict how current conservation efforts affect endangered organisms. To produce a sound set of management options, a conservation biologist needs to collect accurate data, including current population size, factors affecting reproduction (like physiology and behavior), habitat requirements (such as plants and soils), and potential human influences on the endangered population and its habitat (which might be derived through studies in sociology and urban ecology). Within the discipline of ecology, researchers work at four specific levels, sometimes discretely and sometimes with overlap: organism, population, community, and ecosystem (Figure 1).

Figure 1. Ecologists study within several biological levels of organization. (credit “organisms”: modification of work by “Crystl”/Flickr; credit “ecosystems”: modification of work by Tom Carlisle, US Fish and Wildlife Service Headquarters; credit “biosphere”: NASA)

Organismal Ecology

Researchers studying ecology at the organismal level are interested in the adaptations that enable individuals to live in specific habitats. These adaptations can be morphological, physiological, and behavioral. For instance, the Karner blue butterfly ( Lycaeides melissa samuelis ) is a rare butterfly that lives only in open areas with few trees or shrubs, such as pine barrens and oak savannas. It is considered a specialist because the females preferentially oviposit (that is, lay eggs) on wild lupine (Figure 2). This preferential adaptation means that the Karner blue butterfly is highly dependent on the presence of wild lupine plants for its continued survival.

Figure 2. (a) The Karner blue butterfly ( Lycaeides melissa samuelis ). (b) The wild lupine ( Lupinus perennis ) is the host plant for the Karner blue butterfly (credit a: modification of work by J & K Hollingsworth, USFWS; credit b: Joel Trick, USFWS)

After hatching, the larval caterpillars emerge and spend four to six weeks feeding solely on wild lupine. The caterpillars pupate (undergo metamorphosis) and emerge as butterflies after about four weeks. The adult butterflies feed on the nectar of flowers of wild lupine and other plant species. A researcher interested in studying Karner blue butterflies at the organismal level might, in addition to asking questions about egg laying, ask questions about the butterflies’ preferred temperature (a physiological question) or the behavior of the caterpillars when they are at different larval stages (a behavioral question).

Population Ecology

A population is a group of interbreeding organisms that are members of the same species living in the same area at the same time. (Organisms that are all members of the same species are called conspecifics .) A population is identified, in part, by where it lives, and its area of population may have natural or artificial boundaries: natural boundaries might be rivers, mountains, or deserts, while examples of artificial boundaries include mowed grass, manmade structures, or roads. The study of population ecology focuses on the number of individuals in an area and how and why population size changes over time. Population ecologists are particularly interested in counting the Karner blue butterfly, for example, because it is classified as federally endangered. However, the distribution and density of this species is highly influenced by the distribution and abundance of wild lupine. Researchers might ask questions about the factors leading to the decline of wild lupine and how these affect Karner blue butterflies. For example, ecologists know that wild lupine thrives in open areas where trees and shrubs are largely absent. In natural settings, intermittent wildfires regularly remove trees and shrubs, helping to maintain the open areas that wild lupine requires. Mathematical models can be used to understand how wildfire suppression by humans has led to the decline of this important plant for the Karner blue butterfly.

Community Ecology

A biological community consists of the different species within an area, typically a three-dimensional space, and the interactions within and among these species. Community ecologists are interested in the processes driving these interactions and their consequences. Questions about conspecific interactions often focus on competition among members of the same species for a limited resource. Ecologists also study interactions among various species; members of different species are called heterospecifics . Examples of heterospecific interactions include predation, parasitism, herbivory, competition, and pollination. These interactions can have regulating effects on population sizes and can impact ecological and evolutionary processes affecting diversity.

For example, Karner blue butterfly larvae form mutualistic relationships with ants. Mutualism is a form of a long-term relationship that has coevolved between two species and from which each species benefits. For mutualism to exist between individual organisms, each species must receive some benefit from the other as a consequence of the relationship. Researchers have shown that there is an increase in the probability of survival when Karner blue butterfly larvae (caterpillars) are tended by ants. This might be because the larvae spend less time in each life stage when tended by ants, which provides an advantage for the larvae. Meanwhile, the Karner blue butterfly larvae secrete a carbohydrate-rich substance that is an important energy source for the ants. Both the Karner blue larvae and the ants benefit from their interaction.

Ecosystem Ecology

Ecosystem ecology is an extension of organismal, population, and community ecology. The ecosystem is composed of all the biotic  components (living things) in an area along with the abiotic components (non-living things) of that area. Some of the abiotic components include air, water, and soil. Ecosystem biologists ask questions about how nutrients and energy are stored and how they move among organisms and the surrounding atmosphere, soil, and water.

The Karner blue butterflies and the wild lupine live in an oak-pine barren habitat. This habitat is characterized by natural disturbance and nutrient-poor soils that are low in nitrogen. The availability of nutrients is an important factor in the distribution of the plants that live in this habitat. Researchers interested in ecosystem ecology could ask questions about the importance of limited resources and the movement of resources, such as nutrients, though the biotic and abiotic portions of the ecosystem.

Watch this video for another introduction to ecology:

Dividing Ecological Study

Ecology can also be classified on the basis of:

• the primary kinds of organism under study (e.g. animal ecology, plant ecology, insect ecology)
• the biomes principally studied (e.g. forest ecology, grassland ecology, desert ecology, benthic ecology, marine ecology, urban ecology)
• the geographic or climatic area (e.g. arctic ecology, tropical ecology)
• the spatial scale under consideration (e.g. macroecology, landscape ecology)
• the philosophical approach (e.g. systems ecology which adopts a holistic approach)
• the methods used (e.g. molecular ecology)
• Biology. Provided by : OpenStax CNX. Located at : http://cnx.org/contents/[email protected] . License : CC BY: Attribution . License Terms : Download for free at http://cnx.org/contents/[email protected]
• Ecology (disciplines). Provided by : Wikipedia. Located at : https://en.wikipedia.org/wiki/Ecology_(disciplines) . License : CC BY-SA: Attribution-ShareAlike

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What Are the Three Methods Ecologists Use to Study the Environment?

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• Dolphin's Ecological Importance
• The Differences Between an M.D. in Microbiology & a Ph.D in Microbiology

Ecology comes from the Greek words oikos, which means house, and logos, which means the study of. Literally, ecology is the study of our home. Ecologists study a wide range of ecosystems all around the world. Ecosystems as varied as a desert with lizards and cacti, an ocean containing sharks and plankton, and a puddle occupied by microbes may appear to have little in common, but ecologists studying all of them use similar methods. They collect field data, perform experiments, and build mathematical models.

Field Work and Observations

The study of environments generally begins with field observations. Field work often starts with nonquantitative observations. A researcher may take a stroll through the forest or snorkel a reef to look around. Once ecologists have an idea of the system, they can determine what data they’re interested in collecting. It is never possible to measure everything all of the time, so ecologists need to make decisions about the frequency of measurements and types of measurements to take. Some data collection can be automated, through the use of sensors or research towers, such as the four towers at Harvard University's Harvard Forest. Other data collection methods, like vegetation surveys or animal trapping, must be done in person. The data from field work helps ecologists figure out the right questions to ask.

Experiments

Field data is a great first step to understanding an ecosystem, but there are always questions that can’t be answered with the field surveys. In these cases, ecologists will employ manipulative experiments with a control treatment to test hypotheses about the way an ecosystem works. For example, a famous set of experiments by Prof. Stephen Carpenter of the University of Wisconsin involved adding top predator fish to lakes to see if this would control primary production. The idea was based off of observational data about how lakes changed after winter fish kills. Carpenter’s research team found that more predator fish leads to: 1) less small fish, 2) more zooplankton and 3) less phytoplankton. Called a trophic cascade, these experiments have led to improved management of lakes across the world and other ecosystems like Yellowstone National Park.

Modeling is an important tool that ecologists employ to study ecosystems once they think they understand how the ecosystem of an environment works. A model can take many forms, but it represents a specific hypothesis about the mechanics of an ecosystem. The power of modeling is that a good model can let researchers test a range of scenarios that would be too expensive or difficult to do as experiments. Models can help ecologists make predictions about things as varied as how changes to fisheries regulations will affect fisheries stocks or how climate change will impact the ranges of disease carrying species like mosquitoes. Models that predict range expansion of disease carrying mosquitoes can be used to inform doctors in at-risk areas to be on the look out for new diseases such as malaria that may not have occurred there before.

The most powerful research projects are ones that bring together field observations, experiments and modeling. There are programs in place today that are designed to create opportunities for synthesis of these different research methods. For instance, the National Ecological Observatory Network (NEON) is a new network of locations where a huge range of data will be collected for 30 years following its completed construction. According to information obtained March 2014 from the NEON website, construction has been completed on 25 sites, and 27 sites are planned for construction in 2014. At these sites there are also facilities for ecologists to perform experiments, utilizing the data being collected. The experiments and observational data will be used to build continent-scale models to predict how the environment will respond to threats like invasive species and climate change.

• James Madison University: Ecology
• Chartered Institute of Ecology and Environmental Management: Sources of Survey Methods (SoSM)
• Harvard University: Harvard Forest: Research Towers
• University of Wisconsin-Madison: Regime Shifts in Lake Ecosystems: Pattern and Variation
• Nature Education: Trophic Cascades across Diverse Plant Ecosystems
• National Oceanic and Atmospheric Administration: Ecological Modeling Applications
• Texas Tech University: Climate Change Likely Will Allow Tropical Disease to Thrive in United States
• National Ecological Observatory Network: Overview of NEON Science
• University of Notre Dame Environmental Research Center: Regulation of Lake Primary Production by Food Web Structure
• Hydrobiologia: Biomanipulation in Shallow Lakes in The Netherlands: An Evaluation of 18 Case Studies
• The Scientific World Journal: Piscivores, Trophic Cascades, and Lake Management

Based in Washington, D.C., Jason Steele has been writing science articles since 2007. His articles have appeared in a variety of magazines and websites. He received a Bachelor of Science in biology from John's Hopkins and a PhD in biology from the University of Maryland.

Uses of Microbiology in Biology

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1.3: Methods of ecology

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• Clarence Lehman, Shelby Loberg, & Adam Clark
• University of Minnesota via University of Minnesota Libraries Publishing

How do ecologists do ecology? Often, they start with observation, then move to theory—trying to fit observations together to make sense as a whole. Theory then leads to expectations, which in turn lead to experiments. Commonly, experiments aren’t undertaken until there is some theory to be tested and understood.

• Observation
• Serendipity

Observation, theory, and experiment, however, are not the whole story. A large part of science turns out to be serendipity—luck and chance—capitalizing on chance and doing something with it. One example is Alexander Fleming, who discovered penicillin. Some of the bacterial cultures in his lab became contaminated with penicillium mold and the cultures died. That ruined his experiment.

He could have written a memo to the laboratory staff ordering “Always keep mold away from our bacterial cultures. It destroys the cultures and will ruin the hypotheses we are trying to test.” But instead he capitalized on the serendipity, wondered what was happening, and found a substance in penicillium mold that kills bacteria. Fungi and bacteria have been archenemies for perhaps a billion years. Fleming’s discovery has helped physicians actually cure disease, rather than being limited to diagnosing and prognosticating.

Following up on chance is, then, a large part of science. By the way, for an interesting paper, read the original 1929 report by Fleming about penicillium. It is so understated. He writes “the name ‘penicillin’ has been given to filtrates of broth cultures of the mould.” No one had heard of the word before. Then he suggests that “it may be an efficient antiseptic.” One of the greatest discoveries of all time and only, “it may be an efficient antiseptic.”

Cedar Creek is a University of Minnesota research site about thirty miles north of the University’s Saint Paul campus, and is one of the classic ecological research sites in the world. Pictured in Figure \(\PageIndex{1}\) is an experiment set up by Prof. David Tilman. While very carefully designed, it came about because of serendipity—the chance event of a deep two-year drought that altered the abundances of species in a particular way and triggered the idea for this experiment.

Keep your eyes open for such chance events; they can crop up anywhere.