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.

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.

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.

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.

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.

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 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, 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 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.