An ecosystem is a community of living and non-living components that interact in an area. This can be as large as the earth itself or a forest full of plants and animals, or as small as a stomach with its array of microbial inhabitants. Ecosystem health can be measured in different ways, but one good indicator is biodiversity, a measure of the variety of biological species in an ecosystem.
We can evaluate biodiversity using a measure called the Shannon-Wiener Index, proposed by Claude Shannon and Norbert Wiener in the 1940s. The Shannon-Wiener Index is a unitless measurement, calculated as H. The index uses two variables: species richness, or the number of species present, indicated by K, and species evenness, or proportion of each species, indicated by PI. Species richness is the number of unique species in an ecosystem. This example has seven. Species evenness measures how species in an ecosystem are distributed. This means that an ecosystem in which the different species have similar numbers is more even than one where one or two species account for most of the organisms, like this one, relatively overrun with hares.
Now that we know what to measure, let's learn how to measure biodiversity. Since ecosystems can be huge, ecologists had to figure out ways to randomly sample large areas quickly. The simplest of these is the quadrat, which is a frame of fixed size, typically placed at random within a sampling site. Scientists survey the area inside the quadrat, logging the species richness and also their evenness. Using these little windows placed at multiple spots over an ecosystem, they can extrapolate their findings to give diversity estimates for the entire study area. But although this technique allows for a manageable assessment of a large area, it's not perfect. Random placement of quadrants may miss individuals, resulting in under-representation of species and incorrectly low biodiversity estimates.
This limitation means that some communities, especially patchy or non-uniform ones, are better sampled by a more structured approach. Here, our meadow borders the forest and, in reality, consists of different habitat patches. To cover this community fairly, we can divide the landscape into core habitats and importantly, edge habitats. Often, edge areas have more biodiversity because species from both habitat types might live there. But this might get missed in traditional random sampling. Instead, to measure the biodiversity across a community like this, a good strategy may be to first sample the core areas randomly using quadrats. The data collected can then be used to calculate the H value for each core habitat. Next, a transect or sampling line can be laid across each core habitat, extending over into the edge area. Species richness and evenness can then be recorded using quadrats placed at set points along these lines. Now using the Shannon-Wiener formula, the diversity index can be calculated for each distance along the transect, and these can be compared. An area with a greater H value is generally more diverse than one with a lower H. This combined random quadrat and transect technique gives a versatile and more fair assessment of how the different habitats within the same community compare in terms of diversity.
In addition to species measures, scientists may also take measures of the chemical components of an ecosystem to assess its health. For example, they might check for pollution, or examine soil quality by measuring the nutrients present. This information can also be useful to help explain changes in patterns of biodiversity in different regions of a community. So, in our example, if the meadow has lower quality soil than the forest and the edge, it might support less species.
In this lab, you'll measure biodiversity and soil quality in two different core regions, and then examine how biodiversity is affected along an edge habitat.
Populations do not live in isolation; thus, every population interacts with others in certain ways. These interactions give rise to a network of populations. Hence, an ecological community is composed of such population networks of various species interacting with each other within the same area. These biological, or biotic, components may also closely interact with non-living, or abiotic, components, forming an ecosystem. Ecosystems may be as small as the microbial communities inside the human digestive tract, structured by the pH and nutrients of their environment, or as large as a forest containing trees and insects closely linked through the carbon cycle. Ecologists and conservationists have become increasingly interested in ecosystems as humans continue to make major changes to them globally through urbanization and climate change. Alterations to any single component of an ecosystem can affect other closely-linked components, potentially causing drastic changes to the entire system. For these reasons, quantifying and predicting the current and future “health” of ecosystems has become a major topic of ecological research.
Biodiversity
The term “ecosystem health” is metaphorical because and it is difficult to compare the health of very different ecosystems and there is no single value that can be used to quantify how healthy an ecosystem is. For example, deserts and forests have very different species diversities but one is not necessarily healthier than the other. Therefore, multiple metrics have been formulated to represent the health of an ecosystem, and their use depends on the goals of the study. Hence, “ecosystem health” may refer to how valuable an ecosystem is to humans. For example, the value of ecosystem services like carbon sequestration by trees or pollination by bees are used to quantify the health of ecosystems. Other metrics may measure the number of rare species found in an ecosystem, how resistant an ecosystem is to fire, or some other measurements of biotic and abiotic factors. For ecologists, one very popular health measure is that of biological diversity, or “biodiversity.” Biodiversity is a measure of the variety of biological species found in an area and can be calculated using the Shannon-Wiener biodiversity index.
The Shannon-Wiener Index requires two measurements from a local community: species richness and evenness. Species richness is the total number of distinct species within a local community. An area with no species present, such as a freshly paved parking lot, would have a richness value of 0. Rainforests, known for supporting some of the most diverse communities on Earth, have a much greater species richness. While having many species generally coincides with having a diverse and healthy ecosystem, the evenness also needs to be considered. For instance, when one species dominates the area while the others are very rare, the biodiversity in this area is lower than in an area with species of equal abundance. Therefore, areas with many species that are relatively equal in abundance have the highest scores of biodiversity.
Shannon-Wiener is not the only measure of ecosystem biodiversity and health. For example, a popular index, named the EPT index, is used to determine water quality in river systems by assigning values of healthiness to individual organisms. More specifically, this index considers three pollutant-sensitive orders of invertebrates found in rivers, Ephemeroptera (mayflies), Plecoptera (stoneflies), and Trichoptera (caddisflies). The presence of these pollutant-intolerant species in a waterway is used as an indication of good water quality and the ecosystem in question is considered to be healthy.
Often, ecologically-relevant areas are too large to be sampled in entirety. To resolve this problem, ecologists sample multiple smaller plots throughout the study area using quadrats, which are small frames of a predetermined size placed at points throughout the study site, in which a researcher identifies and records all individuals of species of interest. When enough quadrat samples are considered, scientists can extrapolate to make accurate estimates of ecological communities.
Impacts of Ecological Changes
Most natural ecological changes happen over an extended time scale. In addition, humans continue to alter ecosystems. To assess long-term changes in ecosystems, scientists have set up Long Term Ecological Research sites (LTERs). One of the longest running LTERs is the Hubbard Brook Experimental Forest located in New Hampshire, United States. This site and others have increased knowledge about ecosystem scale patterns resulting from deforestation, changes to hydrological regimes, and other long-term ecological disturbances1.
When a major change occurs very rapidly, it is called an ecological disturbance. Fires, hurricanes, and floods are examples of ecological disturbances. Disturbances can alter an ecosystem by wiping out nutrients and changing the composition of the biological community. After a disturbance, the most resistant and resilient species are favored for survival. A resistant species or community is one that can survive major disturbances with minimal detriments and quickly recover from a disturbance, like dandelions after a lawn is mowed. Sampling a site for many years before and after disturbances is unfeasible, but comparing different areas with different disturbance regimes offers a partial solution to this problem.
Disturbed habitats are usually patchy; therefore, using randomly-placed quadrats might result in underrepresentation of species and incorrect biodiversity estimates. For this reason, it is essential to consider the surroundings and some of the characteristics of the habitat that is being studied. This is accomplished in landscape ecology by studying both core and edge habitats. A core habitat is located centrally within a patch, surrounded by the same type of habitat. In contrast, an edge habitat, also known as boundary habitat, borders a different habitat type. Edge habitats, such as where a forest habitat meets a meadow habitat, may have increased biodiversity because species from both habitat types may be found in them. Such differences in biodiversity at the edges of habitats are called edge effects. To assess these transitional areas, ecologists use paths along habitats, called transects, and record the biodiversity of small sampling sites at set intervals along the path. However, not all habitats will have edge effects and sometimes edge species are invasive and can grow in a wider range of habitats, thus not be indicative of a “healthy” ecosystem.
In addition to species measures scientists may also take measures of the chemical components of an ecosystem to assess its health. For example, they might check for pollution, or examine soil quality by measuring the nutrients present. This information can also be useful to help explain changes in patterns of biodiversity in different regions of a community. There are also many variables including temperature, precipitation over a certain time frame, and functional traits of the species, that would be hard to measure and would require advanced statistical analyses. Ecologists are constantly working on new ways to record these variables across greater scales of time and space. This has given way to new methods such as remote sensing of ecosystems, in which satellite imagery is used to estimate variables of interest across the entire globe2. These data require the use of multivariate statistics and other complex mathematical tools that are continually being developed.
As the human populations continue to grow and alter ecosystems worldwide, scientists and concerned citizens work towards conserving and preserving threatened ecosystems. One way to restore heavily altered ecosystems is through bioremediation, which involves the release of biological organisms, usually microorganisms, to break down pollutants and restore favorable traits to an ecosystem3. One example of this is the release of microorganisms in wastewater to break down pollution and restore water to a habitable condition for fish4. Therefore, inventive ways of restoring ecosystems will become increasingly important to remediate human effects on ecosystems.
References
- Likens, Gene E. Fifty years of continuous precipitation and stream chemistry data from the Hubbard Brook ecosystem study (1963–2013). Ecology. Vol. 98 , 8: 2224.
- Zhaoqin Li, Dandan Xu, Xulin Guo. Remote Sensing of Ecosystem Health: Opportunities, Challenges, and Future Perspectives. Sensors (Basel). 2014, Vols. 14(11): 21117–21139.
- Garbisu, Itziar Alkorta Lur Epelde Carlos. Environmental parameters altered by climate change affect the activity of soil microorganisms involved in bioremediation. FEMS Microbiology Letters. 2017, Vol. 364, 19.
- P. Padmavathi, K. Sunitha, K. Veeraiah. Efficacy of probiotics in improving water quality and bacterial flora in fish ponds. Afr. J. Microbiol. Res. 2012, 6(49). 7471-7478.
An ecosystem is a community of living and non-living components that interact in an area. This can be as large as the earth itself or a forest full of plants and animals, or as small as a stomach with its array of microbial inhabitants. Ecosystem health can be measured in different ways, but one good indicator is biodiversity, a measure of the variety of biological species in an ecosystem.
We can evaluate biodiversity using a measure called the Shannon-Wiener Index, proposed by Claude Shannon and Norbert Wiener in the 1940s. The Shannon-Wiener Index is a unitless measurement, calculated as H. The index uses two variables: species richness, or the number of species present, indicated by K, and species evenness, or proportion of each species, indicated by PI. Species richness is the number of unique species in an ecosystem. This example has seven. Species evenness measures how species in an ecosystem are distributed. This means that an ecosystem in which the different species have similar numbers is more even than one where one or two species account for most of the organisms, like this one, relatively overrun with hares.
Now that we know what to measure, let's learn how to measure biodiversity. Since ecosystems can be huge, ecologists had to figure out ways to randomly sample large areas quickly. The simplest of these is the quadrat, which is a frame of fixed size, typically placed at random within a sampling site. Scientists survey the area inside the quadrat, logging the species richness and also their evenness. Using these little windows placed at multiple spots over an ecosystem, they can extrapolate their findings to give diversity estimates for the entire study area. But although this technique allows for a manageable assessment of a large area, it's not perfect. Random placement of quadrants may miss individuals, resulting in under-representation of species and incorrectly low biodiversity estimates.
This limitation means that some communities, especially patchy or non-uniform ones, are better sampled by a more structured approach. Here, our meadow borders the forest and, in reality, consists of different habitat patches. To cover this community fairly, we can divide the landscape into core habitats and importantly, edge habitats. Often, edge areas have more biodiversity because species from both habitat types might live there. But this might get missed in traditional random sampling. Instead, to measure the biodiversity across a community like this, a good strategy may be to first sample the core areas randomly using quadrats. The data collected can then be used to calculate the H value for each core habitat. Next, a transect or sampling line can be laid across each core habitat, extending over into the edge area. Species richness and evenness can then be recorded using quadrats placed at set points along these lines. Now using the Shannon-Wiener formula, the diversity index can be calculated for each distance along the transect, and these can be compared. An area with a greater H value is generally more diverse than one with a lower H. This combined random quadrat and transect technique gives a versatile and more fair assessment of how the different habitats within the same community compare in terms of diversity.
In addition to species measures, scientists may also take measures of the chemical components of an ecosystem to assess its health. For example, they might check for pollution, or examine soil quality by measuring the nutrients present. This information can also be useful to help explain changes in patterns of biodiversity in different regions of a community. So, in our example, if the meadow has lower quality soil than the forest and the edge, it might support less species.
In this lab, you'll measure biodiversity and soil quality in two different core regions, and then examine how biodiversity is affected along an edge habitat.
An ecosystem is a community of living and non-living components that interact in an area. This can be as large as the earth itself or a forest full of plants and animals, or as small as a stomach with its array of microbial inhabitants. Ecosystem health can be measured in different ways, but one good indicator is biodiversity, a measure of the variety of biological species in an ecosystem.
We can evaluate biodiversity using a measure called the Shannon-Wiener Index, proposed by Claude Shannon and Norbert Wiener in the 1940s. The Shannon-Wiener Index is a unitless measurement, calculated as H. The index uses two variables: species richness, or the number of species present, indicated by K, and species evenness, or proportion of each species, indicated by PI. Species richness is the number of unique species in an ecosystem. This example has seven. Species evenness measures how species in an ecosystem are distributed. This means that an ecosystem in which the different species have similar numbers is more even than one where one or two species account for most of the organisms, like this one, relatively overrun with hares.
Now that we know what to measure, let's learn how to measure biodiversity. Since ecosystems can be huge, ecologists had to figure out ways to randomly sample large areas quickly. The simplest of these is the quadrat, which is a frame of fixed size, typically placed at random within a sampling site. Scientists survey the area inside the quadrat, logging the species richness and also their evenness. Using these little windows placed at multiple spots over an ecosystem, they can extrapolate their findings to give diversity estimates for the entire study area. But although this technique allows for a manageable assessment of a large area, it's not perfect. Random placement of quadrants may miss individuals, resulting in under-representation of species and incorrectly low biodiversity estimates.
This limitation means that some communities, especially patchy or non-uniform ones, are better sampled by a more structured approach. Here, our meadow borders the forest and, in reality, consists of different habitat patches. To cover this community fairly, we can divide the landscape into core habitats and importantly, edge habitats. Often, edge areas have more biodiversity because species from both habitat types might live there. But this might get missed in traditional random sampling. Instead, to measure the biodiversity across a community like this, a good strategy may be to first sample the core areas randomly using quadrats. The data collected can then be used to calculate the H value for each core habitat. Next, a transect or sampling line can be laid across each core habitat, extending over into the edge area. Species richness and evenness can then be recorded using quadrats placed at set points along these lines. Now using the Shannon-Wiener formula, the diversity index can be calculated for each distance along the transect, and these can be compared. An area with a greater H value is generally more diverse than one with a lower H. This combined random quadrat and transect technique gives a versatile and more fair assessment of how the different habitats within the same community compare in terms of diversity.
In addition to species measures, scientists may also take measures of the chemical components of an ecosystem to assess its health. For example, they might check for pollution, or examine soil quality by measuring the nutrients present. This information can also be useful to help explain changes in patterns of biodiversity in different regions of a community. So, in our example, if the meadow has lower quality soil than the forest and the edge, it might support less species.
In this lab, you'll measure biodiversity and soil quality in two different core regions, and then examine how biodiversity is affected along an edge habitat.
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