Ecological Indicators and the Bird Community Index
I began a line of research in 1994 with Rob Brooks at the Penn State Cooperative Wetlands Center (now known as Riparia) and Laura Jackson from the USEPA to develop ecological indicators for terrestrial environments using “land birds” (passerines, woodpeckers, doves, cuckoos, hummingbirds, and swifts). That work resulted in the bird community index (BCI), which is both (1) a working indicator that provides a numeric score for a land area based on a species list of sampled birds there, and (2) an illustration of a method for doing that in other regions. What does the indicator indicate?
Ecological indicators reflect some information about the ecological integrity of the land area sampled. Entire books have been written to explain what ecologists mean by “integrity”; this explanation from Simon Fraser University illustrates the concept.
Beginning in the 1970s, James Karr pioneered both the intellectual and practical development of the concept of biological integrity, which he defined as “a balanced, integrated, adaptive community of organisms having a species composition, diversity, and functional organization comparable to that of natural habitat of the region” (Karr and Dudley, 1981. Environmental Management 5: 55–68). A big advantage to using the ecological integrity concept is that “biodiversity” is subject to increase at moderate levels of anthropogenic disturbance. In many cases, species richness and diversity indices are actually comparatively low at sites that might be the best examples of native ecosystems in a region. An index of ecological integrity is structured to offer a clear “dose-response” along the entire gradient of anthropogenic disturbance (although that relationship is not necessarily linear).
Integrity is a complex and controversial topic, and one that makes some ecologists uncomfortable as it relates to the notion of ecological “health”. Their primary objection is to the notion that an ecosystem is supposed to exist in some kind of predetermined state, and that flies in the face of so much of what ecologists have learned over the last century with respect to non-equilibrium concepts. Ecosystems tend not to be static over meaningful time periods, so how can we ascribe some kind of ideal to them?
My response to those objections is twofold. First, I would argue that ecologists often talk past each other when they haven’t explicitly defined the scale at which integrity is to be applied. If we are talking about a 10-ha patch of forest that undergoes a wildfire and converts to an open-canopy shubland, then I would agree that both “forest” and “shrubland” are perfectly acceptable manifestations of the ecological integrity of that 10-ha patch. There is no one thing that that patch should be. Instead, I view integrity as relevant only at broad scales, for example ecoregions. The Ozark/Ouachita/Appalachian Forest ecoregion, for example, has been primarily forested for thousands of years, despite the fact that naturally occurring non-forested patches are also important components of that ecoregion. The point of integrity is not that every square meter of the region needs to be forested or needs to support the maximum possible diversity of species, but that the species that evolved to occur somewhere within the entire ecoregion have the continuing opportunity to do so.
My second response to ecologists who are squeamish about indicators of integrity is that an ecological indicator should be viewed as a hypothesis about integrity, rather than a definitive statement of what “the” integrity “should be”. We cannot know without intensive long-term study if a site really does provide important habitat promoting long-term fitness of any given species. Only where we have invested in such long term observation can we be truly confident that the tenets of Karr’s criteria for integrity are being met.
Ecological integrity is the opportunity for species that evolved in a region to continue to do so.
The Bird Community Index
The original BCI (which we usually term the “Appalachian BCI”) is based on the premise that species differ in their life history traits. Some species adapt well to novel/anthropogenic influences on the landscape; I call these “generalists”. Other species do not respond well to these influences and I consider them to be “specialists”. The delineation is not strictly a response to human disturbances, however, because living things are more complicated than that. Thus folded into these concepts is the idea that some species face inherent challenges to maintaining their populations that others do not, and these might have little to do with response to humans. For example, Nearctic-Neotropical migrants (specialists) face a hazardous two-way journey each year that resident birds (generalists) do not. Birds that normally raise just one brood per year (specialists) might be at a competitive disadvantage against species that might normally raise two or even three (generalists). Integrity at a species assemblage level is a function of the proportions of specialists and generalists in that assemblage. Conceptually, it looks like this:
I find it too limiting, however, to assign individual species as either a specialist or generalist. Most species are mixes of both. For example, a single-brooded resident that must probe bark to find insect prey is a specialist with respect to reproduction and foraging, but a generalist with respect to migratory behavior. To address the variability in life history within species, the BCI does not use the proportion of specialist versus generalist species, it uses the proportion of specialist versus generalist traits among all the species in an assemblage.
We built the original, Appalachian BCI to be one indicator used in concert with many others for a overall ecological assessment of the Mid-Atlantic Highlands Assessment. After proposing a draft indicator based on field data representing a gradient of conditions from the region, we applied the indicator to field data collected from 126 randomly selected locations distributed throughout the assessment region. We identified 4–5 different categories of ecological condition in the region. From the Appalachians, typical land cover from sample sites in the different categories looks like this:
Note how ecological condition is highest in landscapes in which the matrix (the most abundant land cover type) is the native vegetation of the ecoregion. It is only where native forest cover ceases to be the landscape matrix (in this ecoregion taken over by either agricultural or urban land cover) that condition is “low”. The difference between “highest” and “high” condition communities is not that there was more forest cover at the best sites, but rather that those forests generally supported taller trees with a larger trunk diameter and a more dense canopy. In other words, they were older forests than typically found in sites supporting “high” condition bird communities.
Here is an example of the sort of basic changes in life history groups represented at sites in the different categories of condition:
In this illustration, specialist invertivores that forage on the ground or from the bark of trees are very poorly represented at sites in low condition where they represent <4% of the species in bird communities. Their prevalence increases at sites in better condition, where they can occupy about 11–18% of the species at sites in the highest condition category. Exotic species illustrate a similar relationship in reverse: they do not occur at all among the species in highest and high condition communities, but increase to as much as 19% of the species in highly urbanized areas.
The appropriate use of the indicator is to report on the condition of the entire ecoregion, rather than on any individual sample site:
Our work in the Appalachians illustrated that about 10–20% of the land area in the Mid-Atlantic Highlands supported “highest” condition bird communities, about 2–7% of the land area was in the “low-urban” category, and that most of the region (about 29–44% of the land area) was on the cusp between “high” and “low” condition.
Any one of those metrics provides a benchmark state against which changes can be modeled or monitored over time. This is the “report card of ecological condition” for the ecoregion.
We presented different aspects of the Appalachian BCI in a series of reports and papers:
O’Connell, T. J., L. E. Jackson, and R. P. Brooks. 1998. The bird community index: A tool for assessing biotic integrity in the Mid-Atlantic Highlands. Final Report to the USEPA and Report No. 98-4, Penn State Cooperative Wetlands Center, University Park, PA. 57 p.
We followed up with the development of a new BCI for an adjoining ecoregion: the Mid-Atlantic Piedmont and Coastal Plain:
O’Connell, T., R. Brooks, M. Lanzone, and J. Bishop. 2003. A Bird Community Index for the Mid-Atlantic Piedmont and Coastal Plain. Final Report to the U. S. Environmental Protection Agency. Report No. 2003–02, Penn State Cooperative Wetlands Ctr., Pennsylvania State University, University Park, PA. 44pp.
An important question in BCI application is the source data used to apply the indicator. We explored the use of Breeding Bird Survey data in this paper:
O’Connell, T. J., J. A. Bishop, and R. P. Brooks. 2007. Sub-sampling data from the North American Breeding Bird Survey for application to the Bird Community Index, an indicator of ecological condition. Ecological Indicators 7: 679–691.
I made a direct comparison between ecological assessments using the BCI and using the Partners in Flight “conservation value” ranks in this paper, and explored changes in ecological integrity over time:
Another significant offshoot was the development of a new indicator of riparian headwaters in the Mid-Atlantic Region using a BCI-based approach and weighing heavily on the life history of Louisiana Waterthrush:
O’Connell, T. J., R. P. Brooks, R. S. Mulvihill, T. L. Master, and S. E. Laubscher. 2003. Using bioindicators to develop a calibrated index of regional ecological integrity. Final Report to USEPA, STAR Grants Program. Report No. 2003-01, Penn State Cooperative Wetlands Ctr., Pennsylvania State University, University Park, PA. 247 p.
To date, the BCI and additional applications developed by other researchers have been used to construct the USEPA’s Mid-Atlantic Integrated Assessment, to assess cumulative effects of forest loss from mountaintop mining in West Virginia, to assess the condition of New York State’s Adirondack Park, as a component of the National Park Service’s “Vital Signs” monitoring for the Eastern Rivers and Mountains Network, and to help quantify ecological changes in Pennsylvania forests subjected to oil and gas extraction.
Research into different aspects of the BCI approach is ongoing. Current efforts include the development of new BCI models for the Great Plains, Great Lakes, and Northern Hardwoods regions in North America. The approach can theoretically be applied to any terrestrial environment on Earth that supports a large number of territorial breeding birds and has some kind of standardized population monitoring in place that samples birds from discrete locations. Our newest BCI was developed to be applied to the Taiwan Breeding Bird Survey and the nearly complete Irish BCI could be applied to the Atlas of Breeding Birds in Great Britain and Ireland or such monitoring programs as the Countryside Bird Survey.