Premise 8 - Understanding Biological Responses

Click below to view some of the premises from Karr and Chu (1999).

Understanding biological responses requires measuring across degrees of human influence

FROM "Restoring Life in Running Waters" by James R. Karr and Ellen W. Chu
(Reprinted with permission from Island Press)

Our ability to protect biological resources depends on our ability to identify and predict the effects of human actions on biological systems, especially our ability to distinguish between natural and human-induced variation in biological condition. Thus, even though measures taken at places with little or no human influence (e.g., only from "reference" sites) may tell us something about natural variability from place to place and through time at undisturbed sites, they cannot tell us anything about which biological attributes merit watching for signs of human-caused degradation. To find these signs, sampling and analysis should focus on multiple sites within similar environments across the range from minimal to severe human disturbance.

One could choose sampling sites that represent different intensities of only one human activity, such as logging, grazing, or chemical pollution. It would then be possible to evaluate biological responses to a changing "dose" of a single human influence. Though rare, such a study opportunity could help identify the biological response signature characteristic of that activity (Karr et al. 1986; Yoder and Rankin 1995b). Knowledge of such biological response signatures would give researchers a diagnostic tool for watersheds influenced by unknown or multiple human activities. In reality, however, it is virtually impossible to find regions influenced by only a single human activity.

In most circumstances, diverse human activities interact (e.g., during urbanization) to affect conditions in watersheds, water bodies, or stream reaches. In such cases, sites can be grouped and placed on a gradient according to activities and their effects: industrial effluent is more toxic than domestic effluent, for example, and both pose more-serious threats than low dams, weirs, or levees (Figure 5). Removal of natural riparian corridors damages streams, but conversion to a partially herbaceous riparian area is less damaging than conversion to riprap. Streams grouped this way show striking and systematic differences in biological condition across the gradient of human disturbance (Figure 6).

Figure 5

Figure 5: A priori classification system for ranking Japanese streams. Sites were assigned to one of 21 possible categories based on amount and type of effluent, proximity of dams and other structural alterations, and type of riparian vegetation. Even without quantitative measures from each site, this approach allowed sites to be ranked across a range of human influence.

Figure 6

Figure 6: Benthic indexes of biological integrity IBISs for 1 15 Japanesestreams (from Rossano 1995). The top panel shows B-IBIs calculated from half of the II 5-stream data set (circles), which was used to initially select and test metrics for use in the B shows B-IBI values calculated from thesecond half of the data set (pluses); the metrics and scoring criteria used for these data were the metrics and criteria developed from the first half. In the bottom panel, all 115 B-IBIs are plotted.

Sometimes a single variable can capture and integrate multiple sources of influence. Relatively simple descriptors--human population in the watershed, percentage of impervious area, percentage of land area devoted to agriculture or urban uses, or percentage of developed area--are adequate for regional watershed analyses (Meeuwig and Peters 1996). The percentage of impervious area, for example, summarizes the multiple effects of paving, building, and other consequences of urbanization, as in a recent study of Puget Sound lowland streams (Figure 7; see also Maxted 1997). This measure provides a simple surrogate of human influence that works well at percentages of impervious area from near 0% to 60%. Unfortunately, it is less useful in understanding the often large variation in biological condition at some percentages of imperviousness (e.g., 3% to 8%; see Figure 7). Finding the differences in human activity that can explain these biological differences requires information from the watersheds that is more detailed.

Figure 7

Figure 7: Benthic index of biological integrity (B-IBl) plotted against the percentage of impervious area for urban, suburban, and rural stream sites in the Puget Sound lowlands, Washington (from Kleindl 1995). Though B-IBI clearly decreases with increasing impervious area, this plot offers no insight into B-IBI differences among sites with similar percentages of impervious area, especially at low percentages (3% to 17%).

Alternatively, sites may be grouped into qualitative disturbance categories. In a study of recreational influence on stream biology in the northern Rocky Mountains (Figure 8), Patterson (1996) classed sites into four categories associated with different levels of human activity: (1) little or no human influence in the watershed; (2) light recreational use (hiking, backpacking); (3) heavy recreational use (major trailheads, camping areas); and (4) urbanization, grazing, agriculture, or wastewater discharge. Patterson demonstrated that light recreational activity did not substantially reduce B-IBIs in comparison with undisturbed watersheds. Heavy recreational use, in contrast, did significantly alter the benthic invertebrates, although not as much as more-intensive uses including urbanization and agriculture.

Figure 8

Figure 8: Benthic indexes of biological integrity (B-IBIs) for stream sites in Grand Teton National Park, Wyoming (from Patterson 1996). Before B-IBIs were determined, these sites had been placed into four categories of human influence: little or no human activity (NHA), light recreational use (LR), heavy recreation use (HR), and other (0). B-IBIs revealed no significant difference between sites with little or no human activity and those having low recreational use. But B-IBIs were significantly lower for sites used heavily for recreation and lower still for sites subjected to other uses -- specifically, urbanization, grazing, agriculture, and wastewater discharge.

A similar approach was taken in a study of biological response to chemical pollution on three continents: South America, Africa, and southeastern Asia (Thorne and Williams 1997). The authors classified sites according to a pollution gradient based on the integration of six measures of chemical pollution. Biological condition, as indicated by metrics such as total taxa richness (families) and mayfly, stonefly, and caddisfly richness, clearly went down as pollution went up. The biological responses in the three tropical regions were similar; the patterns parallel those seen in temperate regions even though the faunas are all very different.

Data collected over a number of years at the same site(s) can also reveal biological responses as human activities change during that period. Regardless of how one represents a range of human influence among study sites, sampling from sites with different intensities and types of human activity is essential to detect and understand biological responses to human influence. The goal is to compare like environments with like environments--to isolate and understand patterns caused by human activities at sites within those like environments.

Too many existing studies confound patterns of human influence with natural variation over time at undisturbed sites or across different environment types. In other situations, researchers combine measures of human activity, the physical and chemical manifestations of those activities, and their biological consequences in a heterogeneous analysis with ambiguous results. Those analyses may even include measures of physical environment such as stream gradient. When this range of factors (different human influences on different environment types) is lumped in a single analysis, it becomes almost impossible to understand the causes or consequences of human versus natural events.

Consider the following analogy. Three experiments are designed: one to understand variation in natural biological systems as a function of stream size; another to distinguish the effects of pesticide runoff on streams of first, fourth, and sixth order; and a third to define the effects of pesticides on plants and insects. Analyzing samples from the first series of stream sites would tell you about biological responses to changing stream size. Samples from the second series would illustrate changing human influence as a function of stream size. Samples from the third would distinguish responses of different taxa. It would be silly to mix the data from the three studies in a single statistical analysis, without regard to which study the individual samples came from. Yet by using analytical procedures that mix the effects of natural and human-induced variation (in a single correlation matrix, for example), researchers are essentially doing just that: they are ignoring the context of the different components of their data, making it difficult to distinguish the biological signs relevant to resource management or protection. They then confound the sources of the variance they see, even if their initial sampling setup would have permitted discrimination among those sources. Univariate and multivariate analyses all too often suffer from this flaw.

Sampling only from "reference" sites creates a similar problem because it does not provide a way to document which biological attributes vary with human influence (see Premise 31). Careful thought about which variables best summarize human influence and the relationships among those variables should be the foundation of monitoring protocols. Creating opportunities to discover biological patterns in relation to human activity must be foremost.

References

Karr, J. R., K. D. Fausch, P. L. Angermeier, P. R. Yant, and I. J. Schlosser. 1986. Assessment of biological integrity in running waters: A method and its rationale. Illinois Nat. Hist. Surv. Spec. Publ. 5.

Kleindl, W.J. 1995. A benthic index of biotic integrity for Puget Sound lowland streams, Washington, USA. MS thesis, University of Washington, Seattle.

Maxted, J. R. 1997. Biology, probability, and the obvious. Hum. Ecol. Risk Assess. 3: 955-965.

Meeuwig, J. J., and R. H. Peters. 1996. Circumventing phosphorus in lake management: A comparison of chlorophyll a predictions from land use and phosphorus models. Can. J. Fish. Aquat. Sci. 53: 1795-1806.

Patterson, A.J. 1996. The effect of recreation on biotic integrity of small streams in Grand Teton National Park. MS thesis, University of Washington, Seattle.

Rossano, E.M. 1995. Development of an indix of biolocial integrity for Japanese streams (IBI-J). MS thesis, University of Washington, Seattle.

Thorne, R. St. J., and W. P. Williams. 1997. The response of benthic invertebrates to pollution in developing countries: A multimetric system of bioassessment. Freshwater Biol. 37: 671-686.

Yoder, C. O., and E. T. Rankin. 1995b. Biological response signatures and the area of degradation value: New tools for interpreting multimetric data. Pages 263-286 in W. S. Davis and T. P. Simon, eds. Biological Assessment and Criteria: Tools for Water Resource Planning and Decision Making. Lewis, Boca Raton, FL.

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