## Delusions in Habitat Evaluation: Measuring Use, Selection, and Importance > [!Cite]- > Garshelis, David L. “Delusions in Habitat Evaluation: Measuring Use, Selection, and Importance,” n.d. ## Notes %% begin notes %% This is a chapter in the book [*Research Techniques in Animal Ecology: Controversies and Consequences*](https://www.jstor.org/stable/10.7312/boit11340) published by Columbia University Press. %% end notes %% %% begin annotations %% ## Annotations | evernote 2016.04.24 Management of wildlife populations, whether to support a harvest, conserve threatened species, or promote biodiversity, generally entails habitat management. Habitat management presupposes some understanding of species’ needs. To assess a species’ needs, researchers commonly study habitat use and, based on the results, infer selection and preference. Presumably, species should reproduce or survive better (i.e., their fitness should be higher) in habitats that they tend to prefer. Thus, once habitats can be ordered by their relative preference, they can be evaluated as to their relative importance in terms of fitness. Managers can then manipulate landscapes to contain more high-quality habitats and thus produce more of the targeted species. Habitat manipulations specifically intended to produce more animals have been conducted since at least the days of Kublai Khan ( A .D . 1259–-1294; Leopold 1933). Rosenzweig and Abramsky (1986) characterized preferred habitats as those that confer high fitness and would therefore support a high equilibrium density (in the absence of other confounding factors, such as competitors). Generally, the purpose for determining preferences is to evaluate habitat quality or suitability, which I define as the ability of the habitat to sustain life and support population growth. Importance of a habitat is its quality relative to other habitats—its contribution to the sustenance of the population. Assessments of habitat quality and importance (i.e., habitat evaluation) are thus based on the presumption that preference, and hence selection, are linked to fitness (reproduction and survival) and that preference can be gleaned from patterns of observed use.  McClean et al. (1998) used real data on young turkeys ( Meleagris gallopavo), which have fairly narrow and well-known habitat requirements, to compare results of six analytical techniques for assessing habitat selection. In this case, the methods that treat individuals as sample units tended to be less apt to detect habitat selection. This method (compositional analysis) has become increasingly popular because it enables assessment of both second-order and third-order selection and yields statistical comparisons (rankings) among habitats (Donázar et al. 1993; Carroll et al. 1995; Macdonald and Courtenay 1996; Todd et al. 2000). Additionally, because the data are arranged analogous to an ANOVA , in which between-group differences can be tested against within-group variation among individuals, it provides a means of testing for differences among study sites (e.g., with different habitats, different animal density, or different predators or competitors), seasons or years (e.g., with different food conditions), sex–age groups, or groups of animals with different reproductive outputs or different fates (Aebischer et al. 1993a; Aanes and Andersen 1996). Ideally, studies should identify relationships between habitat characteristics and the animal’s fitness. Most of these \[demographic response design studies\] investigated differences in animal density among habitats. Fourteen studies, all on birds, related reproduction (i.e., nesting success) to habitat of nest sites. Three studies, two on birds and one on mammals, attempted to find an association between habitat and survival (Hines 1987; Klinger et al. 1989; Loegering and Fraser 1995), but only one (Loegering and Fraser 1995) detected such a relationship. A fatal flaw of habitat selection studies in general, especially use–availability studies, is that they are based on the assumption that the more available a resource is, the more likely an animal should be to use it. The assumption that we can infer habitat quality of suitability from studies of habitat selection--that selection, even if accurately measured. is directly related to each habitat's potential contribution to individual fitness and hence the population's growth rate--represents what I would call the second fatal flaw in the process of habitat evaluation. The best measure of habitat quality would be a test of its effects on demographic parameters such as population growth and carrying capacity. Sherry and Holmes (1996) felt that density should be relied on as an indicator of habitat quality only if it is corroborated by other data, such as was the case in their study. A final major problem, discussed previously in relation to use-availability and site attribute design, is scale.   A great deal of effort continues to be invested in habitat-related studies of wildlife. In the United States, federal land management agencies in particular have focused on developing formalized procedures for evaluating habitat for wildlife (Morrison et al 1998). The utility of models is to guide further study or help make predictions and decisions regarding complicated systems; thus they warrant testing, but that testing should be viewed as a never-ending process of refinement, properly called benchmarking or calibration.0] Kirsh (1996:37-38): "Unfortunately, proximate habitat features may not indicate habitat suitability, nor do they reveal the possible selective pressures that influence habitat selection in a system. One must measure components of fitness, determine factors that influence fitness, and relate fitness and factors influencing fitness to habitats or habitat features." Demographic response studies are the only means of truly evaluating the relative importance and suitability of habitats for supporting animal populations. Oddly, Hanson (1996) suggested that habitat-specific survival might confuse perceptions of habitat selection. In his small mammal study, perceived habitat selection appeared to be a consequence rather than a cause of differential survival. It seems to me that such knowledge of habitat-specific survival is exactly the desired objective. For many species, habitat-specific densities may be easier to measure than habitat specific reproduction or survival, but density studies may yield uncertain or misleading results because density is the end result of various processes, both demographic and behavioral, each with potentially different habitat-specific responses. Controlled experiments should be used more often in assessing effects of habitat on demographic parameters such as density or reproduction, however even elegant experiments may produce unexpected results in complex systems. A major inherent but generally unstated (maybe unrecognized) assumption of habitat suitability models is that high-quality habitats (i.e., habitats that confer high fitness) are in fact suitable (i.e., able to sustain a population; Kellner et al. 1992). %% end annotations %% %% Import Date: 2024-08-15T07:28:20.566-06:00 %%