## Measuring Habitat Quality: A Review > [!Abstract]- > Understanding habitat quality for birds is crucial for ecologists and managers, but few papers have explored the advantages and disadvantages of different ways to measure it. In this review I clarify terminology and distinguish habitat quality from related terms, differentiate habitat quality at the levels of individual birds and populations, and describe different field methods for measuring habitat quality. As much as feasible, biologists concerned with habitat quality should emphasize demographic variables while recognizing that reproduction, survival, and abundance may not all be positively correlated. The distribution of birds can also reveal habitat quality (e.g., through patterns of habitat selection), but researchers should first investigate how closely their subjects follow ideal distributions because numerous ecological factors can lead birds to select poor and avoid rich habitats. Measures of body condition can provide convenient measures of habitat quality, but to be useful they must be a consequence, rather than a cause, of habitat selection. Habitat ecologists should use caution before relying on shortcuts from more labor-intensive demographic work. To increase the reliability of our habitat quality measurements, we should work to develop new methods to assess critical assumptions of nondemographic indicators, such as whether birds follow ideal distributions under natural conditions and whether spatial variation in body condition manifests in differential fitness. > [!Cite]- > Johnson, Matthew D. “Measuring Habitat Quality: A Review.” _The Condor_ 109, no. 3 (August 1, 2007): 489–504. [https://doi.org/10.1093/condor/109.3.489](https://doi.org/10.1093/condor/109.3.489). ## Notes %% begin notes %% %% end notes %% %% begin annotations %% ## Annotations | evernote 2016.04.25 As much as feasible, biologists concerned with habitat quality should emphasize demographi variables while recognizing that reproduction, survival, and abundance may not all be positively correlated. To increase the reliability of our habitat quality measurements, we should work to develop new methods to assess critical assumptions of nondemographic indicators, such as whether birds follow ideal distributions under natural conditions and whether spatial variation in body condition  manifests in differential fitness.  Local habitat affects the fitness of animals through variation in resources and environmental conditions (Bernstein et al. 1991, Pulliam 2000). Spatial and temporal variation in habitat conditions thus generate strong selective pressure for habitat selection (Cody 1985), which in turn influences reproduction and survival of individual birds (Brown 1969, Fretwell and Lucas 1970, Sutherland and Parker 1985), and contributes to the regulation of bird populations (Newton 1998). It is no surprise, then, that ornithologists have long recognized the need to understand variation in habitat for birds (Block and Brennan 1993). Van Horne (1983) provided a foundational treatment of habitat quality for vertebrates and cautioned that the density of animals in a habitat can, in some cases, be a misleading indicator of habitat quality. Since the publication of her influential and oft-cited paper (Bock and Jones 2004), biologists have recognized that robust measures of habitat quality require a thorough unraveling of habitat-specific measures of demography (i.e., density, reproduction, and survival measures in each habitat considered). Specifically, I have four objectives: (1) clarify terminology and distinguish habitat quality from related terms, (2) differentiate habitat quality at individual and population levels, (3) outline various ways of measuring habitat quality for wild birds, recognizing methods that emphasize demographic, distributional, and individual condition variables, and (4) review how ornithologists have measured habitat quality in the last two decades. This trade-off in quality and quantity of resources was explored by Hobbs and Hanley (1990), and it underscores the necessity of distinguishing habitat quality from the perspective of individual animals, which seek to maximize their own fitness, from the perspective of conservationists concerned with populations (Pidgeon et al. 2006). Fretwell and Lucas (1970) combined the concepts of habitat and fitness into the notion that a habitat confers fitness on its occupants. Wiens (1989b) considered this contribution to an organism’s fitness the habitat fitness potential, which provides the theoretical basis for habitat quality (Garshelis 2000, Railsback et al. 2003). For example, Franklin et al. (2000) quantified habitat fitness potential for Northern Spotted Owls (Strix occidentalis caurina) as the relative contribution to the overall population of individuals occupying a given habitat. Thus, habitat quality at the level of an individual bird is defined as the per capita contribution to population growth expected from a given habitat. Thus, theoreticians distinguish the quality of habitat in the absence of competition, called fundamental habitat quality, from the quality actually experienced by competing occupants, called realized habitat quality.  Under the ideal free model, fundamental habitat quality corresponds with density. Under a despotic distribution, the equilibrium density among fundamentally rich and poor habitats depends on the relative competitive abilities of strong and weak competitors. If weak competitors are much more influenced by competition than strong competitors, the density of birds in poor habitats is likely to be higher than that in rich habitats (Bernstein et al. 1991). In thi case, density will be a misleading indicator ofhabitat quality, and prioritizing habitats should involve measuring the performance of individual birds to assess variation in realized habitat quality.  In this light, the question ‘‘which habitat is best?’’ can be reexamined by asking, how do we measure habitat quality for the relevant managemen unit (populations), when habitat selectionis a process operating at the individual level?  To understand individual habitat quality for population management purposes, we must consider how temporal and spatial scales influence habitat choices and their demographic consequences (Wiens 1989a, Lambrechts et al. 2004). A habitat’s quality can change rapidly for a given species, and care must be taken to understand when resources are most limited and when consequences of habitat occupancy most influence a population (Sherry and Holmes 1995). Indeed, habitat is defined not only by the resources necessary for survival and reproduction,but also by the conditions that constrain their use (Morrison et al. 2006). This descriptive approach to examining wildlife-habitat relationships \[comparing animal distribution or demography to aspects of habitat, especially vegetation (Scott et al. 2002, Morrison et al. 2006)\] is of limited use (Morrison 2001), and experimental work is underutilized to test hypotheses relating habitat quality to features of the landscape humans can potentially influence, such as vegetation cover, forest stand characteristics, habitat fragmentation, and so on. Nonetheless, the features hypothesized to govern habitat quality are feasibly quantified in some systems, allowing habitat quality to be measured directly. Without adequate knowledge of critical resources and constraints and established protocols for how to measure them, researchers aiming to assess avian habitat quality directly may be tempted to use crude vegetation measurements (often gross vegetation type) as surrogates for habitat quality, which is unlikely to yield worthwhile results. Here, I classify these bird-based indicators of habitat quality into three broad groups—demographic, distributional, and individual condition measures— and describe some strengths and limitations of each. As explained earlier, habitat quality is best defined from an individual bird’s perspective as the per capita rate of population increase expected from a given habitat.  Thus, the roots of the concept are demographic and habitat-specific measures of density, reproduction, and survival offer some of the best measures of habitat quality (Virkkala 1990, Holmes et al. 1996, Franklin et al. 2000, Murphy 2001, Persson 2003, Knutson et al. 2006). Using demographics to measure habitat quality assumes the parameters are both measurable and attributable to habitat. The chief disadvantage of demographic measures of habitat quality is that they are difficult to obtain. Quantifying multiple indicators of habitat quality is, in theory, critically important, because habitat conditions favoring density,survival, and reproduction may not be the same (Franklin et al. 2000), which could lead to misleading measures of habitat quality if only one parameter is used to rank habitats. However, Bock and Jones (2004) demonstrated that density was usually roughly correlated with habitat quality for breeding birds, and that decoupling of density and reproduction was not associated with most environmental and life history attributes predicted by theory, although discrepancies emerged most frequently in human disturbed landscapes. The principal weakness in using distribution to reveal habitat quality is that numerous scenarios can lead to animals selecting poor and avoiding rich habitats (Rapport 1991, Railsback et al. 2003), including incomplete information (Shochat et al. 2002, Stamps et al. 2005), ecological traps (Battin 2004), time lags and site fidelity (Davis and Stamps 2004), strong despotic distributions (Parker and Sutherland 1986), a lack of high-quality habitat (Halpern et al. 2005), and others (Bernstein et al. 1991, Block and Brennan 1993, Kristan 2003). Thus, researchers should first establish how well a given system adheres to patterns of ideal habitat selection before using animal distribution to reveal variation in habitat quality (Clark and Shutler 1999, Pulliam 2000, Morris 2003, Zimmerman et al. 2003). Despotic distribution models predict that dominant individuals should settle disproportionately in the highest quality habitat. **When we know what resources and ecological constraints govern fitness and can measure them, measuring habitat quality directly is advisable, but it is often impractical in field settings. In addition, for managers to effect change for wild birds, they must work to identify on-the-ground variables that influence avian demography. However, reproduction, survival, and abundance maynot all be positively correlated, which can lead to misleading indicators of habitat quality.** **When quantifying variables related to the distribution of birds as measures of habitat quality (e.g., habitat selection or habitat occupancy), investigators should first investigate how closely their study species follow ideal distributions, because a variety of ecological factors can lead birds to select poor and avoid rich habitats, violating critical assumptions of all distributional measures. Resolving whether a given bird population more closely follows a free or despotic distribution will also determine whether density is likely to be correlated with fundamental habitat quality. To improve the reliability of distributional measures of habitat quality, ecologists need more approaches for assessing model assumptions that do not require measuring fitness.**  Despite its importance to the discipline and the myriad recognized ways it can be measured, there have been few reviews of habitat quality and how it can be quantified by ornithologists (but see introductions of James 1971, Bernstein et al. 1991, Block and Brennan 1993, Sergio and Newton 2003, Pidgeon et al. 2006). %% end annotations %% %% Import Date: 2024-08-15T08:06:26.428-06:00 %%