Fitness landscapes and life‐table response experiments predict the importance of local areas to population dynamics

Abstract

Abstract. Animal resource requirements differ among life-history stages, and thus, habitat is most appropriately thought of as specific to a particular life stage. Accordingly, different habitats may vary in their significance as functions of (1) the sensitivity of population growth to the life stage for which the habitat is most important, (2) spatial association of each habitat to other habitats, and (3) the abundance of the habitat in question. We used an analogy to a life-table response experiment to develop spatial models linking key habitats to rates of population increase in Greater Sage-grouse. We parameterized models linking demographic rates to vegetation and physical attributes of habitats, including spatial association of some habitats to others, using a decade-long study of Greater Sage-grouse in central Nevada. We modeled the contribution of each pixel in the landscape to regional k (finite rate of population increase) using functional relationships between demographic rates and the attributes of that pixel, and the sensitivity of k to each demographic rate. We incorporated the following demographic rates into our model: female nesting success, survival of chicks from hatching to 45 d, and adult female annual survival. We also incorporated the probability a site was used for nesting. Chick survival (62%) and nest site selection (21%) explained most of the variance in lambda. We found that only~8% of all habitat for Greater Sage-grouse contributed to k > 1. Habitat supporting population growth occurred in mid-high elevation areas with moderate slopes, and a high percent cover of sagebrush, and in nesting areas close to late-brood habitat. Our models indicate that a relatively small proportion of habitat available to Greater Sage-grouse in central Nevada is responsible for maintenance of the population in our study system. We suggest that the general approach we describe here can be used to improve understanding of habitats most likely to regulate populations in other systems, providing an important tool in ecology and conservation.

Effects of power lines on habitat use and demography of greater sage‐grouse (Centrocercus urophasianus)

“…We also found chick survival near the FG transmission line was reduced in years of high raven numbers. However, on average, areas near the FG transmission line were associated with the highest levels of chick survival in our system, which suggests this habitat remained the best option for brood‐rearing (Kane et al ) despite high mortality during years of greater predator abundance. Raven densities have been reported to be greater near sage‐grouse brood‐rearing areas (Bui et al ), indicative of response (either numerical or functional) by ravens to increased food abundance.…”

Using satellite‐derived estimates of plant phenological rhythms to predict sage‐grouse nesting chronology

“…Given that long‐term forecasts for western North America suggest accelerating land‐use and climate changes in the coming decades (Garfin, Jardine, Merideth, Black, & LeRoy, 2013; Seager et al., 2012) we expect several patterns to emerge along elevational clines. First, within these dry habitats, sage‐grouse seek the relatively more productive sites during the brood‐rearing phase to extend access to succulent vegetation (Kane, Sedinger, Gibson, Blomberg, & Atamian, 2017). To mitigate plant desiccation birds can select wetland habitats (Donnelly et al., 2018; Donnelly, Naugle, Hagen, & Maestas, 2016), or in areas of high topographic relief, track succulent vegetation upslope or across aspects (Dahlgren, Messmer, et al, 2016).…”

Landscape Conservation Forecasting for Data-Poor at-Risk Species on Western Public Lands, United States

“…The resulting overall value per pixel was between 0 (not suitable) and 1 (maximally suitable). Statistical habitat suitability models are not constructed with multiple HSIs or an evenness index (e.g., [33,34]). However, in the absence of sufficient demographic data, the above methods account for both the contribution of seasonal habitat suitability and whether some seasonal habitats were deficient and, as a result, lowered the overall habitat suitability [33,34] as the evenness index does.…”

“…Despite million-dollar investments in restoration, significant differences in habitat suitability indices between CUSTODIAL and PREFERRED management rarely exceeded 5% in absolute value for GSG (Table 8) and 10% for UPD (Table 9). This was expected because RSFs incorporate important physical characteristics of the landscape that do not change at all, such as distance to roads, leks, and moist summer vegetation for chick rearing (Supplemental File S6) [33,34]. Therefore, absolute values of 5% and 10%, respectively, change in habitat suitability might represent a sizable improvement to GSG and UPD demography.…”