A multispecies test of source–sink indicators to prioritize habitat for declining populations

Abstract

For species at risk of decline or extinction in source-sink systems, sources are an obvious target for habitat protection actions. However, the way in which source habitats are identified and prioritized can reduce the effectiveness of conservation actions. Although sources and sinks are conceptually defined using both demographic and movement criteria, simplifications are often required in systems with limited data. To assess the conservation outcomes of alternative source metrics and resulting prioritizations, we simulated population dynamics and extinction risk for 3 endangered species. Using empirically based habitat population models, we linked habitat maps with measured site- or habitat-specific demographic conditions, movement abilities, and behaviors. We calculated source-sink metrics over a range of periods of data collection and prioritized consistently high-output sources for conservation. We then tested whether prioritized patches identified the habitats that most affected persistence by removing them and measuring the population response. Conservation decisions based on different source-sink metrics and durations of data collection affected species persistence. Shorter time series obscured the ability of metrics to identify influential habitats, particularly in temporally variable and slowly declining populations. Data-rich source-sink metrics that included both demography and movement information did not always identify the habitats with the greatest influence on extinction risk. In some declining populations, patch abundance better predicted influential habitats for short-term regional persistence. Because source-sink metrics (i.e., births minus deaths; births and immigrations minus deaths and emigration) describe net population conditions and cancel out gross population counts, they may not adequately identify influential habitats in declining populations. For many nonequilibrium populations, new metrics that maintain the counts of individual births, deaths, and movement may provide additional insight into habitats that most influence persistence.

Small giants: Tributaries rescue spatially structured populations from extirpation in a highly fragmented stream

“…Identifying such a source–sink structure among patches is therefore paramount in predicting demographic trajectories of fragmented populations. However, characterising spatial population structure can be challenging without detailed knowledge on vital rates of individual patch populations (Heinrichs et al, 2018). Although patch size is often assumed to determine source–sink dynamics (Verboom et al, 2010), patch quality can outweigh patch size in some cases (Fleishman et al, 2002).…”

Wildfire and the ecological niche: Diminishing habitat suitability for an indicator species within semi‐arid ecosystems

“…We applied our models to a robust spatiotemporal dataset of nest locations and fates of greater sage‐grouse ( Centrocercus urophasianus ; hereafter, sage‐grouse), a ground‐nesting sagebrush‐obligate species that acts as an indicator for the ecological integrity of the sagebrush biome (Hanser & Knick, 2011) and occupies semi‐arid ecoregions characteristic of accelerated wildfire regimes (Scholze, Knorr, Arnell, & Prentice, 2006). While sagebrush cover and the predominance of drought drives range‐wide sage‐grouse distributions (Aldridge et al., 2008; Schroeder et al., 2004), reproduction within their population range depends on predator composition, structure of habitat patches, and localized disturbances (Aldridge & Boyce, 2007; Conover & Roberts, 2017; Heinrichs et al., 2018; Walker, Naugle, & Doherty, 2007). Under these conditions, the increasing frequency and extent of localized disturbance may act to decouple individual habitat selection from reproductive success, likely cascading to more widespread effects on species’ population viability.…”

The ecological uncertainty of wildfire fuel breaks: examples from the sagebrush steppe

“…For instance, spatially explicit analysis and simulation modeling can help to identify specific locations and landscape‐scale configurations that minimize the ecological costs of fuel breaks (eg by considering sage‐grouse movement and key source habitats; Heinrichs et al . ) while maximizing the potential to reduce wildfire spread (Gray and Dickson ). Such analyses will prove even more powerful when combined with better information on fuel break effectiveness and ecological effects, not only for sagebrush communities but also for fire‐prone ecosystems and landscapes worldwide.…”