Living in risky landscapes: delineating management units in multithreat environments for effective species conservation

Abstract

Summary1. Managing threatened species to reduce their extinction risk is a widely used, yet challenging, means of halting biodiversity loss. Species show complex spatial patterns of extinction risk, due to spatial variation in both threats and vulnerability across their ranges. Conservation practitioners, however, rarely consider this spatial variation and routinely apply uniform conservation schemes, either throughout the species' ranges, or following administrative borders that do not match ecological boundaries. Most of these schemes are experience-based (e.g. expert opinion) and thus difficult to replicate. 2. We accounted for spatial variation in species' threats by using multivariate techniques [i.e. cluster analyses and multidimensional scaling (MDS)] to delineate management units for more effective conservation. We grouped breeding territories of the endangered Egyptian vulture, according to interterritory similarity in presence and intensity of their threats. 3. The first three MDS axes explained 62% of the data variation. The first axis separated territories in protected areas, with low human presence, but high risk of illegal poisoning from areas highly dominated by humans. The second axis classified territories regarding the density of sheep/goats and griffon vultures and the presence of wind farms. The third axis confronted territories in protected areas with those in unprotected areas with wind farms. 4. We obtained 18 statistically supported groups (i.e. management units) including 86% of the territories. Territories within the same group were geographically close, agreeing with the underlying spatial autocorrelation of threats. However, six groups (33%) were distributed over more than one administrative region, which will require inter-regional coordination for cost-effective conservation. 5. Synthesis and applications. Our results show wide spatial variation for species' threats and suggest incorporation of this heterogeneity into conservation schemes. We demonstrate how multivariate statistics, coupled with uncertainty analysis, can be employed in a systematic and repeatable way to deal with the heterogeneous landscapes of risk that species face across their ranges. Our approach allows researchers and managers to delineate management units according to similarity in species' threats for any targeted organization level (e.g. individuals, territories, populations). The results can be visualized in Euclidean and geographical spaces for better interpretation, allowing managers to design more effective conservation actions.

Genetic analysis of red deer (Cervus elaphus) administrative management units in a human-dominated landscape

“…Therefore, managing the AMUs separately assumes that these units equate to GMUs, thus representing more or less disconnected (i.e., closed or genetically separated) populations that experience limited reproductive exchange of individuals with other populations (Moritz 1994). However, several recent studies have shown that if this implicit assumption is violated in wildlife management, actions in one management unit (MU) can substantially influence management effectiveness in neighboring units (Hemami et al 2005;Robinson et al 2008;Olea and Mateo-Tomás 2014;Stillfried et al 2017). In such cases, management would need to be extended towards a larger spatial scale that includes multiple MUs and considers the degree of connectivity among them (e.g., Robinson et al 2008;Wäber et al 2013).…”

Small‐scale spatial and temporal variation in the demographic processes underlying the large‐scale decline of eiders in the Baltic Sea

“…Unfortunately, the current practice of applying uniform management and conservation schemes over large spatial scales often ignores the fact that the types and intensities of threats may vary in space and time across the range of a single species, and sometimes even among adjacent populations (e.g., Cowlishaw et al 2009;Olea and Mateo-Tomás 2014). Therefore, assessing spatial variation in threats and management practices across local populations is crucial for successful species conservation, yet this issue has so far received only rudimentary attention from scientists and conservation practitioners (Olea and MateoTomás 2014).…”

Identifying Birds' Collision Risk with Wind Turbines Using a Multidimensional Utilization Distribution Method

“…Relatively high collision fatality rates have been recorded at several large wind farms in locations indicating that turbines pose a risk, especially to large raptors and other soaring birds (Marques et al 2014). The Griffon vulture ( Gyps fulvus ) is one of the raptor species frequently killed by collision with wind turbines in southern Spain (Barrios and Rodríguez 2004; De Lucas et al 2008, 2012; Olea and Mateo‐Tomás 2014). For instance, Carrete et al (2012) found 342 dead Griffon vultures during a 10‐year period (Jan 1998–Mar 2008) in an area of 34 wind farms with 799 turbines in the province of Cádiz, southern Spain.…”