A multifaceted index of population health to detect risk-prone populations and underlying stressors in wildlife

Local declines of wild populations represent the most visible part of biodiversity loss, and their detection often relies on long-term surveys. An alternative to identify risk-prone populations is to use indicators informing on their general health (i.e., their general fitness and ability to cope with changing environment) based on simple and complementary parameters estimated from snapshot sampling. However, most studies on wildlife population health focus on one or only a few parameters, yielding potentially biased conclusions for conservation. Here, we developed a multifaceted index of population health by combining 3 complementary indicators, namely path-ological, ecological, and genetic indicators, based on an integrative approach traditionally used to assess ecosystem multifunctionality. We investigated their complementarity and relevance for detecting brown trout (Salmo trutta) risk-prone populations at a large spatial scale, and the underlying environmental stressors. The multifaceted health index properly represented the individual indicators' complementary information. It iden-tified a cluster of moderately risk-prone populations and raised the alarm for one population. Each indicator was individually associated with distinct environmental stressors relevant for brown trout requirements. The multifaceted health index highlighted surrounding agricultural land and oxygen concentration as the most impacting environmental factors for the general health and sustainability of brown trout populations. The implementation of such integrative index can be transferred to a wide range of species and contexts. This index therefore provides to environmental managers and conservationists a snapshot and easily operated tool to identify risk-prone populations and areas to restore or conserve.