Glimmers of hope in large carnivore recoveries.

In the face of an accelerating extinction crisis, scientists must draw insights from successful conservation interventions to uncover promising strategies for reversing broader declines. Here, we synthesize cases of recovery from a list of 362 species of large carnivores, ecologically important species that function as terminal consumers in many ecological contexts. Large carnivores represent critical conservation targets that have experienced historical declines as a result of direct exploitation and habitat loss. We examine taxonomic and geographic variation in current extinction risk and recovery indices, identify conservation actions associated with positive outcomes, and reveal anthropogenic threats linked to ongoing declines. We find that fewer than 10% of global large carnivore populations are increasing, and only 12 species (3.3%) have experienced genuine improvement in extinction risk, mostly limited to recoveries among marine mammals. Recovery is associated with species legislation enacted at national and international levels, and with management of direct exploitation. Conversely, ongoing declines are robustly linked to threats that include habitat modification and human conflict. Applying lessons from cases of large carnivore recovery will be crucial for restoring intact ecosystems and maintaining the services they provide to humans.

Strong Evidence for an Intraspecific Metabolic Scaling Coefficient Near 0.89 in Fish.

As an example of applying the evidential approach to statistical inference, we address one of the longest standing controversies in ecology, the evidence for, or against, a universal metabolic scaling relationship between metabolic rate and body mass. Using fish as our study taxa, we curated 25 studies with measurements of standard metabolic rate, temperature, and mass, with 55 independent trials and across 16 fish species and confronted this data with flexible random effects models. To quantify the body mass - metabolic rate relationship, we perform model selection using the Schwarz Information Criteria (ΔSIC), an established evidence function. Further, we formulate and justify the use of ΔSIC intervals to delineate the values of the metabolic scaling relationship that should be retained for further consideration. We found strong evidence for a metabolic scaling coefficient of 0.89 with a ΔSIC interval spanning 0.82 to 0.99, implying that mechanistically derived coefficients of 0.67, 0.75, and 1, are not supported by the data. Model selection supports the use of a random intercepts and random slopes by species, consistent with the idea that other factors, such as taxonomy or ecological or lifestyle characteristics, may be critical for discerning the underlying process giving rise to the data. The evidentialist framework applied here, allows for further refinement given additional data and more complex models.