Conservation and management efforts require the monitoring of trends in the abundance of individuals over time. However, numerous species are encountered so rarely during routine sampling that it is difficult to disentangle population trends from spurious patterns caused by sampling effects. Possible alternatives that have been suggested include increasing sampling effort, distributing sampling effort over longer time intervals, and/or accepting lower levels of statistical power for detecting population declines. Herein we propose a novel approach to dealing with this problem, scrutinizing abundance trends at the community level. The approach is based on the assumption that patterns at the community level are more stable than those at the species level, reducing the effects of sampling. We tested this approach using a series of simulations designed to mimic changes in a diverse marine community as a result of fisheries bycatch. Parameters that we varied included the number of species in decline, the rate of decline, and the initial abundance of those species that are in decline. We used changes in the species abundance distribution of the community as a response variable, contrasting the results of our approach with a single-species monitoring approach. Results/Conclusions
Preliminary results suggest that the community-level approach is better at detecting species declines, particularly when numerous species are in decline but the rate of decline is slow and the initial abundances of those species in decline are low. The implications for monitoring are significant: If we are concerned about general processes that affect multiple species (e.g., habitat fragmentation, pollution, fisheries bycatch), adopting a community-level approach to monitoring may improve our ability to detect threats and mitigate them sooner.
