2022 ESA Annual Meeting (August 14 - 19)

COS 66-5 Stay away from the light: Localized light pollution affects entire moth metacommunities

11:00 AM-11:15 AM
513F
Gabriel Khattar, Concordia University;Pedro Peres-Neto,Concordia University;
Background/Question/Methods

The keystone community concept (KCC) posits that communities contribute unevenly to the diversity and connectivity of metacommunities. The KCC implies that the importance of any single community to regional dynamics is greater than its local diversity. This insight is particularly relevant when local diversity is not positively associated with habitat quality, e.g., when anthropogenic stressors attract and trap individuals into localities where fitness is decreased. In this scenario, identifying and protecting keystone communities whose influence on metacommunity structure is disproportionately larger relative to their diversity is paramount to conservation and management. To illustrate that, we proposed a framework that relies on network connectivity metrics and null models to infer the importance of communities to the spatial-temporal structure (i.e., connectivity) of a moth metacommunity. This metacommunity was sampled for six years in the Mt. Halassan National Park (South Korea), a protected mountainous landscape that is surrounded by urban settlements and, consequently, is under direct and indirect (artificial skyglow) influence of light pollution. Given that moths are positively phototactic, we predict that light pollution should be positively correlated with local diversity but negatively correlated with community keystoneness.

Results/Conclusions

By mapping the degree of community keystoneness in space and time, we observed that the internal structure of metacommunities is temporally dynamic, i.e., the relevance of local communities to the maintenance of metacommunity structure fluctuates over time. However, the degree of keystoneness of high-elevation communities was consistently higher than low-elevation communities. The influence of light pollution, climate, and spatial variables on these patterns was inferred by a combination of machine learning algorithms and best-fitting subset models. Our models strongly supported our predictions by showing that: (i) light pollution is positively associated with local diversity but negatively correlated with the keystoneness degree of moth communities; (ii) light pollution is a critical predictor of local diversity and community keystoneness. These results suggest that the effects of light pollution are not limited to local communities under direct impact. It can impact entire metacommunities, including local communities within protected areas. Our study also illustrates how the keystone community concept can advance our understanding of local impacts that have regional consequences on the conservation and management of biodiversity.