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Precipitation-dependent source–sink dynamics in a spatially-structured population of an outbreaking caterpillar

Authors :
Marcel Holyoak
Adam Pepi
Richard Karban
Patrick Grof-Tisza
Source :
Landscape Ecology. 34:1131-1143
Publication Year :
2019
Publisher :
Springer Science and Business Media LLC, 2019.

Abstract

Patch-based population models predominately focus on factors that affect regional processes namely, patch size and connectivity, as the primary drivers explaining patch occupancy. This trend persists despite the recognition that patch quality can strongly influence population demography at the local scale. The quality of patches is often temporally variable and influenced by abiotic conditions. However, few studies have explicitly investigated how climatic variables influence the spatial and temporal dynamics of spatially-structured populations either directly or indirectly through changes in patch quality. Using a 10-year census of a spatially-structured population of an outbreaking caterpillar, we determined the relative importance of patch quality (determined demographically), connectivity, precipitation, and their interactive effects on patch abundance, occupancy, colonization, and extinction. We generated a series of statistical models and performed comparisons using Akaike’s information criterion. We subsequently used likelihood ratio tests to determine the influence of each parameter on model fit. Patch quality and precipitation were the strongest predictors of the observed dynamics. We found that the dynamics of the spatially-structured population of Arctia virginalis were strongly influenced by precipitation: all patches had a higher probability of occupancy, contained higher abundances of caterpillars, and experienced fewer extinctions following wet winters compared to years following droughts. These findings suggest that precipitation may act to influence the strength of heterogeneity of patch quality. This work demonstrates that patch-based models that do not include local and climatic factors may produce poor predictions under future climatic regimes.

Details

ISSN :
15729761 and 09212973
Volume :
34
Database :
OpenAIRE
Journal :
Landscape Ecology
Accession number :
edsair.doi...........d8ca979e0dd0b7c83023938315adfd92
Full Text :
https://doi.org/10.1007/s10980-019-00793-z