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While considerable evidence exists of biogeographic patterns in the intensity of species interactions, the influence of these patterns on variation in community structure is less clear. Studying how the distributions of traits in communities vary along global gradients can inform how variation in interactions and other factors contribute to the process of community assembly. Using a model selection approach on measures of trait dispersion in crustaceans associated with eelgrass ( Zostera marina ) spanning 30° of latitude in two oceans, we found that dispersion strongly increased with increasing predation and decreasing latitude. Ocean and epiphyte load appeared as secondary predictors; Pacific communities were more overdispersed while Atlantic communities were more clustered, and increasing epiphytes were associated with increased clustering. By examining how species interactions and environmental filters influence community structure across biogeographic regions, we demonstrate how both latitudinal variation in species interactions and historical contingency shape these responses. Community trait distributions have implications for ecosystem stability and functioning, and integrating large-scale observations of environmental filters, species interactions and traits can help us predict how communities may respond to environmental change.
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Quantitative Biogeography: Large-Scale, Long-Term Change in the Rocky Intertidal Region of the California Current Large Marine Ecosystem
Biogeographical research has long sought to document current and past species’ distributions through descriptive studies, but in recent decades this field has evolved to (1) capture local to coast-wide quantitative estimates of species’ abundances, (2) link physical processes with species’ distributions, and (3) determine how climate change disrupts biogeographic patterns. However, assessing change requires quantitatively robust data that are both geographically and temporally broad. Historically, such studies were rare, largely due to funding constraints. Here, we present a model for sustaining long-term, quantitative biogeography surveys using a collaborative approach. We also share some key contributions resulting from this model, including (1) a robust understanding of biogeographic patterns and the temporal dynamic of those patterns, (2) more comprehensive assessment of impacts at various scales (e.g., oil spill, coast-wide disease event), and (3) more informed management decisions (e.g., marine protected area design and evaluation).
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- Award ID(s):
- 1737372
- PAR ID:
- 10127266
- Date Published:
- Journal Name:
- Oceanography
- Volume:
- 32
- Issue:
- 3
- ISSN:
- 1042-8275
- Page Range / eLocation ID:
- 26-37
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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