Compared to non‐urban environments, cities host ecological communities with altered taxonomic diversity and functional trait composition. However, we know little about how these urban changes take shape over time. Using historical bee (Apoidea: Anthophila) museum specimens supplemented with online repositories and researcher collections, we investigated whether bee species richness tracked urban and human population growth over the past 118 years. We also determined which species were no longer collected, whether those species shared certain traits, and if collector behavior changed over time. We focused on Wake County, North Carolina, United States where human population size has increased over 16 times over the last century along with the urban area within its largest city, Raleigh, which has increased over four times. We estimated bee species richness with occupancy models, and rarefaction and extrapolation curves to account for imperfect detection and sample coverage. To determine if bee traits correlated with when species were collected, we compiled information on native status, nesting habits, diet breadth, and sociality. We used non‐metric multidimensional scaling to determine if individual collectors contributed different bee assemblages over time. In total, there were 328 species collected in Wake County. We found that although bee species richness varied, there was no clear trend in bee species richness over time. However, recent collections (since 2003) were missing 195 species, and there was a shift in trait composition, particularly lost species were below‐ground nesters. The top collectors in the dataset differed in how often they collected bee species, but this was not consistent between historic and contemporary time periods; some contemporary collectors grouped closer together than others, potentially due to focusing on urban habitats. Use of historical collections and complimentary analyses can fill knowledge gaps to help understand temporal patterns of species richness in taxonomic groups that may not have planned long‐term data.
Correlative species distribution models are widely used to quantify past shifts in ranges or communities, and to predict future outcomes under ongoing global change. Practitioners confront a wide range of potentially plausible models for ecological dynamics, but most specific applications only consider a narrow set. Here, we clarify that certain model structures can embed restrictive assumptions about key sources of forecast uncertainty into an analysis. To evaluate forecast uncertainties and our ability to explain community change, we fit and compared 39 candidate multi‐ or joint species occupancy models to avian incidence data collected at 320 sites across California during the early 20th century and resurveyed a century later. We found massive (>20,000 LOOIC) differences in within‐time information criterion across models. Poorer fitting models omitting multivariate random effects predicted less variation in species richness changes and smaller contemporary communities, with considerable variation in predicted spatial patterns in richness changes across models. The top models suggested avian environmental associations changed across time, contemporary avian occupancy was influenced by previous site‐specific occupancy states, and that both latent site variables and species associations with these variables also varied over time. Collectively, our results recapitulate that simplified model assumptions not only impact predictive fit but may mask important sources of forecast uncertainty and mischaracterize the current state of system understanding when seeking to describe or project community responses to global change. We recommend that researchers seeking to make long‐term forecasts prioritize characterizing forecast uncertainty over seeking to present a single best guess. To do so reliably, we urge practitioners to employ models capable of characterizing the key sources of forecast uncertainty, where predictors, parameters and random effects may vary over time or further interact with previous occurrence states.
more » « less- NSF-PAR ID:
- 10476314
- Publisher / Repository:
- Wiley-Blackwell
- Date Published:
- Journal Name:
- Global Change Biology
- Volume:
- 30
- Issue:
- 1
- ISSN:
- 1354-1013
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Coffee agroforests had the highest species richness and lowest dominance when compared to areca and rubber. Beta diversity was highest in areca for within agroforest measures. Compared across agroforests, coffee had highest beta diversity with areca and rubber. Both elevation and latitude showed an overall positive association with amphibian occupancy, although species‐specific responses varied considerably.
Microhabitat availability was one of the strongest predictors of amphibian occupancy, with mean community response being positive with presence of water bodies and roads. Pond presence increased species richness per site by 34.7% (species‐specific responses in occupancy ranged from –2.7% to 327%). Stream presence alone did not change species richness but species‐specific response ranged from –59% to 273%. Presence of plantation roads also increased species richness by 21.5% (species‐specific response ranged from –82% to 656%). Being unpaved with little vehicular traffic, plantation roads seem to provide additional habitats for amphibians. Presence of all three microhabitats at a site increased species richness by 75%.
Our study highlights the importance of land management strategies that maintain diverse native canopy and freshwater bodies and other microhabitats in sustaining amphibian fauna. Market‐driven land‐use change from coffee to other agroforest types will have detrimental effects on amphibian communities and their long‐term sustainability in the Western Ghats.
