Desert bee and rodent assemblages track climate variability

Melanie R. Kazenel, Pablo A. Cárdenas, Karen W. Wright, Kenneth D. Whitney and Jennifer A. Rudgers, Department of Biology, University of New Mexico, Albuquerque, NM, Melanie R. Kazenel, Pablo A. Cárdenas, Karen W. Wright, Kenneth D. Whitney and Jennifer A. Rudgers, Sevilleta Long Term Ecological Research Program, Albuquerque, NM, Karen W. Wright, Department of Entomology, Texas A&M University, College Station, TX, David C. Lightfoot, Museum of Southwestern Biology, University of New Mexico, Albuquerque, NM, Terry L. Griswold, Pollinating Insects Research Unit, USDA-ARS, Logan, UT, Erica Christensen, Jornada Experimental Range, New Mexico State University, Las Cruces, NM, S.K. Morgan Ernest, Department of Wildlife Ecology and Conservation, University of Florida, Gainesville, FL, Robert L. Schooley, Department of Natural Resources and Environmental Sciences, University of Illinois, Urbana, IL, Paul Stapp, Department of Biological Science, California State University, Fullerton, CA

Background/Question/Methods
Long-term monitoring can enhance the detection of biodiversity declines associated with climate change, improving future projections by reducing reliance on space-for-time substitution, increasing scalability, and expanding resolution to both non-stationary aspects of change: climate mean and variability. In drylands, which face increasingly arid and more variable conditions, bees and rodents are important pollinators and consumers; declines in these groups could have cascading ecological effects. We analyzed long-term bee and rodent abundance data from representative ecosystems in the southwestern USA to examine how species and assemblages tracked climate variability. For bees, we modeled relationships between species abundance and aridity (2002–2015) and projected future population trajectories. We also experimentally measured bees’ thermal and desiccation tolerances to test whether they predicted abundance dynamics. For rodents, we characterized species as either losers or winners under drought and climate variability by considering two time series (1995–2006, 2004–2013) that coincided with wet and dry phases of the Pacific Decadal Oscillation (PDO), which influences regional aridity.
Results/Conclusions
From 2002–2015, 10% of bee species increased in abundance, and 6% decreased, while community size and diversity remained stable. Aridity strongly predicted maximum yearly bee abundance for 95% of bee populations, with nonlinear relationships signaling sensitivity to both mean and variance of aridity. Bee species that tolerated both heat and drought in physiological experiments increased the most over time. Models using future climate projections predicted decreases in bee diversity but no change in abundance during the next 80 years. In contrast, rodent diversity declined regionally by 20-35%, with greater losses during 2004–2013 (dry PDO). Abundance declined regionally only during 2004–2013, with losses of ~5%. Dynamics in rodent diversity and abundance differed spatially among ecosystems, which modulated which species were winners or losers under aridity and amplified climate variability. Winners and losers differed among ecosystems for 70% of rodent taxa, and fewer taxa were winners (18%) than losers (30%) under aridity. During 1995–2006 (wet PDO) plant productivity outranked climate variables as the best regional predictor of abundance for 70% of rodents, whereas during 2004–2013, climate best explained abundance for 60% of taxa. Our results suggest that bee and rodent sensitivities to climate mean and variance influenced population and community temporal dynamics. Our work highlights the value of considering both climate mean and variability to better predict ecological responses to climate change.