An official website of the United States government
Summary Anthropogenetic climate change has caused range shifts among many species. Species distribution models (SDMs) are used to predict how species ranges may change in the future. However, most SDMs rarely consider how climate‐sensitive traits, such as phenology, which affect individuals' demography and fitness, may influence species' ranges.Using > 120 000 herbarium specimens representing 360 plant species distributed across the eastern United States, we developed a novel ‘phenology‐informed’ SDM that integrates phenological responses to changing climates. We compared the ranges of each species forecast by the phenology‐informed SDM with those from conventional SDMs. We further validated the modeling approach using hindcasting.When examining the range changes of all species, our phenology‐informed SDMs forecast less species loss and turnover under climate change than conventional SDMs. These results suggest that dynamic phenological responses of species may help them adjust their ecological niches and persist in their habitats as the climate changes.Plant phenology can modulate species' responses to climate change, mitigating its negative effects on species persistence. Further application of our framework will contribute to a generalized understanding of how traits affect species distributions along environmental gradients and facilitate the use of trait‐based SDMs across spatial and taxonomic scales.
more »
« less
Partly cloudy with a chance of mosquitoes: Developing a flexible approach to forecasting mosquito populations
Abstract Climate‐induced shifts in mosquito phenology and population structure have important implications for the health of humans and wildlife. The timing and intensity of mosquito interactions with infected and susceptible hosts are a primary determinant of vector‐borne disease dynamics. Like most ectotherms, rates of mosquito development and corresponding phenological patterns are expected to change under shifting climates. However, developing accurate forecasts of mosquito phenology under climate change that can be used to inform management programs remains challenging despite an abundance of available data. As climate change will have variable effects on mosquito demography and phenology across species it is vital that we identify associated traits that may explain the observed variation. Here, we review a suite of modeling approaches that could be applied to generate forecasts of mosquito activity under climate change and evaluate the strengths and weaknesses of the different approaches. We describe four primary life history and physiological traits that can be used to constrain models and demonstrate how this prior information can be harnessed to develop a more general understanding of how mosquito activity will shift under changing climates. Combining a trait‐based approach with appropriate modeling techniques can allow for the development of actionable, flexible, and multi‐scale forecasts of mosquito population dynamics and phenology for diverse stakeholders.
more »
« less
- Award ID(s):
- 2217817
- PAR ID:
- 10569902
- Publisher / Repository:
- Ecological Society of America
- Date Published:
- Journal Name:
- Ecosphere
- Volume:
- 15
- Issue:
- 12
- ISSN:
- 2150-8925
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Phenology, the timing of recurrent biological events, is a key mechanism by which species adapt or acclimatize to variable environmental conditions, including those influenced by climate change. Measurable traits, including the onset and end of activity, peak activity, and duration, characterize the phenology of life events, and could be significant predictors of trends in population abundance or stability in a changing climate. Bees provide critical pollination services, and understanding the covariates of bee phenological traits can refine predictions on the vulnerabilities of bees and their services to climate change. We paired 16 years of monthly bee survey data (2002-2019) with climate data for 74 bee species in dryland ecosystems of central New Mexico, USA. Contrary to the current paradigm of temperature as the key driver of insect phenology, twice as many bee species had phenological sensitivity to precipitation (39%) than to temperature (20%). Among phenological traits, the end date of active flying periods was most sensitive to climate. Of the 20% of bee species for which precipitation predicted activity end date, 73% ended activity later in wetter years. Fifteen bee species (~20%) had phenological traits sensitive to temperature, but temperature sensitivity was idiosyncratic, and only four species had earlier onset in warmer years, as expected from results in other biomes. Oligolectic (diet specialist) bee species began, peaked, and ended activity later in the year than polylectic (generalist) species, but phenological traits did not correlate with sociality. All phenological traits showed phylogenetic signal, suggesting evolutionary conservatism of phenology among the common bees of central New Mexico drylands. Finally, species with long activity durations were more common, had greater temporal stability in abundance from year to year, and were less likely to decline over time, perhaps because of their longer window for resource acquisition. Our results suggest that drier climates of the future may shift bee phenological activities toward earlier onset, peak, and end dates, that bees with short activity durations may be among the most sensitive to declines in future climates, and that both generalist and social bees may be able to resist or recover from climate change if they have long durations of flight activity.more » « less
-
Abstract Global climate change is predicted to cause range shifts in the mosquito species that transmit pathogens to humans and wildlife. Recent modeling studies have sought to improve our understanding of the relationship between temperature and the transmission potential of mosquito‐borne pathogens. However, the role of the vertebrate host population, including the importance of host behavioral defenses on mosquito feeding success, remains poorly understood despite ample empirical evidence of its significance to pathogen transmission. Here, we derived thermal performance curves for mosquito and parasite traits and integrated them into two models of vector–host contact to investigate how vertebrate host traits and behaviors affect two key thermal properties of mosquito‐borne parasite transmission: the thermal optimum for transmission and the thermal niche of the parasite population. We parameterized these models for five mosquito‐borne parasite transmission systems, leading to two main conclusions. First, vertebrate host availability may induce a shift in the thermal optimum of transmission. When the tolerance of the vertebrate host to biting from mosquitoes is limited, the thermal optimum of transmission may be altered by as much as 5°C, a magnitude of applied significance. Second, thresholds for sustained transmission depend nonlinearly on both vertebrate host availability and temperature. At any temperature, sustained transmission is impossible when vertebrate hosts are extremely abundant because the probability of encountering an infected individual is negligible. But when host biting tolerance is limited, sustained transmission will also not occur at low host population densities. Furthermore, our model indicates that biting tolerance should interact with vertebrate host population density to adjust the parasite population thermal niche. Together, these results suggest that vertebrate host traits and behaviors play essential roles in the thermal properties of mosquito‐borne parasite transmission. Increasing our understanding of this relationship should lead us to improved predictions about shifting global patterns of mosquito‐borne disease.more » « less
-
Climate change increasingly drives local population dynamics, shifts geographic distributions, and threatens persistence. Gene flow and rapid adaptation could rescue declining populations yet are seldom integrated into forecasts. We modeled eco-evolutionary dynamics under preindustrial, contemporary, and projected climates using up to 9 years of fitness data from 102,272 transplants (115 source populations) ofBoechera strictain five common gardens. Climate change endangers locally adapted populations and reduces genotypic variation in long-term population growth rate, suggesting limited adaptive potential. Upslope migration could stabilize high-elevation populations and preserve low-elevation ecotypes, but unassisted gene flow modeled with genomic data is too spatially restricted. Species distribution models failed to capture current dynamics and likely overestimate persistence under intermediate emissions scenarios, highlighting the importance of modeling evolutionary processes.more » « less
-
ABSTRACT Predicting the effects of climate change on plant and animal populations is an urgent challenge for understanding the fate of biodiversity under global change. At the surface, quantifying how climate drives the vital rates that underlie population dynamics appears simple, yet many decisions are required to connect climate to demographic data. Competing approaches have emerged in the literature with little consensus around best practices. Here we provide a practical guide for how to best link vital rates to climate for the purposes of inference and projection of population dynamics. We first describe the sources of demographic and climate data underlying population models. We then focus on best practices to model the relationships between vital rates and climate, highlighting what we can learn from mechanistic and phenomenological models. Finally, we discuss the challenges of prediction and forecasting in the face of uncertainty about climate‐demographic relationships as well as future climate. We conclude by suggesting ways forward to build this field of research into one that makes robust forecasts of population persistence, with opportunities for synthesis across species.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript
- Journal Article:
- https://doi.org/10.1002/ecs2.70074
