An official website of the United States government
Climate change is a well‐documented driver and threat multiplier of infectious disease in wildlife populations. However, wildlife disease management and climate‐change adaptation have largely operated in isolation. To improve conservation outcomes, we consider the role of climate adaptation in initiating or exacerbating the transmission and spread of wildlife disease and the deleterious effects thereof, as illustrated through several case studies. We offer insights into best practices for disease‐smart adaptation, including a checklist of key factors for assessing disease risks early in the climate adaptation process. By assessing risk, incorporating uncertainty, planning for change, and monitoring outcomes, natural resource managers and conservation practitioners can better prepare for and respond to wildlife disease threats in a changing climate.
more »
« less
Some Forms of Uncertainty May Suppress the Evolution of Social Learning
Successful climate change adaptation depends on the spread and maintenance of adaptive behav- iors. Current theory suggests that the heterogeneity of metapopulation structure can help adaptations diffuse throughout a population. In this paper, we develop an agent-based model of the spread of adaptations in populations with minority-majority metapopulation structure, where subpopulations learn more or less frequently from their own group compared to the other group. In our simulations, minority-majority-structured populations with moderate degrees of in-group preference better spread and maintained an adaptation compared to populations with more equal-sized groups and weak homophily. Minority groups act as incubators for an adaptation, while majority groups act as reservoirs for an adaptation once it has spread widely. This means that adaptations diffuse throughout popula- tions better when minority groups start out knowing an adaptation, as Indigenous populations often do, while cohesion among majority groups further promotes adaptation diffusion. Our work advances the goal of this theme issue by developing new theoretical insights and demonstrating the utility of cultural evolutionary theory and methods as important tools in the nascent science of culture that climate change adaptation needs.
more »
« less
- Award ID(s):
- 2028160
- PAR ID:
- 10451827
- Editor(s):
- Culbertson, J.; Perfors, A.; Rabagliati, H.; Ramenzoni, V.
- Date Published:
- Journal Name:
- Proceedings of the 44th Annual Conference of the Cognitive Science Society
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Epidemic models study the spread of undesired agents through populations, be it infectious diseases through a country, misinformation in social media or pests infesting a region. In combating these epidemics, we rely neither on global top-down interventions, nor solely on individual adaptations. Instead, interventions commonly come from local institutions such as public health departments, moderation teams on social media platforms or other forms of group governance. Classic models, which are often individual or agent-based, are ill-suited to capture local adaptations. We leverage developments of institutional dynamics based on cultural group selection to study how groups attempt local control of an epidemic by taking inspiration from the successes and failures of other groups. Incorporating institutional changes into epidemic dynamics reveals paradoxes: a higher transmission rate can result in smaller outbreaks as does decreasing the speed of institutional adaptation. When groups perceive a contagion as more worrisome, they can invest in improved policies and, if they maintain these policies long enough to have impact, lead to a reduction in endemicity. By looking at the interplay between the speed of institutions and the transmission rate of the contagions, we find rich coevolutionary dynamics that reflect the complexity of known biological and social contagions.more » « less
-
Abstract Human‐modified habitats rarely yield outcomes that are aligned with conservation ideals. Landscapes that are subdivided by roads are no exception, precipitating negative impacts on populations due to fragmentation, pollution, and road kill. Although many populations in human‐modified habitats show evidence for local adaptation, rarely does environmental change yield outright benefits for populations of conservation interest. Contrary to expectations, we report surprising benefits experienced by amphibian populations breeding and dwelling in proximity to roads. We show that roadside populations of the wood frog, Rana sylvatica, exhibit better locomotor performance and higher measures of traits related to fitness compared with frogs from less disturbed environments located further away from roads. These results contrast previous evidence for maladaptation in roadside populations of wood frogs studied elsewhere. Our results indicate that altered habitats might not be unequivocally detrimental and at times might contribute to metapopulation success. While the frequency of such beneficial outcomes remains unknown, their occurrence underscores the complexity of inferring consequences of environmental change.more » « less
-
Infectious diseases have detrimental impacts across wildlife taxa. Despite this, we often lack information on the complex spatial and contact structures of host populations, reducing our ability to understand disease spread and our preparedness for epidemic response. This is also prevalent in the marine environment, where rapid habitat changes due to anthropogenic disturbances and human-induced climate change are heightening the vulnerability of marine species to disease. Recognizing these risks, we leveraged a collated dataset to establish a data-driven epidemiological metapopulation model for Tamanend’s bottlenose dolphins (Tursiops erebennus), whose populations are periodically impacted by deadly respiratory disease. We found their spatial distribution and contact is heterogeneous throughout their habitat and by ecotype, which explains differences in past infection burdens. With our metapopulation approach, we demonstrate spatial hotspots for epidemic risk during migratory seasons and that populations in some central estuaries would be the most effective sentinels for disease surveillance. These mathematical models provide a generalizable, non-invasive tool that takes advantage of routinely collected wildlife data to mechanistically understand disease transmission and inform disease surveillance tactics. Our findings highlight the heterogeneities that play a crucial role in shaping the impacts of infectious diseases, and how a data-driven understanding of these mechanisms enhances epidemic preparedness.more » « less
-
Long-term snowpack decline is among the best-understood impacts of climate change on water resources systems. This trend has been observed for decades and is projected to continue even in climate projections in which total runoff volumes do not change significantly. For basins in which snowpack has historically provided intra-annual water storage, snowpack decline creates several issues that may require adaptation to infrastructure, operations, or both. This study develops an approach to analyze vulnerabilities and adaptations specifically focused on the challenge of snowpack decline, using the northern California reservoir system as a case study. We first introduce an open-source daily time-step simulation model of this system, which is validated against historical observations of operations. Multiobjective vulnerabilities to snowpack decline are then examined using a set of downscaled climate scenarios to capture the physically based effects of rising temperatures. A statistical analysis shows that the primary impacts include water supply shortage and lower reservoir storage resulting from the seasonal shift in runoff timing. These challenges identified from the vulnerability assessment inform proposed adaptations to operations to maintain multiobjective performance across the ensemble of plausible future scenarios, which include other uncertain hydrologic changes. To adapt seasonal reservoir management without the cost of additional infrastructure, we specifically propose and test adaptations that parameterize the structure of existing operating policies: a dynamic flood control rule curve and revised snowpack-to-streamflow forecasting methods to improve seasonal runoff predictability given declining snowpack. These adaptations are shown to mitigate the majority of vulnerabilities caused by snowpack decline across the scenario ensemble, with remaining opportunities for improvement using formal policy search and dynamic adaptation techniques. The coupled approach to vulnerability assessment and adaptation is generalizable to other snowmelt-dominated water resources systems facing the loss of seasonal storage due to rising temperatures.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Conference Paper:
- The DOI is not currently available.
