Multi-season climate projections forecast declines in migratory monarch butterflies.

Climate change poses a unique threat to migratory species as it has the potential to alter environmental conditions at multiple points along a species' migratory route. The eastern migratory population of monarch butterflies (Danaus plexippus) has declined markedly over the last few decades, in part due to variation in breeding-season climate. Here, we combined a retrospective, annual-cycle model for the eastern monarch population with climate projections within the spring breeding grounds in eastern Texas and across the summer breeding grounds in the midwestern U.S. and southern Ontario, Canada to evaluate how monarchs are likely to respond to climate change over the next century. Our results reveal that projected changes in breeding-season climate are likely to lead to decreases in monarch abundance, with high potential for overwintering population size to fall below the historical minimum three or more times in the next two decades. Climatic changes across the expansive summer breeding grounds will also cause shifts in the distribution of monarchs, with higher projected abundances in areas that become wetter but not appreciably hotter (e.g., northern Ohio) and declines in abundance where summer temperatures are projected to increase well above those observed in the recent past (e.g., northern Minnesota). Although climate uncertainties dominate long-term population forecasts, our analyses suggest that we can improve precision of near-term forecasts by collecting targeted data to better understand relationships between breeding-season climate variables and local monarch abundance. Overall, our results highlight the importance of accounting for the impacts of climate changes throughout the full-annual cycle of migratory species.

Accounting for sources of uncertainty when forecasting population responses to climate change.

In Focus: Jaatinen, K., Westerbom, M., Norkko, A., Mustonen, O., & Koons, D. N. (2021). Detrimental impacts of climate change may be exacerbated by density-dependent population regulation in blue mussels. Journal of Animal Ecology, 90, 562-573, https://doi.org/10.1111/1365-2656.13377. Conservation strategies for threatened species are increasingly dependent on forecasts of population responses to climate change. For such forecasts to be accurate, they must account for multiple sources of uncertainty, including those associated with projections of future climate scenarios and those associated with the models used to describe population dynamics. While many population forecasts incorporate parameter uncertainty in abiotic effects and process variance related to unexplained temporal variation, most forecasts overlook the importance of evaluating uncertainty in the structure of the population model itself. By accounting for structural uncertainties in a model of population growth for blue mussels, Jaatinen et al. (2021) demonstrated that density-dependent processes are likely to exacerbate adverse effects of climate change and reduce population viability of this keystone species. These findings highlight the importance of incorporating structural unknowns in population forecasts and the value of approaches that account for multiple sources of climate and model uncertainties. Forecasts that capture a range of possible population trajectories under climate change will help ensure efficient allocation of limited conservation resources.

Drought-mediated extinction of an arid-land amphibian: insights from a spatially explicit dynamic occupancy model.

Understanding how natural and anthropogenic processes affect population dynamics of species with patchy distributions is critical to predicting their responses to environmental changes. Despite considerable evidence that demographic rates and dispersal patterns vary temporally in response to an array of biotic and abiotic processes, few applications of metapopulation theory have sought to explore factors that explain spatiotemporal variation in extinction or colonization rates. To facilitate exploring these factors, we extended a spatially explicit model of metapopulation dynamics to create a framework that requires only binary presence-absence data, makes few assumptions about the dispersal process, and accounts for imperfect detection. We apply this framework to 22 yr of biannual survey data for lowland leopard frogs, Lithobates yavapaiensis, an amphibian that inhabits arid stream systems in the southwestern United States and northern Mexico. Our results highlight the importance of accounting for factors that govern temporal variation in transition probabilities, as both extinction and colonization rates varied with hydrologic conditions. Specifically, local extinctions were more frequent during drought periods, particularly at sites without reliable surface water. Colonization rates increased when larval and dispersal periods were wetter than normal, which increased the probability that potential emigrants metamorphosed and reached neighboring sites. Extirpation of frogs from all sites in one watershed during a period of severe drought demonstrated the influence of site-level features, as frogs persisted only in areas where most sites held water consistently and where the amount of sediment deposited from high-elevation wildfires was low. Application of our model provided novel insights into how climate-related processes affected the distribution and population dynamics of an arid-land amphibian. The approach we describe has application to a wide array of species that inhabit patchy environments, can improve our understanding of factors that govern metapopulation dynamics, and can inform strategies for conservation of imperiled species.

A spatially explicit hierarchical model to characterize population viability.

Many of the processes that govern the viability of animal populations vary spatially, yet population viability analyses (PVAs) that account explicitly for spatial variation are rare. We develop a PVA model that incorporates autocorrelation into the analysis of local demographic information to produce spatially explicit estimates of demography and viability at relatively fine spatial scales across a large spatial extent. We use a hierarchical, spatial, autoregressive model for capture-recapture data from multiple locations to obtain spatially explicit estimates of adult survival (ϕad ), juvenile survival (ϕjuv ), and juvenile-to-adult transition rates (ψ), and a spatial autoregressive model for recruitment data from multiple locations to obtain spatially explicit estimates of recruitment (R). We combine local estimates of demographic rates in stage-structured population models to estimate the rate of population change (λ), then use estimates of λ (and its uncertainty) to forecast changes in local abundance and produce spatially explicit estimates of viability (probability of extirpation, Pex ). We apply the model to demographic data for the Sonoran desert tortoise (Gopherus morafkai) collected across its geographic range in Arizona. There was modest spatial variation in λ^ (0.94-1.03), which reflected spatial variation in ϕ^ad (0.85-0.95), ϕ^juv (0.70-0.89), and ψ^ (0.07-0.13). Recruitment data were too sparse for spatially explicit estimates; therefore, we used a range-wide estimate ( R^  = 0.32 1-yr-old females per female per year). Spatial patterns in demographic rates were complex, but ϕ^ad , ϕ^juv , and λ^ tended to be lower and ψ^ higher in the northwestern portion of the range. Spatial patterns in Pex varied with local abundance. For local abundances >500, Pex was near zero (<0.05) across most of the range after 100 yr; as abundances decreased, however, Pex approached one in the northwestern portion of the range and remained low elsewhere. When local abundances were <50, western and southern populations were vulnerable (Pex  > 0.25). This approach to PVA offers the potential to reveal spatial patterns in demography and viability that can inform conservation and management at multiple spatial scales, provide insight into scale-related investigations in population ecology, and improve basic ecological knowledge of landscape-level phenomena.

Spatial and temporal variation in survival of a rare reptile: a 22-year study of Sonoran desert tortoises.

Although many species may be vulnerable to changes in climate, forecasting species-level responses can be challenging given the array of physiological, behavioral, and demographic attributes that might be affected. One strategy to improve forecasts is to evaluate how species responded to climatic variation in the past. We used 22 years of capture-recapture data for Sonoran desert tortoises (Gopherus morafkai) collected from 15 locations across their geographic range in Arizona to evaluate how environmental factors affected spatial and temporal variation in survival. Although rates of annual survival were generally high ([Formula: see text] = 0.92), survival of adults decreased with drought severity, especially in portions of their range that were most arid and nearest to cities. In three locations where large numbers of carcasses from marked tortoises were recovered, survival of adults was markedly lower during periods of severe drought ([Formula: see text] = 0.77-0.81) compared to all other periods ([Formula: see text] = 0.93-0.98). Assuming continued levels of dependency of humans on fossil fuels, survival of adult tortoises is predicted to decrease by an average of 3 % during 2035-2060 relative to survival during 1987-2008 in 14 of the 15 populations we studied. This decrease could reduce persistence of tortoise populations, especially in arid portions of their range. Temporal and spatial variation in drought conditions are important determinants of survival in adult desert tortoises.

Changes in climate drive recent monarch butterfly dynamics.

Declines in the abundance and diversity of insects pose a substantial threat to terrestrial ecosystems worldwide. Yet, identifying the causes of these declines has proved difficult, even for well-studied species like monarch butterflies, whose eastern North American population has decreased markedly over the last three decades. Three hypotheses have been proposed to explain the changes observed in the eastern monarch population: loss of milkweed host plants from increased herbicide use, mortality during autumn migration and/or early-winter resettlement and changes in breeding-season climate. Here, we use a hierarchical modelling approach, combining data from >18,000 systematic surveys to evaluate support for each of these hypotheses over a 25-yr period. Between 2004 and 2018, breeding-season weather was nearly seven times more important than other factors in explaining variation in summer population size, which was positively associated with the size of the subsequent overwintering population. Although data limitations prevent definitive evaluation of the factors governing population size between 1994 and 2003 (the period of the steepest monarch decline coinciding with a widespread increase in herbicide use), breeding-season weather was similarly identified as an important driver of monarch population size. If observed changes in spring and summer climate continue, portions of the current breeding range may become inhospitable for monarchs. Our results highlight the increasingly important contribution of a changing climate to insect declines.

Academic ecosystems must evolve to support a sustainable postdoc workforce.

The postdoctoral workforce comprises a growing proportion of the science, technology, engineering and mathematics (STEM) community, and plays a vital role in advancing science. Postdoc professional development, however, remains rooted in outdated realities. We propose enhancements to postdoc-centred policies and practices to better align this career stage with contemporary job markets and work life. By facilitating productivity, wellness and career advancement, the proposed changes will benefit all stakeholders in postdoc success-including research teams, institutions, professional societies and the scientific community as a whole. To catalyse reform, we outline recommendations for (1) skills-based training tailored to the current career landscape, and (2) supportive policies and tools outlined in postdoc handbooks. We also invite the ecology and evolution community to lead further progressive reform.

Hydrologic variability governs population dynamics of a vulnerable amphibian in an arid environment.

Dynamics of many amphibian populations are governed by the distribution and availability of water. Therefore, understanding the hydrological mechanisms that explain spatial and temporal variation in occupancy and abundance will improve our ability to conserve and recover populations of vulnerable amphibians. We used 16 years of survey data from intermittent mountain streams in the Sonoran Desert to evaluate how availability of surface water affected survival and adult recruitment of a threatened amphibian, the lowland leopard frog (Lithobates yavapaiensis). Across the entire study period, monthly survival of adults ranged from 0.72 to 0.99 during summer and 0.59 to 0.94 during winter and increased with availability of surface water (Z = 7.66; P < 0.01). Recruitment of frogs into the adult age class occurred primarily during winter and ranged from 1.9 to 3.8 individuals/season/pool; like survival, recruitment increased with availability of surface water (Z = 3.67; P < 0.01). Although abundance of frogs varied across seasons and years, we found no evidence of a systematic trend during the 16-year study period. Given the strong influence of surface water on population dynamics of leopard frogs, conservation of many riparian obligates in this and similar arid regions likely depends critically on minimizing threats to structures and ecosystem processes that maintain surface waters. Understanding the influence of surface-water availability on riparian organisms is particularly important because climate change is likely to decrease precipitation and increase ambient temperatures in desert riparian systems, both of which have the potential to alter fundamentally the hydrology of these systems.