• Energy Research

AbstractSpecies inventories are crucial for conservation but are difficult to assemble and maintain. Bioblitzes, which encourage the public to document biodiversity in a particular area and timeframe, may offer useful information, but their integration with other datasets poses challenges. We investigated the potential contribution of bioblitzes to natural resource management using observations from the United States National Park Service (NPS) 2016 Centennial Bioblitz. Through automated cross‐referencing over 19,000 iNaturalist “research‐grade” observations from 107 national parks with existing park inventory lists, we matched 86% of species documented in the Bioblitz to NPS species lists based on current taxonomy and matched another 6% of species using alternative scientific names through our matching process in R. Of the remaining 13.5% that did not match the NPS species lists, 84% of the unmatched species were manually found within the lists or were outside the boundaries of the park, identifying 141 native species that were unrecorded in NPS species lists. Many introduced species were recorded more often in parks closer to cities. Parks near cities also drew more participants. Our study shows how public participation through iNaturalist and bioblitzes can facilitate biodiversity monitoring across large spatial scales.

Climate change and invasive species pose novel and combined challenges to ecosystem management and ecological restoration. Managers and decision-makers can address these challenges via climate-smart invasive species management, defined as any management strategy or action that considers and aims to reduce the interactive effects of climate change and invasions. To facilitate this approach in the Northeastern U.S. and Canada, members of the Northeast Regional Invasive Species & Climate Change Management Network (NE RISCC) have created a set of guidelines for how to consider and incorporate the interactive effects of climate change and invasions at multiple stages of management based on feedback from managers via surveys, formal research interviews, informal conversations, a workshop at the 2023 New York Invasive Species Expo, and an online workshop in April 2024. The focus of these guidelines is on the areas served by the NE RISCC, but can also serve as a starting point for climate-smart invasive species management efforts in other regions. ; U.S. Geological Survey, Northeast Climate Adaptation Science Center (NE CASC) through Grant No. G21AC10648-02

AbstractNatural ecosystems store large amounts of carbon globally, as organisms absorb carbon from the atmosphere to build large, long-lasting, or slow-decaying structures such as tree bark or root systems. An ecosystem’s carbon sequestration potential is tightly linked to its biological diversity. Yet when considering future projections, many carbon sequestration models fail to account for the role biodiversity plays in carbon storage. Here, we assess the consequences of plant biodiversity loss for carbon storage under multiple climate and land-use change scenarios. We link a macroecological model projecting changes in vascular plant richness under different scenarios with empirical data on relationships between biodiversity and biomass. We find that biodiversity declines from climate and land use change could lead to a global loss of between7.44-103.14PgC (global sustainability scenario) and10.87-145.95PgC (fossil-fueled development scenario). This indicates a self-reinforcing feedback loop, where higher levels of climate change lead to greater biodiversity loss, which in turn leads to greater carbon emissions and ultimately more climate change. Conversely, biodiversity conservation and restoration can help achieve climate change mitigation goals.

AbstractAimPhenological mismatches, when life‐events become mistimed with optimal environmental conditions, have become increasingly common under climate change. Population‐level susceptibility to mismatches depends on how phenology and phenotypic plasticity vary across a species’ distributional range. Here, we quantify the environmental drivers of colour moult phenology, phenotypic plasticity, and the extent of phenological mismatch in seasonal camouflage to assess vulnerability to mismatch in a common North American mammal.LocationNorth America.Time period2010–2017.Major taxa studiedSnowshoe hare (Lepus americanus).MethodsWe used > 5,500 by‐catch photographs of snowshoe hares from 448 remote camera trap sites at three independent study areas. To quantify moult phenology and phenotypic plasticity, we used multinomial logistic regression models that incorporated geospatial and high‐resolution climate data. We estimated occurrence of camouflage mismatch between hares’ coat colour and the presence and absence of snow over 7 years of monitoring.ResultsSpatial and temporal variation in moult phenology depended on local climate conditions more so than on latitude. First, hares in colder, snowier areas moulted earlier in the fall and later in the spring. Next, hares exhibited phenotypic plasticity in moult phenology in response to annual variation in temperature and snow duration, especially in the spring. Finally, the occurrence of camouflage mismatch varied in space and time; white hares on dark, snowless background occurred primarily during low‐snow years in regions characterized by shallow, short‐lasting snowpack.Main conclusionsLong‐term climate and annual variation in snow and temperature determine coat colour moult phenology in snowshoe hares. In most areas, climate change leads to shorter snow seasons, but the occurrence of camouflage mismatch varies across the species’ range. Our results underscore the population‐specific susceptibility to climate change‐induced stressors and the necessity to understand this variation to prioritize the populations most vulnerable under global environmental change.

Populations along geographical range limits are often exposed to unsuitable climate and low resource availability relative to core populations. As such, there has been a renewed focus on understanding the factors that determine range limits to better predict how species will respond to global change. Using recent theory on range limits and classical understanding of density dependence, we evaluated the influence of resource availability on the snowshoe hareLepus americanusalong its trailing range edge. We estimated variation in population density, habitat use, survival, and parasite loads to test the Great Escape Hypothesis (GEH), i.e. that density dependence determines, in part, a species' persistence along trailing edges. We found that variability in resource availability affected density and population fluctuations and led to trade‐offs in survival for snowshoe hare populations in the northeastern USA. Hares living in resource‐limited environments had lower and less variable population density, yet higher survival and lower parasitism compared to populations living in resource‐rich environments. We suggest that density‐dependent dynamics, elicited by resource availability, provide hares a unique survival advantage and partly explain persistence along their trailing edge. We hypothesize that this low‐density escape from predation and parasitism occurs for other prey species along trailing edges, but the extent to which it occurs is likely conditional on the quality of matrix habitat. Our work indicates that biotic factors play an important role in shaping species' trailing edges and more detailed examination of non‐climatic factors is warranted to better inform conservation and management decisions.

Refugia have long been studied from paleontological and biogeographical perspectives to understand how populations persisted during past periods of unfavorable climate. Recently, researchers have applied the idea to contemporary landscapes to identify climate change refugia, here defined as areas relatively buffered from contemporary climate change over time that enable persistence of valued physical, ecological, and socio-cultural resources. We differentiate historical and contemporary views, and characterize physical and ecological processes that create and maintain climate change refugia. We then delineate how refugia can fit into existing decision support frameworks for climate adaptation and describe seven steps for managing them. Finally, we identify challenges and opportunities for operationalizing the concept of climate change refugia. Managing climate change refugia can be an important option for conservation in the face of ongoing climate change.

A massive expansion of renewable energy (RE) is underway to meet the world's climate goals. Although RE serves to reduce threats from climate change, it can also pose threats to species whose current and future ranges intersect with RE installations. Here, we propose a "Climate-Smart Siting" framework for addressing potential conflicts between RE expansion and biodiversity conservation. The framework engenders authentic consultation with affected and disadvantaged communities throughout and uses overlay and optimization routines to identify focal areas now and in the future where RE development poses promise and peril as species' ranges shift in response to climate change. We use this framework to demonstrate methods, identify decision outcomes, and discuss market-based levers for aligning RE expansion with the United Nations Global Biodiversity Framework now and as climate change progresses. In the face of the climate crisis, a Climate-Smart Siting strategy could help create solutions without causing further harm to biodiversity and human communities..

Aim: Identifying the mechanisms influencing species' distributions is critical for accurate climate change forecasts. However, current approaches are limited by correlative models that cannot distinguish between direct and indirect effects. Location: New Hampshire and Vermont, USA. Methods: Using causal and correlational models and new theory on range limits, we compared current (2014–2019) and future (2080s) distributions of ecologically important mammalian carnivores and competitors along range limits in the northeastern US under two global climate models (GCMs) and a high-emissions scenario (RCP8.5) of projected snow and forest biomass change. Results: Our hypothesis that causal models of climate-mediated competition would result in different distribution predictions than correlational models, both in the current and future periods, was well-supported by our results; however, these patterns were prominent only for species pairs that exhibited strong interactions. The causal model predicted the current distribution of Canada lynx (Lynx canadensis) more accurately, likely because it incorporated the influence of competitive interactions mediated by snow with the closely related bobcat (Lynx rufus). Both modeling frameworks predicted an overall decline in lynx occurrence in the central high elevation regions and increased occurrence in the northeastern region in the 2080s due to changes in land use that provided optimal habitat. However, these losses and gains were less substantial in the causal model due to the inclusion of an indirect buffering effect of snow on lynx. Main conclusions: Our comparative analysis indicates that a causal framework, steeped in ecological theory, can be used to generate spatially-explicit predictions of species distributions. This approach can be used to disentangle correlated predictors that have previously hampered understanding of range limits and species' response to climate change. We used data from 257 camera-trap sites spaced in non-overlapping grids based on the home range size of the smallest carnivore species (Martes americana = 2x2 km). Each site included a remote camera positioned facing north on a tree, 1–2 m above the snow surface, and pointed at a slight downward angle towards a stake positioned 3–5 m from the camera. Commercial skunk lure and turkey feathers were used as attractants and placed directly on the snow stakes. Cameras were set to take 1–3 consecutive pictures every 1–10 sec when triggered, depending on the brand and model, and checked on average 3 (range = 1–9) times each season to download data, refresh attractants, and to ensure cameras were working properly. We used camera data from autumn to spring (16 October–15 May) for each year (2014–2019). This seasonal range was chosen as it approximates demographic (i.e., births and deaths) and geographic closure (i.e., dispersal) and is based on species' ecological responses to snowpack and leaf phenology of the region. We identified species in photographs by their unique morphology and field marks and used consensus from multiple observers when identification was uncertain. We organized camera data into weekly occasions using CPW Photo Warehouse and recorded whether or not each species was detected during the occasion. The data (sem_dat.csv) contains best unbiased predictors of occurrence (BUPs) for each species at each site and year. The locations of the sites were not included as Canada lynx (Lynx canadensis) and American marten (Martes americana) are federally-threatened and state-endangered species, respectively, in our study region. BUPs for each species are listed by their common name and exogenous variables include unscaled values (depth, biomass) and scaled values (depth_s, biomass_s), the latter of which were used in the SEM. The siteID column is the site specific id of the each camera site and was specified as a random effect in each generalized linear mixed effects model (GLMM) in the SEM. The associated R code (DDI-2020-0432R2) can be used to peform the SEM using the data.