The combination of continuing anthropogenic impact on ecosystems across the globe and the observation of catastrophic shifts in some systems has generated substantial interest in understanding and predicting ecological tipping points. The recent establishment and full operation of NEON has created an opportunity for researchers to access extensive datasets monitoring the composition and functioning of a wide range of ecosystems. These data may be uniquely effective for studying regime shifts and tipping points in ecological systems because of their long time horizon, spatial extent, and most importantly the coordinated monitoring of many biotic and abiotic components of focal ecosystems. The variety of these data can capture a range of potential community shifts while also monitoring an extensive set of environmental drivers. This combination is critical for assessing whether changes are a result of external forcings or internal dynamics. Here, we present an overview of regime shift dynamics; describe a variety of approaches to identify tipping points with data from time series, spatial patterns, or frequency distributions of community states across environmental conditions; and suggest a number of NEON data products that may be appropriate for such analyses.

Biological invasions represent an important and unique case of ecological transformation that can strongly influence species and entire ecosystems. Challenges in managing invasions arise on multiple fronts, ranging from diverse and often divergent values associated with native and introduced species, logistical constraints, and transformation via other change agents (e.g., climate and land-use change). We address biological invasions considering the Resist-Accept-Direct (RAD) framework for addressing ecological transformation. Because RAD is focused on decisions, we address both social and ecological factors that influence preferences for decision alternatives. We address social factors first as these can constrain the range of alternatives considered in an ecological context. Next, we address ecological dynamics by modeling trajectories from RAD alternatives in a two-species scenario involving impacts of introduced brook trout (Salvelinus fontinalis) on native bull trout (S. confluentus). Results reveal that decision alternatives aligned with each of the major components of RAD can produce positive outcomes. In a management context, these findings highlight the value of investing in early engagement to fully identify decision alternatives, formalizing models of system dynamics to understand ecological trajectories, and applying this knowledge to set the stage for longer term efforts to address biological invasions.    

Despite striking global change, management to ensure healthy landscapes and sustained natural resources has tended to set objectives on the basis of the historical range of variability in stationary ecosystems. Many social–ecological systems are moving into novel conditions that can result in ecological transformation. We present four foundations to enable a transition to future-oriented conservation and management that increases capacity to manage change. The foundations are to identify plausible social–ecological trajectories, to apply upstream and deliberate engagement and decision-making with stakeholders, to formulate management pathways to desired futures, and to consider a portfolio approach to manage risk and account for multiple preferences across space and time. We use the Kenai National Wildlife Refuge in Alaska as a case study to illustrate how the four foundations address common land management challenges for navigating transformation and deciding when, where, and how to resist, accept, or direct social–ecological change.  

Aim Anticipating when and where changes in species' demographic rates will lead to range shifts in response to changing climate remains a major challenge. Despite evidence of increasing mortality in dry forests across the globe in response to drought and warming temperatures, the overall impacts on the distribution of dry forests are largely unknown because we lack comparable large-scale data on tree recruitment rates. Here, our aim was to develop range-wide population models for dry forest tree species (pinyon pine and juniper), quantifying both mortality and recruitment, to better understand where and under what conditions species range contractions are occurring. Location Western United States. Major taxa studied Two pinyon pine (Pinus spp.) and three juniper (Juniperus spp.) species. Methods We developed range-wide demographic models for five species using forest inventory data from across the western United States and estimated population trends and climate vulnerability. Results We find that four of the five species are declining in parts of their range, with Pinus edulis having the largest proportion of populations declining (24%). Population vulnerability increases with aridity and temperature, with up to ~50% of populations declining in the warmest and driest conditions. Mortality and recruitment were both essential to explaining where populations are declining. Main conclusions Our results suggest that dry forest species are undergoing an active range shift driven by both changing recruitment and mortality, and that increasing temperatures and drought threaten the long-term viability of many of these species in their current range. While four of the five species examined were experiencing some declines, P. edulis is currently most vulnerable. Management actions such as reducing tree density may be able to mitigate some of these impacts. The framework we present to estimate range-wide demographic rates can be applied to other species to determine where range contractions are most likely.

FY 2022 Projects from the USGS North Central Climate Adaptation Science Center (NC CASC). Contact: casc@usgs.gov

This study investigates optimal grassland easement acquisition strategies with a focus on the roles of environmental benefit additionality and spatial spillover effect of grassland conversion. Numerical analysis shows that the optimal solution under a targeting strategy that does not consider any spatial spillover effect may secure less environmental benefit additionality than does a heuristic algorithm that considers spatial spillover. Moreover, heuristic algorithms that consider either conversion probability or spatial spillover can generally achieve more than 97% of environmental benefit additionality obtained under the optimal solution of a targeting strategy that considers both additionality and spatial spillover.

Macroecology research seeks to understand ecological phenomena with causes and consequences that accumulate, interact, and emerge across scales spanning several orders of magnitude. Broad-extent, fine-grain information (i.e., high spatial resolution data over large areas) is needed to adequately capture these cross-scale phenomena, but these data have historically been costly to acquire and process. Unoccupied aerial systems (UAS or drones carrying a sensor payload) and the National Ecological Observatory Network (NEON) make the broad-extent, fine-grain observational domain more accessible to researchers by lowering costs and reducing the need for highly specialized equipment. Integration of these tools can further democratize macroecological research, as their strengths and weaknesses are complementary. However, using these tools for macroecology can be challenging because mental models are lacking, thus requiring large up-front investments in time, energy, and creativity to become proficient. This challenge inspired a working group of UAS-using academic ecologists, NEON professionals, imaging scientists, remote sensing specialists, and aeronautical engineers at the 2019 NEON Science Summit in Boulder, Colorado, to synthesize current knowledge on how to use UAS with NEON in a mental model for an intended audience of ecologists new to these tools. Specifically, we provide (1) a collection of core principles for collecting high-quality UAS data for NEON integration and (2) a case study illustrating a sample workflow for processing UAS data into meaningful ecological information and integrating it with NEON data collected on the ground—with the Terrestrial Observation System—and remotely—from the Airborne Observation Platform. With this mental model, we advance the democratization of macroecology by making a key observational domain—the broad-extent, fine-grain domain—more accessible via NEON/UAS integration.

State fish and wildlife agencies are required to submit a State Wildlife Action Plan (SWAP) every 10 years to be eligible for grants through the State Wildlife Grant Program. With the next round of revisions due in 2025, the U.S. Geological Survey North Central Climate Adaptation Science Center is evaluating how to best support states with further integrating climate-informed planning in their SWAPs. Here, we summarize how states in the North Central region, which includes Colorado, Kansas, Montana, Nebraska, North Dakota, South Dakota, and Wyoming, addressed adaptation planning in their 2015 SWAPs. We review climate adaptation considerations in required SWAP elements one through five, including species, habitats, threats, conservation actions, and conservation monitoring, respectively. We also include a list of potential strategies that the North Central Climate Adaptation Science Center could use to support states in the North Central region with further advancing the integration of climate-informed planning in ongoing and future SWAP revisions. These strategies were primarily identified during meetings in 2021 with six of seven state fish and wildlife agencies in the North Central region where we discussed their priority needs relating to climate-informed planning. Our hope is that these strategies will enhance existing efforts in the region to advance the integration of climate change in conservation planning.

State fish and wildlife agencies are required to submit a State Wildlife Action Plan (SWAP) every 10 years to be eligible for grants through the State Wildlife Grant Program. With the next round of revisions due in 2025, the U.S. Geological Survey North Central Climate Adaptation Science Center is evaluating how to best support states with further integrating climate-informed planning in their SWAPs. Here, we summarize how states in the North Central region, which includes Colorado, Kansas, Montana, Nebraska, North Dakota, South Dakota, and Wyoming, addressed adaptation planning in their 2015 SWAPs. We review climate adaptation considerations in required SWAP elements one through five, including species, habitats, threats, conservation actions, and conservation monitoring, respectively. We also include a list of potential strategies that the North Central Climate Adaptation Science Center could use to support states in the North Central region with further advancing the integration of climate-informed planning in ongoing and future SWAP revisions. These strategies were primarily identified during meetings in 2021 with six of seven state fish and wildlife agencies in the North Central region where we discussed their priority needs relating to climate-informed planning. Our hope is that these strategies will enhance existing efforts in the region to advance the integration of climate change in conservation planning.