Managing biodiversity under climate change: challenges,frameworks, and tools for adaptation

The myriad challenges facing biodiversity under climate change are reflected in the challenges facing managers planning for these impacts. An ever-expanding number of recommendations and tools for climate change adaptation exist to aid managers in these efforts, yet navigating these various resources can lead to information overload and paralysis in decision-making. Here we provide a synthesis of the key considerations, approaches, and available tools for integrating climate change adaptation into management plans. We discuss principal elements in climate change adaptation—incorporating uncertainty through scenario planning and adaptive management—and review three leading frameworks for incorporating climate change adaptation into place-based biodiversity conservation planning. Finally, we identify the following key questions needed for long-term conservation planning and review the associated tools and techniques needed to address them: (1) How is the climate projected to change in my study area?; (2) How are non-climatic stressors projected to change?; (3) How vulnerable are species to climate change impacts?; (4) How are species ranges likely to respond?; and (5) How are management strategies expected to affect outcomes? In doing so, we aim to aid natural resource managers in navigating the burgeoning field of climate change adaptation planning and provide managers a roadmap for managing biodiversity under climate change.     

Phenology research for natural resource management in the United States

Natural resource professionals in the United States recognize that climate-induced changes in phenology can substantially affect resource management. This is reflected in national climate change response plans recently released by major resource agencies. However, managers on-the-ground are often unclear about how to use phenological information to inform their management practices. Until recently, this was at least partially due to the lack of broad-based, standardized phenology data collection across taxa and geographic regions. Such efforts are now underway, albeit in very early stages. Nonetheless, a major hurdle still exists: phenology-linked climate change research has focused more on describing broad ecological changes rather than making direct connections to local to regional management concerns. To help researchers better design relevant research for use in conservation and management decision-making processes, we describe phenology-related research topics that facilitate “actionable” science. Examples include research on evolution and phenotypic plasticity related to vulnerability, the demographic consequences of trophic mismatch, the role of invasive species, and building robust ecological forecast models. Such efforts will increase phenology literacy among on-the-ground resource managers and provide information relevant for short- and long-term decision-making, particularly as related to climate response planning and implementing climate-informed monitoring in the context of adaptive management. In sum, we argue that phenological information is a crucial component of the resource management toolbox that facilitates identification and evaluation of strategies that will reduce the vulnerability of natural systems to climate change. Management-savvy researchers can play an important role in reaching this goal.     

Incorporating climate change into ecosystem service assessments and decisions: a review

Climate change is having a significant impact on ecosystem services and is likely to become increasingly important as this phenomenon intensifies. Future impacts can be difficult to assess as they often involve long timescales, dynamic systems with high uncertainties, and are typically confounded by other drivers of change. Despite a growing literature on climate change impacts on ecosystem services, no quantitative syntheses exist. Hence, we lack an overarching understanding of the impacts of climate change, how they are being assessed, and the extent to which other drivers, uncertainties, and decision making are incorporated. To address this, we systematically reviewed the peer‐reviewed literature that assesses climate change impacts on ecosystem services at subglobal scales. We found that the impact of climate change on most types of services was predominantly negative (59% negative, 24% mixed, 4% neutral, 13% positive), but varied across services, drivers, and assessment methods. Although uncertainty was usually incorporated, there were substantial gaps in the sources of uncertainty included, along with the methods used to incorporate them. We found that relatively few studies integrated decision making, and even fewer studies aimed to identify solutions that were robust to uncertainty. For management or policy to ensure the delivery of ecosystem services, integrated approaches that incorporate multiple drivers of change and account for multiple sources of uncertainty are needed. This is undoubtedly a challenging task, but ignoring these complexities can result in misleading assessments of the impacts of climate change, suboptimal management outcomes, and the inefficient allocation of resources for climate adaptation.     

Monitoring in the Context of Structured Decision-Making and Adaptive Management

Abstract: In a natural resource management setting, monitoring is a crucial component of an informed process for making decisions, and monitoring design should be driven by the decision context and associated uncertainties. Monitoring itself can play ≥3 roles. First, it is important for state-dependent decision-making, as when managers need to know the system state before deciding on the appropriate course of action during the ensuing management cycle. Second, monitoring is critical for evaluating the effectiveness of management actions relative to objectives. Third, in an adaptive management setting, monitoring provides the feedback loop for learning about the system; learning is sought not for its own sake but primarily to better achieve management objectives. In this case, monitoring should be designed to reduce the critical uncertainties in models of the managed system. The United States Geological Survey and United States Fish and Wildlife Service are conducting a large-scale management experiment on 23 National Wildlife Refuges across the Northeast and Midwest Regions. The primary management objective is to provide habitat for migratory waterbirds, particularly during migration, using water-level manipulations in managed wetlands. Key uncertainties are related to the potential trade-offs created by management for a specific waterbird guild (e.g., migratory shorebirds) and the response of waterbirds, plant communities, and invertebrates to specific experimental hydroperiods. We reviewed the monitoring program associated with this study, and the ways that specific observations fill ≥1 of the roles identified above. We used observations from our monitoring to improve state-dependent decisions to control undesired plants, to evaluate management performance relative to shallow-water habitat objectives, and to evaluate potential trade-offs between waterfowl and shorebird habitat management. With limited staff and budgets, management agencies need efficient monitoring programs that are used for decision-making, not comprehensive studies that elucidate all manner of ecological relationships.     

Modelling adaptive management strategies for coping with the impacts of climate variability and change on riverine algal blooms

The impact of climate change on hydrology and water resources is one of the most critical issues facing the world in the next few decades. In particular, there is a need to quantify the risks associated with maintaining the security of resource quantity and quality, and to assess the effectiveness of potential management strategies. In this paper, we assess the impacts of climate variability and change on one aspect of river health. A simple model of Anabaena algal bloom occurrence at a weir pool in the lower Murrumbidgee River, Australia, has been coupled to a catchment model that is used to simulate streamflow, irrigation demand and diversions, dam water storage and releases, and decision-making by both irrigators and managers. Long-term climate data are obtained from a statistical downscaling algorithm, which, when applied to global climate model predictions can provide climate data suitable for driving the coupled model under a variety of climatic scenarios. The coupled model is then used to assess the impact of climate variability and projected climate change on the frequency, duration and magnitude of Anabaena blooms. The impact of two management strategies for bloom control are also assessed and it is shown that even a single, quite simple, resource-neutral, adaptive management strategy has the potential to substantially reduce the occurrence and impact of algal blooms and to more than compensate for the deleterious impacts of climate change. This result supports the notion that planning for the future can lead to positive outcomes in the present.     

Can Boreal and Temperate Forest Management be Adapted to the Uncertainties of 21st Century Climate Change?

Considerable uncertainties remain about magnitude and character, if not general direction of anthropogenic climate change. Global mean temperature could increase by 1.5–4.5°C or more over historic levels, and extreme weather events—drought, storms, and flooding—are likely to increase greatly in frequency. Although ecologists and foresters agree that the practice of forestry will be transformed under climate change, these uncertainties compound the challenge of achieving sustainable, adaptive forest management. In this aritcle, we (i) present a multidisciplinary synthesis of current knowledge of responses of temperate and boreal tree species and forest communities to climate change, and (ii) outline silvicultural strategies for adapting temperate and boreal forests to confront climate change. Our knowledge synthesis proceeds through critical appraisals of efforts to model future tree distributions and responses to climate change, and reviews physiological, phenological, acclimation, and epigenetic responses to climate. As is the case of climate change itself, there are numerous uncertainties about tree species and provenance responses to climate change. For example, acclimation of respiration and epigenetic conditioning of seed embryos has the potential to buffer species against limited warming. Provenances within species also display idiosyncratic responses to altered climates, implying that soemm varieties will be more resilient or resistant to climate change than others. Genetically determined limits to climatic tolerance, and the limits of tree community resistance and resilience (speed of recovery from disturbance) in the face of climate-related disturbances are largely unknown. These unknowns require managers to adopt a portfolio of silvicultural strategies, which may range from minor modifications of current practices to design of novel multi-species stands that may have no historical analogue. Forest managers must be prepared to respond nimbly as they develop, incorporate new insights about climate change and species responses to warming into their practices. Marshalling all strategies and sources of knowledge should enable forest managers to mount (at least) a partially successful response to the challenges of climate change.     

Multi‐model comparison highlights consistency in predicted effect of warming on a semi‐arid shrub

A number of modeling approaches have been developed to predict the impacts of climate change on species distributions, performance, and abundance. The stronger the agreement from models that represent different processes and are based on distinct and independent sources of information, the greater the confidence we can have in their predictions. Evaluating the level of confidence is particularly important when predictions are used to guide conservation or restoration decisions. We used a multi‐model approach to predict climate change impacts on big sagebrush (Artemisia tridentata), the dominant plant species on roughly 43 million hectares in the western United States and a key resource for many endemic wildlife species. To evaluate the climate sensitivity of A. tridentata, we developed four predictive models, two based on empirically derived spatial and temporal relationships, and two that applied mechanistic approaches to simulate sagebrush recruitment and growth. This approach enabled us to produce an aggregate index of climate change vulnerability and uncertainty based on the level of agreement between models. Despite large differences in model structure, predictions of sagebrush response to climate change were largely consistent. Performance, as measured by change in cover, growth, or recruitment, was predicted to decrease at the warmest sites, but increase throughout the cooler portions of sagebrush's range. A sensitivity analysis indicated that sagebrush performance responds more strongly to changes in temperature than precipitation. Most of the uncertainty in model predictions reflected variation among the ecological models, raising questions about the reliability of forecasts based on a single modeling approach. Our results highlight the value of a multi‐model approach in forecasting climate change impacts and uncertainties and should help land managers to maximize the value of conservation investments.     

Assessing uncertainties in land cover projections

Understanding uncertainties in land cover projections is critical to investigating land‐based climate mitigation policies, assessing the potential of climate adaptation strategies and quantifying the impacts of land cover change on the climate system. Here, we identify and quantify uncertainties in global and European land cover projections over a diverse range of model types and scenarios, extending the analysis beyond the agro‐economic models included in previous comparisons. The results from 75 simulations over 18 models are analysed and show a large range in land cover area projections, with the highest variability occurring in future cropland areas. We demonstrate systematic differences in land cover areas associated with the characteristics of the modelling approach, which is at least as great as the differences attributed to the scenario variations. The results lead us to conclude that a higher degree of uncertainty exists in land use projections than currently included in climate or earth system projections. To account for land use uncertainty, it is recommended to use a diverse set of models and approaches when assessing the potential impacts of land cover change on future climate. Additionally, further work is needed to better understand the assumptions driving land use model results and reveal the causes of uncertainty in more depth, to help reduce model uncertainty and improve the projections of land cover.     

Preparing Wildlife for Climate Change: How Far Have We Come?

Global biodiversity is in unprecedented decline and on-the-ground solutions are imperative for conservation. Although there is a large volume of evidence related to climate change effects on wildlife, research on climate adaptation strategies is lagging. To assess the current state of knowledge in climate adaptation, we conducted a comprehensive literature review and evaluated 1,346 peer-reviewed publications for management recommendations designed to address the consequences of climate change on wildlife populations. From 509 publications, we identified 2,306 recommendations and employed both qualitative and quantitative methods for data analysis. Although we found an increase in the volume and diversity of recommendations since 2007, a focus on protected areas (26%, 596 of 2,306 recommendations) and the non-reserve matrix (12%, 276 of 2,306 recommendations) remained prominent in the climate adaptation literature. Common concepts include protected areas, invasive species, ecosystem services, adaptive management, stepping stones, assisted migration, and conservation easements. In contrast, only 1% of recommendations focused on reproduction (n = 26), survival (n = 14), disease (n = 26), or human-wildlife conflict (n = 24). Few recommendations reflected the potential for local-scale management interventions. We demonstrate limited advancement in preparing natural resource managers in climate adaptation at local, management-relevant scales. Additional research is needed to identify and evaluate climate adaptation strategies aimed at reducing the vulnerability of wildlife to contemporary climate change. © 2020 The Wildlife Society.     

Habitat Restoration and Climate Change: Dealing with Climate Variability,Incomplete Data,and Management Decisions with Tree Translocations

Restoration programs need to increasingly address both the restitution of biodiversity and ecosystem services and the preparation of habitats for future climate change. One option to adapt habitats to climate change in the temperate zone is the translocation of southern populations to compensate for climate change effects—an option known as assisted migration (AM). Although AM is widely criticized for endangered species, forest managers are more confident that tree populations can be translocated with success because of previous experiences within native ranges. Here, we contend that translocations of tree populations are also subject to uncertainties, and we extract lessons for future programs of AM within species ranges from a well‐documented failed case of population translocation of Pinus pinaster Ait. in Europe. The failure of these translocations originated from the unawareness of several unpredictable ecological and social events: cryptic maladaptation of the introduced populations, underestimation of climate variability differences between the source and target sites, and complexity in the management schemes, postponing decisions that could have been undertaken earlier. Under the no‐analog conditions that are expected with climate change, management decisions need to be made with incomplete data, implying that a certain degree of maladaptation should always be expected when restoring plant populations from local or external seed sources .     

Decision‐making under climatic uncertainty: A case study involving an Australian Ramsar‐listed wetland

Summary Conservation management in agricultural landscapes involves identification and prioritization of assets, and interventions to reverse or arrest decline. Planning requires synthesis of hydrological, ecological and agronomic information and intuitions. We provide a case study involving the Lake Warden Wetland System, a Ramsar‐listed site on the south coast of Western Australia threatened by salinity and flooding. As the relative merits of management options (including engineering‐based solutions and catchment revegetation) may be sensitive to climate change, we captured our knowledge and understanding of the effectiveness of options under different climate change scenarios using Bayesian belief networks. We insulated against overconfidence by an info‐gap analysis that describes the trade‐off between aspiration and immunity to uncertainty. Only engineering‐based solutions offer reasonable prospects for achieving stated conservation goals in the Lake Warden Wetland System within a 25‐year time horizon. Marginal gains derived from co‐investment in revegetation varied among the assets. We advocate explicit treatment of uncertainty and risk‐based approaches to decision‐making to equip managers with a means of progressing conservation goals. The complementary insights offered by Bayesian belief networks and info‐gap analysis provide a sound basis for managers to assess the extent to which candidate management actions are robust to uncertainty.     

Contribution of crop model structure,parameters and climate projections to uncertainty in climate change impact assessments

Climate change impact assessments are plagued with uncertainties from many sources, such as climate projections or the inadequacies in structure and parameters of the impact model. Previous studies tried to account for the uncertainty from one or two of these. Here, we developed a triple‐ensemble probabilistic assessment using seven crop models, multiple sets of model parameters and eight contrasting climate projections together to comprehensively account for uncertainties from these three important sources. We demonstrated the approach in assessing climate change impact on barley growth and yield at Jokioinen, Finland in the Boreal climatic zone and Lleida, Spain in the Mediterranean climatic zone, for the 2050s. We further quantified and compared the contribution of crop model structure, crop model parameters and climate projections to the total variance of ensemble output using Analysis of Variance (ANOVA). Based on the triple‐ensemble probabilistic assessment, the median of simulated yield change was ?4% and +16%, and the probability of decreasing yield was 63% and 31% in the 2050s, at Jokioinen and Lleida, respectively, relative to 1981–2010. The contribution of crop model structure to the total variance of ensemble output was larger than that from downscaled climate projections and model parameters. The relative contribution of crop model parameters and downscaled climate projections to the total variance of ensemble output varied greatly among the seven crop models and between the two sites. The contribution of downscaled climate projections was on average larger than that of crop model parameters. This information on the uncertainty from different sources can be quite useful for model users to decide where to put the most effort when preparing or choosing models or parameters for impact analyses. We concluded that the triple‐ensemble probabilistic approach that accounts for the uncertainties from multiple important sources provide more comprehensive information for quantifying uncertainties in climate change impact assessments as compared to the conventional approaches that are deterministic or only account for the uncertainties from one or two of the uncertainty sources.     

Adaptive Management and the Value of Information: Learning Via Intervention in Epidemiology

Optimal intervention for disease outbreaks is often impeded by severe scientific uncertainty. Adaptive management (AM), long-used in natural resource management, is a structured decision-making approach to solving dynamic problems that accounts for the value of resolving uncertainty via real-time evaluation of alternative models. We propose an AM approach to design and evaluate intervention strategies in epidemiology, using real-time surveillance to resolve model uncertainty as management proceeds, with foot-and-mouth disease (FMD) culling and measles vaccination as case studies. We use simulations of alternative intervention strategies under competing models to quantify the effect of model uncertainty on decision making, in terms of the value of information, and quantify the benefit of adaptive versus static intervention strategies. Culling decisions during the 2001 UK FMD outbreak were contentious due to uncertainty about the spatial scale of transmission. The expected benefit of resolving this uncertainty prior to a new outbreak on a UK-like landscape would be £45–£60 million relative to the strategy that minimizes livestock losses averaged over alternate transmission models. AM during the outbreak would be expected to recover up to £20.1 million of this expected benefit. AM would also recommend a more conservative initial approach (culling of infected premises and dangerous contact farms) than would a fixed strategy (which would additionally require culling of contiguous premises). For optimal targeting of measles vaccination, based on an outbreak in Malawi in 2010, AM allows better distribution of resources across the affected region; its utility depends on uncertainty about both the at-risk population and logistical capacity. When daily vaccination rates are highly constrained, the optimal initial strategy is to conduct a small, quick campaign; a reduction in expected burden of approximately 10,000 cases could result if campaign targets can be updated on the basis of the true susceptible population. Formal incorporation of a policy to update future management actions in response to information gained in the course of an outbreak can change the optimal initial response and result in significant cost savings. AM provides a framework for using multiple models to facilitate public-health decision making and an objective basis for updating management actions in response to improved scientific understanding.     

Tracking the effect of climate change on ecosystem functioning using protected areas: Africa as a case study

Protected areas represent important core ‘units’ for in situ conservation. However, the current static system is at risk from the effects of global environmental change. This is especially true in Africa, a biodiversity-rich continent expected to be hit hard by climate change. Focusing on African protected areas that experience limited human impact (International Union for Conservation of Nature (IUCN) categories I and II), we tested three hypotheses regarding the impact of climate change on the dynamics of net primary productivity (NPP). We expected a lower annual NPP and higher seasonality in NPP in Eastern and Southern Africa; changes in NPP dynamics to coincide with changes in precipitation; no correlation between changes in NPP dynamics and human development. To test these expectations, we used the Normalised Difference Vegetation Index (NDVI) as an index of NPP. Results show that, between 1982 and 2008, an increased vegetation greenness was observed in 27% of the protected areas monitored (mostly in Western Africa), and an increased seasonality in 9% of them (mostly in Eastern and Southern Africa). Our results lend support to current expectations regarding the impacts of climate change, and demonstrate how protected areas of IUCN categories I and II could be used to track the effect of climate change on ecosystem functioning in Africa, and possibly elsewhere. The study highlights the need for a dynamic approach to conservation, where the relevance and efficiency of management actions need to be regularly evaluated. It also demonstrates that satellite-based approaches offer a cheap, verifiable way to quickly identify protected areas of concern at a global scale, supporting managers in their effort to design and apply adaptive management strategies.     

Forecasting Distributional Responses of Limber Pine to Climate Change at Management-Relevant Scales in Rocky Mountain National Park

Resource managers at parks and other protected areas are increasingly expected to factor climate change explicitly into their decision making frameworks. However, most protected areas are small relative to the geographic ranges of species being managed, so forecasts need to consider local adaptation and community dynamics that are correlated with climate and affect distributions inside protected area boundaries. Additionally, niche theory suggests that species'' physiological capacities to respond to climate change may be underestimated when forecasts fail to consider the full breadth of climates occupied by the species rangewide. Here, using correlative species distribution models that contrast estimates of climatic sensitivity inferred from the two spatial extents, we quantify the response of limber pine (Pinus flexilis) to climate change in Rocky Mountain National Park (Colorado, USA). Models are trained locally within the park where limber pine is the community dominant tree species, a distinct structural-compositional vegetation class of interest to managers, and also rangewide, as suggested by niche theory. Model forecasts through 2100 under two representative concentration pathways (RCP 4.5 and 8.5 W/m²) show that the distribution of limber pine in the park is expected to move upslope in elevation, but changes in total and core patch area remain highly uncertain. Most of this uncertainty is biological, as magnitudes of projected change are considerably more variable between the two spatial extents used in model training than they are between RCPs, and novel future climates only affect local model predictions associated with RCP 8.5 after 2091. Combined, these results illustrate the importance of accounting for unknowns in species'' climatic sensitivities when forecasting distributional scenarios that are used to inform management decisions. We discuss how our results for limber pine may be interpreted in the context of climate change vulnerability and used to help guide adaptive management.     

Choice of baseline climate data impacts projected species' responses to climate change

Climate data created from historic climate observations are integral to most assessments of potential climate change impacts, and frequently comprise the baseline period used to infer species‐climate relationships. They are often also central to downscaling coarse resolution climate simulations from General Circulation Models (GCMs) to project future climate scenarios at ecologically relevant spatial scales. Uncertainty in these baseline data can be large, particularly where weather observations are sparse and climate dynamics are complex (e.g. over mountainous or coastal regions). Yet, importantly, this uncertainty is almost universally overlooked when assessing potential responses of species to climate change. Here, we assessed the importance of historic baseline climate uncertainty for projections of species' responses to future climate change. We built species distribution models (SDMs) for 895 African bird species of conservation concern, using six different climate baselines. We projected these models to two future periods (2040–2069, 2070–2099), using downscaled climate projections, and calculated species turnover and changes in species‐specific climate suitability. We found that the choice of baseline climate data constituted an important source of uncertainty in projections of both species turnover and species‐specific climate suitability, often comparable with, or more important than, uncertainty arising from the choice of GCM. Importantly, the relative contribution of these factors to projection uncertainty varied spatially. Moreover, when projecting SDMs to sites of biodiversity importance (Important Bird and Biodiversity Areas), these uncertainties altered site‐level impacts, which could affect conservation prioritization. Our results highlight that projections of species' responses to climate change are sensitive to uncertainty in the baseline climatology. We recommend that this should be considered routinely in such analyses.     

Climate change and biological invasions: evidence,expectations, and response options

A changing climate may directly or indirectly influence biological invasions by altering the likelihood of introduction or establishment, as well as modifying the geographic range, environmental impacts, economic costs or management of alien species. A comprehensive assessment of empirical and theoretical evidence identified how each of these processes is likely to be shaped by climate change for alien plants, animals and pathogens in terrestrial, freshwater and marine environments of Great Britain. The strongest contemporary evidence for the potential role of climate change in the establishment of new alien species is for terrestrial arthropods, as a result of their ectothermic physiology, often high dispersal rate and their strong association with trade as well as commensal relationships with human environments. By contrast, there is little empirical support for higher temperatures increasing the rate of alien plant establishment due to the stronger effects of residence time and propagule pressure. The magnitude of any direct climate effect on the number of new alien species will be small relative to human‐assisted introductions driven by socioeconomic factors. Casual alien species (sleepers) whose population persistence is limited by climate are expected to exhibit greater rates of establishment under climate change assuming that propagule pressure remains at least at current levels. Surveillance and management targeting sleeper pests and diseases may be the most cost‐effective option to reduce future impacts under climate change. Most established alien species will increase their distribution range in Great Britain over the next century. However, such range increases are very likely be the result of natural expansion of populations that have yet to reach equilibrium with their environment, rather than a direct consequence of climate change. To assess the potential realised range of alien species will require a spatially explicit approach that not only integrates bioclimatic suitability and population‐level demographic rates but also simulation of landscape‐level processes (e.g. dispersal, land‐use change, host/habitat distribution, non‐climatic edaphic constraints). In terms of invasive alien species that have known economic or biodiversity impacts, the taxa that are likely to be the most responsive are plant pathogens and insect pests of agricultural crops. However, the extent to which climate adaptation strategies lead to new crops, altered rotations, and different farming practices (e.g. irrigation, fertilization) will all shape the potential agricultural impacts of alien species. The greatest uncertainty in the effects of climate change on biological invasions exists with identifying the future character of new species introductions and predicting ecosystem impacts. Two complementary strategies may work under these conditions of high uncertainty: (i) prioritise ecosystems in terms of their perceived vulnerability to climate change and prevent ingress or expansion of alien species therein that may exacerbate problems; (ii) target those ecosystem already threatened by alien species and implement management to prevent the situation deteriorating under climate change.     

Using value of information to prioritize research needs for migratory bird management under climate change: a case study using federal land acquisition in the United States

In response to global habitat loss, many governmental and non‐governmental organizations have implemented land acquisition programs to protect critical habitats permanently for priority species. The ability of these protected areas to meet future management objectives may be compromised if the effects of climate change are not considered in acquisition decisions. Unfortunately, the effects of climate change on ecological systems are complex and plagued by uncertainty, making it difficult for organizations to prioritize research needs to improve decision‐making. Herein, we demonstrate the use of qualitative value of information analysis to identify and prioritize which sources of uncertainty should be reduced to improve land acquisition decisions to protect migratory birds in the face of climate change. The qualitative value of information analysis process involves four steps: (i) articulating alternative hypotheses; (ii) determining the magnitude of uncertainty regarding each hypothesis; (iii) evaluating the relevance of each hypothesis to acquisition decision‐making; and (iv) assessing the feasibility of reducing the uncertainty surrounding each hypothesis through research and monitoring. We demonstrate this approach using the objectives of 3 U.S. federal land acquisition programs that focus on migratory bird management. We used a comprehensive literature review, expert elicitation, and professional judgement to evaluate 11 hypotheses about the effect of climate change on migratory birds. Based on our results, we provide a list of priorities for future research and monitoring to reduce uncertainty and improve land acquisition decisions for the programs considered in our case study. Reducing uncertainty about how climate change will influence the spatial distribution of priority species and biotic homogenization were identified as the highest priorities for future research due to both the value of this information for improving land acquisition decisions and the feasibility of reducing uncertainty through research and monitoring. Research on how changes in precipitation patterns and winter severity will influence migratory bird abundance is also expected to benefit land acquisition decisions. By contrast, hypotheses about phenology and migration distance were identified as low priorities for research. By providing a rigorous and transparent approach to prioritizing research, we demonstrate that qualitative value of information is a valuable tool for prioritizing research and improving management decisions in other complex, high‐uncertainty cases where traditional quantitative value of information analysis is not possible. Given the inherent complexity of ecological systems under climate change, and the difficulty of identifying management‐relevant research priorities, we expect this approach to have wide applications within the field of natural resource management.     

Where can managers effectively resist climate-driven ecological transformation in pinyon–juniper woodlands of the US Southwest?

Pinyon–juniper (PJ) woodlands are an important component of dryland ecosystems across the US West and are potentially susceptible to ecological transformation. However, predicting woodland futures is complicated by species-specific strategies for persisting and reproducing under drought conditions, uncertainty in future climate, and limitations to inferring demographic rates from forest inventory data. Here, we leverage new demographic models to quantify how climate change is expected to alter population demographics in five PJ tree species in the US West and place our results in the context of a climate adaptation framework to resist, accept, or direct ecological transformation. Two of five study species, Pinus edulis and Juniperus monosperma, are projected to experience population declines, driven by both rising mortality and decreasing recruitment rates. These declines are reasonably consistent across various climate futures, and the magnitude of uncertainty in population growth due to future climate is less than uncertainty due to how demographic rates will respond to changing climate. We assess the effectiveness of management to reduce tree density and mitigate competition, and use the results to classify southwest woodlands into areas where transformation is (a) unlikely and can be passively resisted, (b) likely but may be resisted by active management, and (c) likely unavoidable, requiring managers to accept or direct the trajectory. Population declines are projected to promote ecological transformation in the warmer and drier PJ communities of the southwest, encompassing 37.1%–81.1% of our sites, depending on future climate scenarios. Less than 20% of sites expected to transform away from PJ have potential to retain existing tree composition by density reduction. Our results inform where this adaptation strategy could successfully resist ecological transformation in coming decades and allow for a portfolio design approach across the geographic range of PJ woodlands.     

A continent under stress: interactions, feedbacks and risks associated with impact of modified land cover on Australia's climate

Global climate change is the major and most urgent global environmental issue. Australia is already experiencing climate change as evidenced by higher temperatures and more frequent and severe droughts. These impacts are compounded by increasing land use pressures on natural resources and native ecosystems. This paper provides a synthesis of the interactions, feedbacks and risks of natural climate variability, climate change and land use/land cover change (LUCC) impacting on the Australian continent and how they vary regionally. We review evidence of climate change and underlying processes resulting from interactions between global warming caused by increased concentration of atmospheric greenhouse gases and modification of the land surface. The consequences of ignoring the effect of LUCC on current and future droughts in Australia could have catastrophic consequences for the nation's environment, economy and communities. We highlight the need for more integrated, long-term and adaptive policies and regional natural resource management strategies that restore the beneficial feedbacks between native vegetation cover and local-regional climate, to help ameliorate the impact of global warming.