Monitoring the condition of natural resources in US national parks

Composite estimation to combine spatially overlapping environmental monitoring surveys

Long-term environmental monitoring surveys are designed to achieve a desired precision (measured by variance) of resource conditions based on natural variability information. Over time, increases in resource variability and in data use to address issues focused on small areas with limited sample sizes require bolstering of attainable precision. It is often prohibitive to do this by increasing sampling effort. In cases with spatially overlapping monitoring surveys, composite estimation offers a statistical way to obtain a precision-weighted combination of survey estimates to provide improved population estimates (more accurate) with improved precisions (lower variances). We present a composite estimator for overlapping surveys, a summary of compositing procedures, and a case study to illustrate the procedures and benefits of composite estimation. The study uses the two terrestrial monitoring surveys administered by the Bureau of Land Management (BLM) that entirely overlap. Using 2015-18 data and 13 land-health indicators, we obtained and compared survey and composite indicator estimates of percent area meeting land-health standards for sagebrush communities in Wyoming's Greater Sage-Grouse (Centrocercus urophasianus) Core and NonCore conservation areas on BLM-managed lands. We statistically assessed differences in indicator estimates between the conservation areas using composite estimates and estimates of the two surveys individually. We found composite variance to be about six to 24 units lower than 37% of the survey variances and composite estimates to differ by about six to 10 percentage points from six survey estimates. The composite improvements resulted in finding 11 indicators to statistically differ (p <0.05) between the conservation areas compared to only six and seven indicators for the individual surveys. Overall, we found composite estimation to be an efficient and useful option for improving environmental monitoring information where two surveys entirely overlap and suggest how this estimation method could be beneficial where environmental surveys partially overlap and in small area applications.

Mapping ecosystem services in protected areas. A systematic review

Protected areas (PAs) supply ecosystem services (ES) essential for human wellbeing. Mapping is a critical exercise that allows an understanding of the spatial distribution of the different ES in PAs. This work aims to conduct a systematic literature review on mapping ES in PAs. In order to carry out this systematic review, the Preferred Reporting Items for Systematic Reviews and Meta-Analyses method was applied. The results showed an increase in the number of works between 2012 and 2023, and they were especially conducted in Europe and Asia and less in North America, South America, and Oceania. Most studies were developed in terrestrial areas, and the International Union for Conservation of Nature classified them into types II and IV. Most of the works followed the Millennium Ecosystem Assessment classification and were mainly focused on the supply dimension. Regulating and maintenance and cultural ES were the most mapped dimensions in PAs. The most frequent provisioning ES mapped in PAs were Animals reared for nutritional purposes and Cultivated terrestrial plants grown for nutritional purposes. In regulating and maintenance, Maintaining nursery populations and habitats and Regulation of the chemical composition of the atmosphere and oceans were the most analysed. For cultural ES, Characteristics of living systems that enable activities promoting health, recuperation, or enjoyment through active or immersive interactions and Characteristics of living systems that enable aesthetic experiences were the most mapped ES in PAs. Most works followed a quantitative approach, although the number of qualitative studies is high. Finally, most of the works needed to be validated, which may hamper the credibility of mapping ES in PAs. Overall, this systematic review contributed to a global picture of studies distribution, the areas where they are needed, and the most popular dimensions and sections as the methodologies were applied.

A Dataset of Amphibian Species in U.S. National Parks

National parks and other protected areas are important for preserving landscapes and biodiversity worldwide. An essential component of the mission of the United States (U.S.) National Park Service (NPS) requires understanding and maintaining accurate inventories of species on protected lands. We describe a new, national-scale synthesis of amphibian species occurrence in the NPS system. Many park units have a list of amphibian species observed within their borders compiled from various sources and available publicly through the NPSpecies platform. However, many of the observations in NPSpecies remain unverified and the lists are often outdated. We updated the amphibian dataset for each park unit by collating old and new park-level records and had them verified by regional experts. The new dataset contains occurrence records for 292 of the 424 NPS units and includes updated taxonomy, international and state conservation rankings, hyperlinks to a supporting reference for each record, specific notes, and related fields which can be used to better understand and manage amphibian biodiversity within a single park or group of parks.

Overabundant deer and invasive plants drive widespread regeneration debt in eastern United States national parks

Advanced regeneration, in the form of tree seedlings and saplings, is critical for ensuring the long-term viability and resilience of forest ecosystems in the eastern United States. Lack of regeneration and/or compositional mismatch between regeneration and canopy layers, called regeneration debt, can lead to shifts in forest composition, structure, and, in extreme cases, forest loss. In this study, we examined status and trends in regeneration across 39 national parks from Virginia to Maine, spanning 12 years to apply the regeneration debt concept. We further refined the concept by adding new metrics and classifying results into easily interpreted categories adapted from the literature: imminent failure, probable failure, insecure, and secure. We then used model selection to determine the potential drivers most influencing patterns of regeneration debt. Status and trends indicated widespread regeneration debt in eastern national parks, with 27 of 39 parks classified as imminent or probable failure. Deer browse impact was consistently the strongest predictor of regeneration abundance. The most pervasive component of regeneration debt observed across parks was a sapling bottleneck, characterized by critically low sapling density of native canopy species and significant declines in native canopy sapling basal area or density for most parks. Regeneration mismatches also threaten forest resilience in many parks, where native canopy seedlings and saplings were outnumbered by native subcanopy species, particularly species that are less palatable deer browse. The devastating impact of emerald ash borer eliminating ash as a native canopy tree also drove regeneration mismatches in many parks that contain abundant ash regeneration, demonstrating the vulnerability of forests that lack diverse understories to invasive pests and pathogens. These findings underscore the critical importance of an integrated forest management approach that promotes an abundant and diverse regeneration layer. In most cases, this can only be achieved through long-term (i.e., multidecadal) management of white-tailed deer and invasive plants. Small-scale disturbances that increase structural complexity may also promote regeneration where stress from deer and invasive plants is minimal. Without immediate and sustained management intervention, the forest loss we are already observing may become a widespread pattern in eastern national parks and the broader region.

Measuring the Impact of Conservation: The Growing Importance of Monitoring Fauna, Flora and Funga

Many stakeholders, from governments to civil society to businesses, lack the data they need to make informed decisions on biodiversity, jeopardising efforts to conserve, restore and sustainably manage nature. Here we review the importance of enhancing biodiversity monitoring, assess the challenges involved and identify potential solutions. Capacity for biodiversity monitoring needs to be enhanced urgently, especially in poorer, high-biodiversity countries where data gaps are disproportionately high. Modern tools and technologies, including remote sensing, bioacoustics and environmental DNA, should be used at larger scales to fill taxonomic and geographic data gaps, especially in the tropics, in marine and freshwater biomes, and for plants, fungi and invertebrates. Stakeholders need to follow best monitoring practices, adopting appropriate indicators and using counterfactual approaches to measure and attribute outcomes and impacts. Data should be made openly and freely available. Companies need to invest in collecting the data required to enhance sustainability in their operations and supply chains. With governments soon to commit to the post-2020 global biodiversity framework, the time is right to make a concerted push on monitoring. However, action at scale is needed now if we are to enhance results-based management adequately to conserve the biodiversity and ecosystem services we all depend on.

A comparison of monitoring designs to assess wildlife community parameters across spatial scales

Dedicated long-term monitoring at appropriate spatial and temporal scales is necessary to understand biodiversity losses and develop effective conservation plans. Wildlife monitoring is often achieved by obtaining data at a combination of spatial scales, ranging from local to broad, to understand the status, trends, and drivers of individual species or whole communities and their dynamics. However, limited resources for monitoring necessitates tradeoffs in the scope and scale of data collection. Careful consideration of the spatial and temporal allocation of finite sampling effort is crucial for monitoring programs that span multiple spatial scales. Here we evaluate the ability of five monitoring designs-stratified random, weighted effort, indicator unit, rotating panel, and split panel-to recover parameter values that describe the status (occupancy), trends (change in occupancy), and drivers (spatially varying covariate and an autologistic term) of wildlife communities at two spatial scales. Using an amphibian monitoring program that spans a network of US national parks as a motivating example, we conducted a simulation study for a regional community occupancy sampling program to compare the monitoring designs across varying levels of sampling effort (ranging from 10% to 50%). We found that the stratified random design outperformed the other designs for most parameters of interest at both scales and was thus generally preferable in balancing the estimation of status, trends, and drivers across scales. However, we found that other designs had improved performance in specific situations. For example, the rotating panel design performed best at estimating spatial drivers at a regional level. Thus, our results highlight the nuanced scenarios in which various design strategies may be preferred and offer guidance as to how managers can balance common tradeoffs in large-scale and long-term monitoring programs in terms of the specific knowledge gained. Monitoring designs that improve accuracy in parameter estimates are needed to guide conservation policy and management decisions in the face of broad-scale environmental challenges, but the preferred design is sensitive to the specific objectives of a monitoring program.

Identifying monitoring information needs that support the management of fish in large rivers

Management actions intended to benefit fish in large rivers can directly or indirectly affect multiple ecosystem components. Without consideration of the effects of management on non-target ecosystem components, unintended consequences may limit management efficacy. Monitoring can help clarify the effects of management actions, including on non-target ecosystem components, but only if data are collected to characterize key ecosystem processes that could affect the outcome. Scientists from across the U.S. convened to develop a conceptual model that would help identify monitoring information needed to better understand how natural and anthropogenic factors affect large river fishes. We applied the conceptual model to case studies in four large U.S. rivers. The application of the conceptual model indicates the model is flexible and relevant to large rivers in different geographic settings and with different management challenges. By visualizing how natural and anthropogenic drivers directly or indirectly affect cascading ecosystem tiers, our model identified critical information gaps and uncertainties that, if resolved, could inform how to best meet management objectives. Despite large differences in the physical and ecological contexts of the river systems, the case studies also demonstrated substantial commonalities in the data needed to better understand how stressors affect fish in these systems. For example, in most systems information on river discharge and water temperature were needed and available. Conversely, information regarding trophic relationships and the habitat requirements of larval fishes were generally lacking. This result suggests that there is a need to better understand a set of common factors across large-river systems. We provide a stepwise procedure to facilitate the application of our conceptual model to other river systems and management goals.

OUP accepted manuscript

Extreme events have increased in frequency globally, with a simultaneous surge in scientific interest about their ecological responses, particularly in sensitive freshwater, coastal, and marine ecosystems. We synthesized observational studies of extreme events in these aquatic ecosystems, finding that many studies do not use consistent definitions of extreme events. Furthermore, many studies do not capture ecological responses across the full spatial scale of the events. In contrast, sampling often extends across longer temporal scales than the event itself, highlighting the usefulness of long-term monitoring. Many ecological studies of extreme events measure biological responses but exclude chemical and physical responses, underscoring the need for integrative and multidisciplinary approaches. To advance extreme event research, we suggest prioritizing pre- and postevent data collection, including leveraging long-term monitoring; making intersite and cross-scale comparisons; adopting novel empirical and statistical approaches; and developing funding streams to support flexible and responsive data collection.

A Systematic Review on the Integration of Remote Sensing and GIS to Forest and Grassland Ecosystem Health Attributes, Indicators, and Measures

It is important to protect forest and grassland ecosystems because they are ecologically rich and provide numerous ecosystem services. Upscaling monitoring from local to global scale is imperative in reaching this goal. The SDG Agenda does not include indicators that directly quantify ecosystem health. Remote sensing and Geographic Information Systems (GIS) can bridge the gap for large-scale ecosystem health assessment. We systematically reviewed field-based and remote-based measures of ecosystem health for forests and grasslands, identified the most important ones and provided an overview on remote sensing and GIS-based measures. We included 163 English language studies within terrestrial non-tropical biomes and used a pre-defined classification system to extract ecological stressors and attributes, collected corresponding indicators, measures, and proxy values. We found that the main ecological attributes of each ecosystem contribute differently in the literature, and that almost half of the examined studies used remote sensing to estimate indicators. The major stressor for forests was “climate change”, followed by “insect infestation”; for grasslands it was “grazing”, followed by “climate change”. “Biotic interactions, composition, and structure” was the most important ecological attribute for both ecosystems. “Fire disturbance” was the second most important for forests, while for grasslands it was “soil chemistry and structure”. Less than a fifth of studies used vegetation indices; NDVI was the most common. There are monitoring inconsistencies from the broad range of indicators and measures. Therefore, we recommend a standardized field, GIS, and remote sensing-based approach to monitor ecosystem health and integrity and facilitate land managers and policy-makers.

Improving the ability of a BACI design to detect impacts within a kelp-forest community

Distinguishing between human impacts and natural variation in abundance remains difficult because most species exhibit complex patterns of variation in space and time. When ecological monitoring data are available, a before-after-control-impact (BACI) analysis can control natural spatial and temporal variation to better identify an impact and estimate its magnitude. However, populations with limited distributions and confounding spatial-temporal dynamics can violate core assumptions of BACI-type designs. In this study, we assessed how such properties affect the potential to identify impacts. Specifically, we quantified the conditions under which BACI analyses correctly (or incorrectly) identified simulated anthropogenic impacts in a spatially and temporally replicated data set of fish, macroalgal, and invertebrate species found on nearshore subtidal reefs in southern California, USA. We found BACI failed to assess very localized impacts, and had low power but high precision when assessing region-wide impacts. Power was highest for severe impacts of moderate spatial scale, and impacts were most easily detected in species with stable, widely distributed populations. Serial autocorrelation in the data greatly inflated false impact detection rates, and could be partly controlled for statistically, while spatial synchrony in dynamics had no consistent effect on power or false detection rates. Unfortunately, species that offer high power to detect real impacts were also more likely to detect impacts where none had occurred. However, considering power and false detection rates together can identify promising indicator species, and collectively analyzing data for similar species improved the net ability to assess impacts. These insights set expectations for the sizes and severities of impacts that BACI analyses can detect in real systems, point to the importance of serial autocorrelation (but not of spatial synchrony), and indicate how to choose the species, and groups of species, that can best identify impacts.

COVID-19 pandemic impacts on conservation research, management, and public engagement in US national parks

The COVID-19 pandemic has disrupted the timing and substance of conservation research, management, and public engagement in protected areas around the world. This disruption is evident in US national parks, which play a key role in protecting natural and cultural resources and providing outdoor experiences for the public. Collectively, US national parks protect 34 million ha, host more than 300 million visits annually, and serve as one of the world's largest informal education organizations. The pandemic has altered park conditions and operations in a variety of ways. Shifts in operational conditions related to safety issues, reduced staffing, and decreased park revenues have forced managers to make difficult trade-offs among competing priorities. Long-term research and monitoring of the health of ecosystems and wildlife populations have been interrupted. Time-sensitive management practices, such as control of invasive plants and restoration of degraded habitat, have been delayed. And public engagement has largely shifted from in-person experiences to virtual engagement through social media and other online interactions. These changes pose challenges for accomplishing important science, management, and public engagement goals, but they also create opportunities for developing more flexible monitoring programs and inclusive methods of public engagement. The COVID-19 pandemic reinforces the need for strategic science, management planning, flexible operations, and online public engagement to help managers address rapid and unpredictable challenges.

NABat: A top-down, bottom-up solution to collaborative continental-scale monitoring

Collaborative monitoring over broad scales and levels of ecological organization can inform conservation efforts necessary to address the contemporary biodiversity crisis. An important challenge to collaborative monitoring is motivating local engagement with enough buy-in from stakeholders while providing adequate top-down direction for scientific rigor, quality control, and coordination. Collaborative monitoring must reconcile this inherent tension between top-down control and bottom-up engagement. Highly mobile and cryptic taxa, such as bats, present a particularly acute challenge. Given their scale of movement, complex life histories, and rapidly expanding threats, understanding population trends of bats requires coordinated broad-scale collaborative monitoring. The North American Bat Monitoring Program (NABat) reconciles top-down, bottom-up tension with a hierarchical master sample survey design, integrated data analysis, dynamic data curation, regional monitoring hubs, and knowledge delivery through web-based infrastructure. NABat supports collaborative monitoring across spatial and organizational scales and the full annual lifecycle of bats.

Long-term trends indicate that invasive plants are pervasive and increasing in eastern national parks

While invasive plant distributions are relatively well known in the eastern United States, temporal changes in species distributions and interactions among species have received little attention. Managers are therefore left to make management decisions without knowing which species pose the greatest threats based on their ability to spread, persist and outcompete other invasive species. To fill this gap, we used the U.S. National Park Service's Inventory and Monitoring Program data collected from over 1,400 permanent forest plots spanning 12 yr and covering 39 eastern national parks to analyze invasive plant trends. We analyzed trends in abundance at multiple scales, including plot frequency, quadrat frequency, and average quadrat cover. We examined trends overall, by functional group, and by species. We detected considerably more increasing than decreasing trends in invasive plant abundance. In fact, 80% of the parks in our study had at least one significant increasing trend in invasive abundance over time. Where detected, significant negative trends tended to be herbaceous or graminoid species. However, these declines were often countered by roughly equivalent increases in invasive shrubs over the same time period, and we only detected overall declines in invasive abundance in two parks in our study. Present in over 30% of plots and responsible for the steepest and greatest number of significant increases, Japanese stiltgrass (Microstegium vimineum) was the most aggressive invader in our study and is a high management priority. Invasive shrubs, especially Japanese barberry (Berberis thunbergii), Japanese honeysuckle (Lonicera japonica), multiflora rose (Rosa multiflora), and wineberry (Rubus phoenicolasius), also increased across multiple parks, and sometimes at the expense of Japanese stiltgrass. Given the added risks to human health from tick-borne diseases, invasive shrubs are a high management priority. While these findings provide critical information to managers for species prioritization, they also demonstrate the incredible management challenge that invasive plants pose in protected areas, particularly since we documented few overall declines in invasive abundance. As parks work to overcome deferred maintenance of infrastructure, our findings suggest that deferred management of natural resources, particularly invasive species, requires similar attention and long-term commitment to reverse these widespread increasing invasive trends.

Post-Fire Vegetation Response in a Repeatedly Burned Low-Elevation Sagebrush Steppe Protected Area Provides Insights About Resilience and Invasion Resistance

Sagebrush steppe ecosystems are threatened by human land-use legacies, biological invasions, and altered fire and climate dynamics. Steppe protected areas are therefore of heightened conservation importance but are few and vulnerable to the same impacts broadly affecting sagebrush steppe. To address this problem, sagebrush steppe conservation science is increasingly emphasizing a focus on resilience to fire and resistance to non-native annual grass invasion as a decision framework. It is well-established that the positive feedback loop between fire and annual grass invasion is the driving process of most contemporary steppe degradation. We use a newly developed ordinal zero-augmented beta regression model fit to large-sample vegetation monitoring data from John Day Fossil Beds National Monument, USA, spanning 7 years to evaluate fire responses of two native perennial foundation bunchgrasses and two non-native invasive annual grasses in a repeatedly burned, historically grazed, and inherently low-resilient protected area. We structured our model hierarchically to support inferences about variation among ecological site types and over time after also accounting for growing-season water deficit, fine-scale topographic variation, and burn severity. We use a state-and-transition conceptual diagram and abundances of plants listed in ecological site reference conditions to formalize our hypothesis of fire-accelerated transition to ecologically novel annual grassland. Notably, big sagebrush (Artemisia tridentata) and other woody species were entirely removed by fire. The two perennial grasses, bluebunch wheatgrass (Pseudoroegneria spicata) and Thurber's needlegrass (Achnatherum thurberianum) exhibited fire resiliency, with no apparent trend after fire. The two annual grasses, cheatgrass (Bromus tectorum) and medusahead (Taeniatherum caput-medusae), increased in response to burn severity, most notably medusahead. Surprisingly, we found no variation in grass cover among ecological sites, suggesting fire-driven homogenization as shrubs were removed and annual grasses became dominant. We found contrasting responses among all four grass species along gradients of topography and water deficit, informative to protected-area conservation strategies. The fine-grained influence of topography was particularly important to variation in cover among species and provides a foothold for conservation in low-resilient, aridic steppe. Broadly, our study demonstrates how to operationalize resilience and resistance concepts for protected areas by integrating empirical data with conceptual and statistical models.

Assessing trends and vulnerabilities in the mutualism between whitebark pine (Pinus albicaulis) and Clark's nutcracker (Nucifraga columbiana) in national parks of the Sierra-Cascade region

Dispersal of whitebark pine (Pinus albicaulis Engelm.), a keystone species of many high-elevation ecosystems in western North America, depends on Clark’s nutcracker (Nucifraga columbiana Wilson), a seed-caching bird with an affinity for whitebark seeds. To the extent that this dependence is mutual, declines in whitebark seed production could cause declines in nutcracker abundance. Whitebark pine is in decline across much of its range due to interacting stressors, including the non-native pathogen white pine blister rust (Cronartium ribicola J. C. Fisch.). We used avian point-count data and tree surveys from four national park units to investigate whether trends in whitebark pine can explain trends in Clark’s nutcracker. Spatial trends were modeled using recent data from two parks, while temporal trends were modeled using longer time-series of nutcracker and whitebark data from two additional parks. To assess the potential dependence of nutcrackers on whitebark, we linked a model of nutcracker density (accounting for detection probability) with a model of whitebark trends, using a Bayesian framework to translate uncertainty in whitebark metrics to uncertainty in nutcracker density. In Mount Rainier National Park, temporal models showed dramatic declines in nutcracker density concurrent with significant increases in whitebark crown mortality and trees infected with white pine blister rust. However, nutcrackers did not trend with whitebark metrics in North Cascades National Park Service Complex. In spatial models of data from Yosemite National Park and Sequoia-Kings Canyon National Park, nutcracker density varied not only with local cover of whitebark but also with elevation and, in Sequoia-Kings Canyon, with cover of another species of white pine. Our results add support for the hypothesis that the mutualism between whitebark pine and Clark’s nutcracker is vulnerable to disruption by blister rust, and our approach integrates data across monitoring programs to explore trends in species interactions.

Assessing Climate Change in the Trinational Upper Rhine Region: How Can We Operationalize Vulnerability Using an Indicator-Based, Meso-Scale Approach?

Climate vulnerability assessments are an important prerequisite for establishing successful climate adaptation strategies. Despite a growing number of assessments on the national or global scale, there is still a need for regionalized studies with a high resolution to identify meso-scale vulnerability patterns. In this paper, we present an indicator-based assessment that was carried out in the Trinational Metropolitan Region Upper Rhine within the Interreg-V project Clim’Ability. The analyzed region is characterized by strong cross-border and transnational linkages, similar ecological features and climatic stressors but differing political, administrative, cultural and legal conditions. In this rather complex setting, we operationalized a state-of-the art vulnerability framework using 18 quantified indicators and aggregating them into a vulnerability index. We show that it is possible to downscale the methods used in recent assessments to a regional context with a challenging data situation and discuss strengths and uncertainties. The results are mapped for stakeholder communication purposes. They provide an evidence-base to the identification of the trinational vulnerability pattern and may enable stakeholders and decision-makers to enhance their own climate adaptation planning.

Using a structured decision analysis to evaluate bald eagle vital signs monitoring in Southwest Alaska National Parks

Monitoring programs can benefit from an adaptive monitoring approach, where key decisions about why, where, what, and how to monitor are revisited periodically in order to ensure programmatic relevancy.The National Park Service (NPS) monitors status and trends of vital signs to evaluate compliance with the NPS mission. Although abundant, The Southwest Alaska Network (SWAN) monitors bald eagles because of their inherent importance to park visitors and role as an important ecological indicator. Our goal is to identify an optimal monitoring program that may be standardized among participating parks.We gathered an expert panel of scientists and managers, and implemented a Delphi Process to gather information about the bald eagle monitoring program. Panelists generated a list of means objectives for the monitoring program: minimizing cost, minimizing effort, maximizing the ability to detect change in bald eagle populations, and maximizing the amount of accurate information collected about bald eagles.We used a swing-weighting technique to assign importance to each objective. Collecting accurate information about bald eagles was considered the most important means objective.Combining panelist-generated information with objective importance, we analyzed the scenarios and defined the optimal decision using linear value modeling. Through our analysis, we found that a "Comprehensive" monitoring scenario, comprised of all feasible monitoring metrics, is the optimal monitoring scenario. Even with greatly increased cost, the Comprehensive monitoring scenario remains the best solution.We suggest further exploration of the cost and effort required for the Comprehensive scenario, to determine whether it is in the parks' best interest to begin monitoring additional metrics.

A cost efficient spatially balanced hierarchical sampling design for monitoring boreal birds incorporating access costs and habitat stratification

Predicting and mitigating impacts of climate change and development within the boreal biome requires a sound understanding of factors influencing the abundance, distribution, and population dynamics of species inhabiting this vast biome. Unfortunately, the limited accessibility of the boreal biome has resulted in sparse and spatially biased sampling, and thus our understanding of boreal bird population dynamics is limited. To implement effective conservation of boreal birds, a cost-effective approach to sampling the boreal biome will be needed. Our objective was to devise a sampling scheme for monitoring boreal birds that would improve our ability to model species-habitat relationships and monitor changes in population size and distribution. A statistically rigorous design to achieve these objectives would have to be spatially balanced and hierarchically structured with respect to ecozones, ecoregions and political jurisdictions. Therefore, we developed a multi-stage hierarchically structured sampling design known as the Boreal Optimal Sampling Strategy (BOSS) that included cost constraints, habitat stratification, and optimization to provide a cost-effective alternative to other common monitoring designs. Our design provided similar habitat and spatial representation to habitat stratification and equal-probability spatially balanced designs, respectively. Not only was our design able to achieve the desired habitat representation and spatial balance necessary to meet our objectives, it was also significantly less expensive (1.3−2.6 times less) than the alternative designs we considered. To further balance trade-offs between cost and representativeness prior to field implementation, we ran multiple iterations of the BOSS design and selected the one which minimized predicted costs while maximizing a multi-criteria evaluation of representativeness. Field implementation of the design in three vastly different regions over three field seasons showed that the approach can be implemented in a wide variety of logistical scenarios and ecological conditions. We provide worked examples and scripts to allow our approach to be implemented or adapted elsewhere. We also provide recommendations for possible future refinements to our approach, but recommend that our design now be implemented to provide unbiased information to assess the status of boreal birds and inform conservation and management actions.

Remote Sensing Applications in Monitoring of Protected Areas

Protected areas (PAs) have been established worldwide for achieving long-term goals in the conservation of nature with the associated ecosystem services and cultural values. Globally, 15% of the world’s terrestrial lands and inland waters, excluding Antarctica, are designated as PAs. About 4.12% of the global ocean and 10.2% of coastal and marine areas under national jurisdiction are set as marine protected areas (MPAs). Protected lands and waters serve as the fundamental building blocks of virtually all national and international conservation strategies, supported by governments and international institutions. Some of the PAs are the only places that contain undisturbed landscape, seascape and ecosystems on the planet Earth. With intensified impacts from climate and environmental change, PAs have become more important to serve as indicators of ecosystem status and functions. Earth’s remaining wilderness areas are becoming increasingly important buffers against changing conditions. The development of remote sensing platforms and sensors and the improvement in science and technology provide crucial support for the monitoring and management of PAs across the world. In this editorial paper, we reviewed research developments using state-of-the-art remote sensing technologies, discussed the challenges of remote sensing applications in the inventory, monitoring, management and governance of PAs and summarized the highlights of the articles published in this Special Issue.

Developing a circumpolar programme for the monitoring of Arctic terrestrial biodiversity

The Arctic is undergoing biological and environmental changes, and a coordinated effort to monitor is critical to detect these changes. The Circumpolar Biodiversity Monitoring Programme (CBMP) of the Arctic Council biodiversity working group, Conservation of Arctic Flora and Fauna (CAFF), has developed pan-Arctic biodiversity monitoring plans that aims to improve the ability to detect and report on long-term changes. Whilst introducing this special issue, this paper also presents the making of the terrestrial monitoring plan and discusses how the plan follows the steps required for an adaptive and ecosystem-based monitoring programme. In this article, we discuss how data on key findings can be used to inform circumpolar and global assessments, including the State of the Arctic Terrestrial Biodiversity Report, which will be the first terrestrial assessment made by the CBMP. Key findings, advice for future monitoring and lessons learned will be used in planning next steps of pan-Arctic coordinated monitoring.

Right place. Right time. Right tool: guidance for using target analysis to increase the likelihood of invasive species detection

In response to the National Invasive Species Council’s 2016–2018 Management Plan, this paper provides guidance on applying target analysis as part of a comprehensive framework for the early detection of and rapid response to invasive species (EDRR). Target analysis is a strategic approach for detecting one or more invasive species at a specific locality and time, using a particular method and/or technology(ies). Target analyses, which are employed across a wide range of disciplines, are intended to increase the likelihood of detection of a known target in order to maximize survey effectiveness and cost-efficiency. Although target analyses are not yet a standard approach to invasive species management, some federal agencies are employing target analyses in principle and/or in part to improve EDRR capacities. These initiatives can provide a foundation for a more standardized and comprehensive approach to target analyses. Guidance is provided for improving computational information. Federal agencies and their partners would benefit from a concerted effort to collect the information necessary to perform rigorous target analyses and make it available through open access platforms.

Exposure of Protected and Unprotected Forest to Plant Invasions in the Eastern United States

Research Highlights: We demonstrate a macroscale framework combining an invasibility model with forest inventory data, and evaluate regional forest exposure to harmful invasive plants under different types of forest protection. Background and Objectives: Protected areas are a fundamental component of natural resource conservation. The exposure of protected forests to invasive plants can impede achievement of conservation goals, and the effectiveness of protection for limiting forest invasions is uncertain. We conducted a macroscale assessment of the exposure of protected and unprotected forests to harmful invasive plants in the eastern United States. Materials and Methods: Invasibility (the probability that a forest site has been invaded) was estimated for 82,506 inventory plots from site and landscape attributes. The invaded forest area was estimated by using the inventory sample design to scale up plot invasibility estimates to all forest area. We compared the invasibility and the invaded forest area of seven categories of protection with that of de facto protected (publicly owned) forest and unprotected forest in 13 ecological provinces. Results: We estimate approximately 51% of the total forest area has been exposed to harmful invasive plants, including 30% of the protected forest, 38% of the de facto protected forest, and 56% of the unprotected forest. Based on cumulative invasibility, the relative exposure of protection categories depended on the assumed invasibility threshold. Based on the invaded forest area, the five least-exposed protection categories were wilderness area (13% invaded), national park (18%), sustainable use (26%), nature reserve (31%), and de facto protected Federal land (36%). Of the total uninvaded forest area, only 15% was protected and 14% had de facto protection. Conclusions: Any protection is better than none, and public ownership alone is as effective as some types of formal protection. Since most of the remaining uninvaded forest area is unprotected, landscape-level management strategies will provide the most opportunities to conserve it.

Wild bees of Grand Staircase-Escalante National Monument: richness, abundance, and spatio-temporal beta-diversity

Interest in bees has grown dramatically in recent years in light of several studies that have reported widespread declines in bees and other pollinators. Investigating declines in wild bees can be difficult, however, due to the lack of faunal surveys that provide baseline data of bee richness and diversity. Protected lands such as national monuments and national parks can provide unique opportunities to learn about and monitor bee populations dynamics in a natural setting because the opportunity for large-scale changes to the landscape are reduced compared to unprotected lands. Here we report on a 4-year study of bees in Grand Staircase-Escalante National Monument (GSENM), found in southern Utah, USA. Using opportunistic collecting and a series of standardized plots, we collected bees throughout the six-month flowering season for four consecutive years. In total, 660 bee species are now known from the area, across 55 genera, and including 49 new species. Two genera not previously known to occur in the state of Utah were discovered, as well as 16 new species records for the state. Bees include ground-nesters, cavity- and twig-nesters, cleptoparasites, narrow specialists, generalists, solitary, and social species. The bee fauna reached peak diversity each spring, but also experienced a second peak in diversity in late summer, following monsoonal rains. The majority of GSENM’s bees are highly localized, occurring in only a few locations throughout the monument, and often in low abundance, but consistently across the four years. Only a few species are widespread and super-abundant. Certain flowering plants appear to be inordinately attractive to the bees in GSENM, including several invasive species. GSENM protects one of the richest bee faunas in the west; the large elevational gradient, incredible number of flowering plants, and the mosaic of habitats are all likely contributors to this rich assemblage of bees.

Trend estimation for complex survey designs of water chemistry indicators from Sierra Nevada Lakes

Surveys for long-term monitoring programs managing natural resources often incorporate sampling design complexity. However, design weights are often ignored in trend models of data from complex sampling designs. Generalized random tessellation stratified samples of a simulated population of lakes are selected with various levels of survey design complexity, and three trend approaches are compared. We compare an unweighted trend model, linear regression models of the trend in design-based estimates of annual status, and a probability-weighted iterative generalized least squares (PWIGLS) approach with a linearization variance. The bias and confidence interval coverage of the trend estimate and the size and power of the trend test are used to evaluate weighted and unweighted approaches. We find that the unweighted approach often outperforms the other trend approaches by providing high power for trend detection and nominal confidence interval coverage of the true trend regression parameter. We also find that variance composition and revisit design structure affect the performance of the PWIGLS estimator. When a subpopulation exhibiting an extreme trend is sampled disproportionately to its occurrence in the population, the unweighted approach may produce biased estimates of trend with poor confidence interval coverage. We recommend considering variance composition and potential subpopulation trends when selecting sampling designs and trend analysis approaches.

Optimization of an ecological integrity monitoring program for protected areas: Case study for a network of national parks

Over the last few years, several of the world’s national park networks have implemented ecological integrity monitoring programs. These programs are based on a series of indicators to detect changes in ecosystem integrity. There are many scientific and logistical challenges in developing these programs due to limits in both our knowledge of ecosystems functioning and the resources for implementing such programs. Thus, the relatively quick and simple implementation of many monitoring programs has been to the detriment of their scientific validity. Few studies have focused on evaluating an entire monitoring program. This project presents an approach to evaluate the ecological and statistical relevance of ecosystem integrity indicators measured within a program with the goal of iterative optimization. The approach is based on three complementary elements: (1) spatial characterization of park ecosystems based on the classification of satellite imagery, (2) ecological validation of indicators based on ecosystem conceptual models and (3) statistical validation of indicators based on analyses of statistical power. This innovative approach allows a systematic, quantified, reproducible and generalizable review of the indicators of an ecological integrity monitoring program. It provides managers with an overview of the spatial representativeness of indicators, their ecological and statistical relevance according to different parameters such as the period monitored, the amount of change to be detected, and the degree of significance. Thus, the approach identifies monitoring gaps and offers various alternatives for improving sampling. The approach was developed and tested in the network of Quebec national parks, more specifically in the Frontenac, Jacques-Cartier and Bic national parks. The results clearly identify the strengths and weaknesses of the current program in place and possible improvements are proposed for these parks. This approach is a relevant tool for park networks, particularly for those that have limited resources for monitoring ecological integrity.

Vulnerability and fragility risk indices for non-renewable resources

Protected areas are tasked with mitigating impacts to a wide range of invaluable resources. These resources are often subject to a variety of potential natural and anthropogenic impacts that require monitoring efforts and management actions to minimize the degradation of these resources. However, due to insufficient funding and staff, managers often have to prioritize efforts, leaving some resources at higher risk to impact. Attempts to address this issue have resulted in numerous qualitative and semi-quantitative frameworks for prioritization based on resource vulnerability. Here, we add to those methods by modifying an internationally standardized vulnerability framework, quantify both resource vulnerability, susceptibility to human disturbance, and fragility, susceptibility to natural disturbance. This modified framework quantifies impacts through a six-step process: identifying the resource and management objectives, identifying exposure and sensitivity indicators, define scoring criteria for each indicator, collect and compile data, calculate indices, and prioritize sites for mitigations. We applied this methodology to two resource types in Grand Canyon National Park (GRCA): caves and fossil sites. Three hundred sixty-five cave sites and 127 fossil sites in GRCA were used for this analysis. The majority of cave and fossil sites scored moderate to low vulnerability (0-6 out of 10 points) and moderate to low fragility for fossils. The percentage of sites that fell in the high-priority range was 5.5% for fossils and 21.9% for caves. These results are consistent with the known state of these resources and the results present a tool for managers to utilize to prioritize monitoring and management needs.

Projected avifaunal responses to climate change across the U.S. National Park System

Birds in U.S. national parks find strong protection from many longstanding and pervasive threats, but remain highly exposed to effects of ongoing climate change. To understand how climate change is likely to alter bird communities in parks, we used species distribution models relating North American Breeding Bird Survey (summer) and Audubon Christmas Bird Count (winter) observations to climate data from the early 2000s and projected to 2041–2070 (hereafter, mid-century) under high and low greenhouse gas concentration trajectories, RCP8.5 and RCP2.6. We analyzed climate suitability projections over time for 513 species across 274 national parks, classifying them as improving, worsening, stable, potential colonization, and potential extirpation. U.S. national parks are projected to become increasingly important for birds in the coming decades as potential colonizations exceed extirpations in 62–100% of parks, with an average ratio of potential colonizations to extirpations of 4.1 in winter and 1.4 in summer under RCP8.5. Average species turnover is 23% in both summer and winter under RCP8.5. Species turnover (Bray-Curtis) and potential colonization and extirpation rates are positively correlated with latitude in the contiguous 48 states. Parks in the Midwest and Northeast are expected to see particularly high rates of change. All patterns are more extreme under RCP8.5 than under RCP2.6. Based on the ratio of potential colonization and extirpation, parks were classified into overall trend groups associated with specific climate-informed conservation strategies. Substantial change to bird and ecological communities is anticipated in coming decades, and current thinking suggests managing towards a forward-looking concept of ecological integrity that accepts change and novel ecological conditions, rather than focusing management goals exclusively on maintaining or restoring a static set of historical conditions.

Snowmelt timing, phenology, and growing season length in conifer forests of Crater Lake National Park, USA

Anthropogenic climate change is having significant impacts on montane and high-elevation areas globally. Warmer winter temperatures are driving reduced snowpack in the western USA with broad potential impacts on ecosystem dynamics of particular concern for protected areas. Vegetation phenology is a sensitive indicator of ecological response to climate change and is associated with snowmelt timing. Human monitoring of climate impacts can be resource prohibitive for land management agencies, whereas remotely sensed phenology observations are freely available at a range of spatiotemporal scales. Little work has been done in regions dominated by evergreen conifer cover, which represents many mountain regions at temperate latitudes. We used moderate resolution imaging spectroradiometer (MODIS) data to assess the influence of snowmelt timing and elevation on five phenology metrics (green up, maximum greenness, senescence, dormancy, and growing season length) within Crater Lake National Park, Oregon, USA from 2001 to 2012. Earlier annual mean snowmelt timing was significantly correlated with earlier onset of green up at the landscape scale. Snowmelt timing and elevation have significant explanatory power for phenology, though with high variability. Elevation has a moderate control on early season indicators such as snowmelt timing and green up and less on late-season variables such as senescence and growing season length. PCA results show that early season indicators and late season indicators vary independently. These results have important implications for ecosystem dynamics, management, and conservation, particularly of species such as whitebark pine (Pinus albicaulis) in alpine and subalpine areas.