Conservation Biology最新文献

Many citizen scientists are highly motivated to help address the current extinction crisis. Their work is making valuable contributions to protecting species by raising awareness, identifying species occurrences, assessing population trends, and informing direct management actions, such as captive breeding. However, clear guidance is lacking about how to use existing citizen science data sets and how to design effective citizen science programs that directly inform extinction risk assessments and resulting conservation actions based on the International Union for Conservation of Nature (IUCN) Red List criteria. This may be because of a mismatch between what citizen science can deliver to address extinction risk and the reality of what is needed to inform threatened species listing based on IUCN criteria. To overcome this problem, we examined each IUCN Red List criterion (A-E) relative to the five major types of citizen science outputs relevant to IUCN assessments (occurrence data, presence-absence observations, structured surveys, physical samples, and narratives) to recommend which outputs are most suited to use when applying the IUCN extinction risk assessment process. We explored real-world examples of citizen science projects on amphibians and fungi that have delivered valuable data and knowledge for IUCN assessments. We found that although occurrence data are routinely used in the assessment process, simply adding more observations of occurrence from citizen science information may not be as valuable as inclusion of more nuanced data types, such as presence-absence data or information on threats from structured surveys. We then explored the characteristics of citizen science projects that have already delivered valuable data to support assessments. These projects were led by recognized experts who champion and validate citizen science data, thereby giving greater confidence in its accuracy. We urge increased recognition of the value of citizen science data within the assessment process.

Finding effective pathogen mitigation strategies is one of the biggest challenges humans face today. In the context of wildlife, emerging infectious diseases have repeatedly caused widespread host morbidity and population declines of numerous taxa. In areas yet unaffected by a pathogen, a proactive management approach has the potential to minimize or prevent host mortality. However, typically critical information on disease dynamics in a novel host system is lacking, empirical evidence on efficacy of management interventions is limited, and there is a lack of validated predictive models. As such, quantitative support for identifying effective management interventions is largely absent, and the opportunity for proactive management is often missed. We considered the potential invasion of the chytrid fungus, Batrachochytrium salamandrivorans (Bsal), whose expected emergence in North America poses a severe threat to hundreds of salamander species in this global salamander biodiversity hotspot. We developed and parameterized a dynamic multistate occupancy model to forecast host and pathogen occurrence, following expected emergence of the pathogen, and evaluated the response of salamander populations to different management scenarios. Our model forecasted that taking no action is expected to be catastrophic to salamander populations. Proactive action was predicted to maximize host occupancy outcomes relative to wait-and-see reactive management, thus providing quantitative support for proactive management opportunities. The eradication of Bsal was unlikely under all the evaluated management options. Contrary to our expectations, even early pathogen detection had little effect on Bsal or host occupancy outcomes. Our results provide quantitative support that proactive management is the optimal strategy for promoting persistence of disease-threatened salamander populations. Our approach fills a critical gap by defining a framework for evaluating management options prior to pathogen invasion and can thus serve as a template for addressing novel disease threats that jeopardize wildlife and human health.

The Pacific Islands region is home to several of the world's biodiversity hotspots, yet its unique flora and fauna are under threat because of biological invasions. These invasions are likely to proliferate as human activity increases and large-scale natural disturbances unfold, exacerbated by climate change. Remote sensing data and techniques provide a feasible method to map and monitor invasive plant species and inform invasive plant species management across the Pacific Islands region. We used case studies taken from literature retrieved from Google Scholar, 3 regional agencies' digital libraries, and 2 online catalogs on invasive plant species management to examine the uptake and challenges faced in the implementation of remote sensing technology in the Pacific region. We synthesized remote sensing techniques and outlined their potential to detect and map invasive plant species based on species phenology, structural characteristics, and image texture algorithms. The application of remote sensing methods to detect invasive plant species was heavily reliant on species ecology, extent of invasion, and available geospatial and remotely sensed image data. However, current mechanisms that support invasive plant species management, including policy frameworks and geospatial data infrastructure, operated in isolation, leading to duplication of efforts and creating unsustainable solutions for the region. For remote sensing to support invasive plant species management in the region, key stakeholders including conservation managers, researchers, and practitioners; funding agencies; and regional organizations must invest, where possible, in the broader geospatial and environmental sector, integrate, and streamline policies and improve capacity and technology access.

Grassland conservation planning often focuses on high-risk landscapes, but many grassland conversion models are not designed to optimize conservation planning because they lack multidimensional risk assessments and are misaligned with ecological and conservation delivery scales. To aid grassland conservation planning, we developed landscape-scale models at relevant scales that predict future (2021-2031) total and proportional loss of unprotected grassland to cropland or development. We developed models for 20 ecoregions across the contiguous United States by relating past conversion (2011-2021) to a suite of covariates in random forest regression models and applying the models to contemporary covariates to predict future loss. Overall, grassland loss models performed well, and explanatory power varied spatially across ecoregions (total loss model: weighted group mean R² = 0.89 [range: 0.83-0.96], root mean squared error [RMSE] = 9.29 ha [range: 2.83-22.77 ha]; proportional loss model: weighted group mean R² = 0.74 [range: 0.64-0.87], RMSE = 0.03 [range: 0.02-0.06]). Amount of crop in the landscape and distance to cities, ethanol plants, and concentrated animal feeding operations had high variable importance in both models. Total grass loss was greater when there were moderate amounts of grass, crop, or development (∼50%) in the landscape. Proportional grass loss was greater when there was less grass (∼<30%) and more crop or development (∼>50%). Some variables had a large effect on only a subset of ecoregions, for example, grass loss was greater when ∼>70% of the landscape was enrolled in the Conservation Reserve Program. Our methods provide a simple and flexible approach for developing risk layers well suited for conservation that can be extended globally. Our conversion models can support conservation planning by enabling prioritization as a function of risk that can be further optimized by incorporating biological value and cost.

Monitoring programs are pivotal to establishing sound management. Due to economic, logistic, and time limitations, monitoring programs often overlook differences among life-history stages. However, species occurrence does not necessarily mean population viability, and it is unclear to what extent monitoring programs that do not consider separately adult presence and reproduction provide effective management indications. Unfortunately, collecting data on certain life stages requires high sampling effort, leading to a trade-off between model reliability and resources needed for monitoring. We collected data on presence and reproduction of amphibians by monitoring 207 waterbodies in Lombardy (northern Italy) in 2017-2022. We then used multistate occupancy models to test whether certain environmental features, namely, pond area, hydroperiod, forest cover, shade, aquatic vegetation, and predators' presence, differentially affected adult occurrence and breeding probabilities of multiple amphibian species. To assess optimal sampling efforts, we modeled the detection probabilities of adults and reproduction across multiple species. Finally, we identified the optimal monitoring strategy under different scenarios of resource availability, comparing adult-only monitoring versus joint assessment of the occurrence of adults and reproduction. In many cases, the main drivers of adult occurrence and reproduction did not coincide because most investigated ecological variables affected one life stage or the other. Forest area, for instance, increased occurrence probabilities of adults of the endemic Rana latastei but showed no effect on their reproduction probabilities. Quantitative estimates of the sampling effort showed that occurrence of adults was easier to spot in 4 out of 7 species. Multicriteria decision analyses showed that when resources were scarce, monitoring adults was the optimal strategy for those 4 species. Conversely, with more resources, monitoring both adults and reproduction emerged as the best strategy for all the considered species. Integrated monitoring of adults and reproduction is essential to comprehensively identify effective conservation measures for amphibians.

Protected areas are typically considered a cornerstone of conservation programs and play a fundamental role in protecting natural areas and biodiversity. Human-driven land-use and land-cover (LULC) changes lead to habitat loss and biodiversity loss inside protected areas, impairing their effectiveness. However, the global dynamics of habitat quality and habitat degradation in protected areas remain unclear. We used the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model based on global annual remotely sensed data to examine the spatial and temporal trends in habitat quality and degradation in global terrestrial protected areas. Habitat quality represented the ability of habitats to provide suitable conditions for the persistence of individuals and populations, and habitat degradation represented the impacts on habitats from human-driven LULC changes in the surrounding landscape. Based on a linear mixed-effects modeling method, we also explored the relationship between habitat degradation trends and protected area characteristics, biophysical factors, and socioeconomic factors. Habitat quality declined by 0.005 (0.6%) and habitat degradation increased by 0.002 (11%) from 1992 to 2020 globally, and similar trends occurred even in remote or restrictively managed protected areas. Habitat degradation was attributed primarily to nonirrigated cropland (62%) and urbanization (27%) in 2020. Increases in elevation, gross domestic production per capita, and human population density and decreases in agricultural suitability were associated with accelerated habitat degradation. Our results suggest that human-induced LULC changes have expanded from already-exploited areas into relatively undisturbed areas, and that in wealthy countries in particular, degradation is related to rapid urbanization and increasing demand for agricultural products.

Agreements reached at the Antarctic Treaty Consultative Meetings (ATCMs) are among the primary means for addressing Antarctic conservation and environmental protection issues. However, according to contemporary scholars, Antarctic Treaty decision-making is becoming increasingly unresponsive to the rising environmental challenges in the region. We assessed the performance of Antarctic Treaty decision-making by measuring the rate and diversity of decision-making over the last 6 decades. To measure the rate, we counted the number of inputs and outputs of ATCMs and calculated the time taken for legally binding outputs to enter into force. To measure diversity, we calculated the range of topics addressed by the inputs and outputs of ATCMs. The average number of agreements reached per ATCM increased from 1961 to 2022. Although the diversity of Antarctic topics discussed at ATCMs remained consistently high, the diversity of topics on which legally binding agreements were adopted declined significantly. Antarctic issues-including those of highest priority-are now almost entirely dealt with through nonbinding, soft-law agreements. It is plausible that this move away from binding decisions reflects a dynamic governance institution evolving to respond to new pressures. However, we suggest that the change reveals a concerning shift in decision-making behavior and performance, unique to the treaty's history. Soft law is beneficial in some cases, but its overuse diminishes accountability and transparency, significantly reducing the parties' abilities to understand and measure their performance, including the outcomes and impacts of decisions. Although the rate and diversity of ATCM inputs and outputs provide only a partial view of decision-making performance, the exploration of these metrics provides a foundation for asking essential questions about the impacts of Antarctic Treaty governance on the region's environmental protection and conservation.

Many nations are struggling to reduce deforestation, despite having extensive environmental protection laws in place and commitments to international agreements that address the biodiversity and climate crises. We developed a novel framework to quantify the extent to which contemporary deforestation is being captured under national and subnational laws. We then applied this framework to northern Australia as a case study, a development and deforestation hotspot with ecosystems of global significance. First, deforestation may be compliant under all relevant legislation, either through assessment and approval or because of exemptions in the legislation. Second, deforestation may be compliant under at least one relevant law, but not all. Third, there may be no evidence of deforestation assessment or exemption from assessment, despite their apparent requirement, which could mean the deforestation is potentially noncompliant. Finally, deforestation may occur in an area or under circumstances that are beyond the intended scope of any relevant legislation. All deforestation that we analyzed was hypothetically covered by one or more laws. However, 65% of deforestation was potentially noncompliant with at least one law. Because multiple laws could be relevant to a given clearing event, the majority of clearing was still compliant with at least one law, but of these events, only a small proportion was explicitly approved (19%). The remaining were permitted under various exemptions. Of all the legislation we analyzed, most of the exempt clearing occurred under one subnational law and most potentially noncompliant clearing occurred under one national law. Our results showed that even a nation with a suite of mature environmental protection laws is falling well short of achieving international commitments regarding deforestation. Our framework can be used to pinpoint the pathways of policy change required for nations to align local laws with these international accords.

Biodiversity is critical for maintaining ecosystem function but is threatened by increasing anthropogenic pressures. In the Southern Ocean, a highly biologically productive region containing many endemic species, proactive management is urgently needed to mitigate increasing pressures from fishing, climate change, and tourism. Site-based conservation is one important tool for managing the negative impacts of human activities on ecosystems. The Key Biodiversity Area (KBA) Standard is a standardized framework used to define sites vital for the persistence of global biodiversity based on criteria and quantitative thresholds. We used tracking data from 14 species of Antarctic and subantarctic seabirds and pinnipeds from the publicly available Retrospective Analysis of Antarctic Tracking Data (RAATD) data set to define KBAs for a diverse suite of marine predators. We used track2kba, an R package that supports identification of KBAs from telemetry data through identification of highly used habitat areas and estimates of local abundance within sites. We compared abundance estimates at each site with thresholds for KBA criteria A1, B1, and D1 (related to globally threatened species, individual geographically restricted species, and demographic aggregations, respectively). We identified 30 potential KBAs for 13 species distributed throughout the Southern Ocean that were vital for each individual species, population, and life-history stage for which they were determined. These areas were identified as highly used by these populations based on observational data and complement the ongoing habitat modeling and bioregionalization work that has been used to prioritize conservation areas in this region. Although further work is needed to identify potential KBAs based on additional current and future data sets, we highlight the benefits of utilizing KBAs as part of a holistic approach to marine conservation, given their significant value as a global conservation tool.