Conservation Biology最新文献

Indigenous Peoples actively manage or have tenure rights over lands where many rare and valued species occur. To meet national and global conservation targets, it is important to meaningfully consider Indigenous knowledges and rights in endangered species laws. We examined whether the Canadian Species at Risk Act (SARA) has upheld its commitment to consider Indigenous knowledges in decisions pertaining to endangered species assessment. Using data from 823 species status assessments published from 1998 to 2023, we constructed indicators and derived a composite score for 5 tenets of Indigenized models of conservation: those that center Indigenous sovereignty, incorporate place-based knowledges, emphasize interconnectedness, draw from Indigenous knowledge sources, and recognize the cultural importance of species. Over the last quarter century, we found no evidence of improved consideration or inclusion of Indigenous knowledges and science in species status assessments. Although status assessments in northern jurisdictions tended to be better aligned with Indigenized frameworks of conservation, mean composite scores remained low across status assessments (mean = 0.9/5 in 2023). To advance the meaningful consideration of Indigenous Peoples and their knowledges in conservation practices and policies, we recommend honoring endangered species laws' specifications to consider Indigenous knowledges at every step of the process, from species assessment, to increasing capacity, to meaningfully engaging Indigenous Peoples.

Constructed value of information (CVoI) is an expert elicitation decision-analytic tool used to prioritize sources of uncertainty based on their potential to improve decision outcomes if resolved. Despite increased application of CVoI, the robustness of CVoI prioritization of sources of uncertainty relative to differences in expert elicitation and scoring methods has not been evaluated. We engaged a group of species experts in a decision-analytic process to elicit uncertainties, framed as alternative hypotheses, about current population declines of the American kestrel (Falco sparverius) in the United States. Participants scored 13 hypotheses across 3 CVoI criteria, which are defined as constructed scales. Rather than experts selecting a single score per criterion, we used a likelihood point method to incorporate parametric uncertainty in the scoring process, in which experts were given 100 points to distribute across possible score categories within the criterion-specific constructed scale. Experts provided scores over 2 scoring rounds, with an opportunity to review and discuss initial scores between rounds. We used a Shannon entropy calculation to quantify how evenly participants allotted their points. We used simulation to evaluate the robustness of our prioritization results relative to a scoring method in which participants selected a single score category for each criterion. Participants often spread their points across 2 adjacent scores, reflecting parametric uncertainty. For one third of the hypothesis-scoring round combinations, the prioritization results differed in approximately 50% of simulations. The highest scoring hypotheses related to how the use of artificial versus natural nest cavities affects fecundity or survival, whether winter roosting sites are a limiting factor for population growth, and whether gamebird habitat management may benefit kestrel populations. Our CVoI prioritization framework can be used to develop collaborative research that is directly relevant to a management decision and is an advance in eliciting more representative expert beliefs.

The design of experiments to investigate the combined effects of multiple stressors requires exposing target organisms to multiple combinations of stressor doses. Concurrent manipulation of stressors is often infeasible with wildlife, but long-lasting health effects allow individual health to be used as an integrator of prior stressor exposure. The population of bottlenose dolphins in Barataria Bay, Louisiana, experienced long-lasting health effects after exposure to oil from the Deepwater Horizon spill. We investigated whether compromised health status affects dolphins' ability to respond to other stressors, specifically vessel traffic, potentially leading to increased collision risk. We used this case study to develop a hypothesis-driven experimental approach to assess the combined effects of multiple stressors in a large, long-lived vertebrate species. We conducted controlled vessel approaches to test whether the health status of targeted dolphins affected their behavioral responses. Our results highlighted some effects of health, suggesting that oil spills may exacerbate the effects of other stressors in coastal populations. For example, lung disease was associated with a delayed dive response, which could affect the ability to vertically avoid vessels and lead to increased collision risk. However, health effects on response probability were overall smaller than anticipated, and other contextual variables (e.g., sex, age, calf presence, prior experience, and exposure context) contributed to response variability. Our work demonstrated the value of formalizing stressor interactions as multidimensional dose-response functions and showed the feasibility of an experimental, multiple-stressor study in a wild system in which individual health status can be used as an integrator of prior stressor exposure. This approach has broad implications for other species that are difficult to handle experimentally. The quantification and management of the cumulative risk from multiple stressors on wildlife will require a combination of empirical and mechanistic approaches to inform long-term, population consequences.

The delineation of nature by political borders and the restricted accessibility of ecological research data present intertwined challenges to global biodiversity conservation. We examined how the nationalization of biodiversity and the privatization of ecological data hinder effective cross-boundary management of natural resources and perpetuate socioeconomic inequities. The ecological consequences of imposing geopolitical boundaries on species distributions include fragmented management regimes, inconsistent protection across ranges, and misaligned conservation priorities for transboundary populations. Biases inherent in national species assessments lead to systematic misclassification of conservation status, distorted estimates of biodiversity change, and inefficient allocation of conservation resources across borders. The limitations arising from anthropocentric terminology in conservation science can reinforce false native-non-native dichotomies, obscure context-dependent ecological impacts, and undermine transboundary management coherence. We argue that existing conservation frameworks have struggled to address these challenges at scale due to entrenched institutional constraints. As a way forward, we advocate for supranational ecological governance grounded in open-access data, equitable funding, and collaborative frameworks that transcend political boundaries.

Selecting effective surrogate species is essential for improving conservation planning efficiency under limited resources. However, the selection process is often hindered by conceptual ambiguities and inconsistent methodologies. Moreover, most existing studies focus on assessing surrogate species but fail to integrate them into practical spatial conservation planning. We developed a multidimensional effectiveness index (EI) that integrates umbrella, keystone, flagship, and protection dimensions to quantitatively evaluate the conservation potential of mammal species. Applying this framework to 346 mammal species in China, we ranked species by EI and incorporated top-performing subsets into systematic spatial prioritization with Zonation, with condition and cost layers representing climate vulnerability and human pressure, respectively. We assessed surrogate performance across 4 planning scenarios and 10 selection thresholds. Species with high EI scores achieved up to 80% or greater spatial representation based only on the 20-30% of species with the highest EI scores, substantially improving planning efficiency. The resulting priority conservation areas (PCAs) covered approximately 2.69 million km², accounting for ∼28% of China's land area. The PCAs were concentrated in biodiversity hotspots such as the Hengduan Mountains, southeastern Xizang, Yunnan, northeastern China, and Taiwan. Most of China's pilot national parks overlapped with the identified PCAs, underscoring the ecological validity of the framework. This study bridges the gap between species-level assessments and spatial conservation planning. The proposed framework is flexible and broadly applicable, offering a practical tool to optimize surrogate selection and support national and global biodiversity targets.

Following large-scale threatening events, a key challenge is to rapidly establish which species have been most affected and are in need of urgent conservation. For data-poor taxa, such assessments are challenging. In Australia, invertebrates represent over 90% of faunal diversity and are critical for ecosystem function, yet most are undescribed, and, of the described, most are poorly known. Thus, it is important to have a way to estimate susceptibility to major disturbance of data-deficient taxa. We developed a novel trait-based method for assessing the impact of a major wildfire on invertebrates. We applied it to 1220 species that showed high distributional overlap with the 2019-2020 Australian megafires. We estimated susceptibility based on the microhabitat species occupy, their life-history and ecological traits, and mechanisms that account for key data uncertainties (number of usable occurrence records, availability of traits data, and recency of taxonomic work). We found 748 species likely to be of potential conservation concern following the megafires; 169, 579, and 454 were highly, moderately, and mildly threatened by a major fire, respectively. Most species (867) were associated with poor or very poor data quality. Of the 867 poorly known species, 97 were most at risk from a major fire. Our approach is generalizable to other data-deficient taxa and to major disturbance events globally and can be used to improve representation of poorly known species in conservation assessments and threat mitigation decisions. If the uncertainties and knowledge gaps we identified are addressed, it is likely risk prediction could be improved.

Illegal wildlife trade is an important branch of global environmental crime. It relies heavily on transit countries to promote the cross-border movement of illegal wildlife products by boosting markets, laundering services, processing and packaging products, and concealing routes. However, transit countries' strategic role is not well understood. We constructed a dataset of 15 years of illegal wildlife seizure cases from the Center for Advanced Defense Studies (C4ADS) air seizure database and Wildlife Trade Portal database. From the dataset, we determined transnational illegal wildlife trade routes with complete supply chain information. There were 84 transit countries, and the organisms involved in trade included mammals, birds, reptiles, marine species, amphibians, and arthropods. We identified that about 40% of illegal wildlife trade routes crossed one or multiple countries. Species being moved along these routes originated mainly from Africa and were transported through African, European, or Asian countries to East Asia or Southeast Asia. Transit countries for illegal wildlife products tended to be geographically close to and have a high trade volume of legal biological products with both the origin and destination countries and had advanced airport infrastructure. Transit countries were associated with 39.7% more individual animal products being illegally traded, particularly ivory, pangolin products, and rhinoceros horn, and served as key bridges among economically underdeveloped and geographically distant countries with weak trade links in legal biological products. These findings highlight the importance of monitoring and enforcement in transit countries and suggest that transit hubs be targeted based on location, trade in legal biological products, and transport infrastructure.

Human development is a driver of global change and a major threat to biodiversity. Protected areas maintain and support biodiversity, but outside stressors, such as climate change and land use change, can negatively influence natural resources within protected areas. We examined the effects of land surface temperature and the surrounding landscape context on the structure and composition of the breeding bird community in national parks in the Mid-Atlantic (USA). We used avian point count surveys, conducted annually from 2007 to 2024, to estimate the composition of 16 avian guilds and estimated land surface temperature at each survey point. We defined 3 landscape context types (forested, urban, and agricultural) based on the dominant land cover surrounding each survey point. We used multivariate generalized linear models to test community-level (all guilds combined) and guild-level (individual guilds) responses to local land surface temperature and landscape context. We hypothesized a negative relationship between within-guild abundance and land surface temperature, and stronger negative relationships in specialist guilds and variation in response based on the landscape context. Landscape context influenced local land surface temperature and, therefore, avian guild responses. Points in forest-dominated landscapes averaged 2°C cooler than points in urban or agricultural landscapes. The majority of specialist guilds had an interaction with land surface temperature and landscape context. There were negative effects of high land surface temperature on the bird community. These effects differed across landscape context, with less extreme negative relationships detected at points surrounded by forest relative to points in urban or agricultural landscapes. Because increased forest cover is important to retain natural cooling and mitigate the effects of urban heat, preserving or increasing forest cover could help preserve and maintain bird community resilience in a warming climate.

Persistent demand for wildlife-derived products perpetuates international trafficking and the exploitation of legitimate globalized transport networks. The annual movement of millions of shipping cargo containers, of which few are inspected due to resource constraints, facilitates the smuggling of large quantities of wildlife contraband. Rapid, noninvasive screening tools are essential for border control agencies to effectively detect and intercept wildlife trafficking attempts, though such tools are currently limited. Detection dog programs could be highly effective in this context; however, their capacity to screen large volumes of cargo without disrupting port operations remains a challenge. We explored the feasibility of pairing an air extraction device, which samples air from sealed containers, with canine detection to improve screening measures. To evaluate this method, we used pelts from adult specimens of the African lion (Panthera leo), cheetah (Acinonyx jubatus), leopard (Panthera pardus), snow leopard (Panthera uncia), and tiger (Panthera tigris) concealed in containers to simulate smuggling scenarios. On average across the container configurations trialed, the detection dog achieved high diagnostic sensitivity (97.6%, 95% CI 95.1-100.0) and specificity (84.8%, 95% CI 79.1-90.6). Detection accuracy was not significantly influenced by airflow conditions (extraction only vs. mixed-mode ventilation) or pelt arrangement within the containers. These findings highlight the potential of this approach in enhancing the detection of concealed wildlife products. However, the air extraction protocol must be validated under real-world operational conditions to confirm its practicability. Through the integration of extraction-based air sampling into existing screening frameworks, this approach could offer a scalable, noninvasive strategy to strengthen wildlife trafficking detection.