Conservation Biology最新文献

Several legal acts mandate that management agencies regularly assess biological populations. For species with distinct markings, these assessments can be conducted noninvasively via capture-recapture and photographic identification (photo-ID), which involves processing considerable quantities of photographic data. To ease this burden, agencies increasingly rely on automated identification (ID) algorithms. Identification algorithms present agencies with an opportunity-reducing the cost of population assessments-and a challenge-propagating misidentifications into abundance estimates at a large scale. We explored several strategies for generating capture histories with an ID algorithm, evaluating trade-offs between labor costs and estimation error in a hypothetical population assessment. To that end, we conducted a simulation study informed by 39 photo-ID datasets representing 24 cetacean species. We fed the results into a custom optimization tool to discern the optimal strategy for each dataset. Our strategies included choosing between truly and partially automated photo-ID and, in the case of the latter, choosing the number of suggested matches to inspect. True automation was optimal for datasets for which the algorithm identified individuals well. As identification performance declined, the optimization recommended that users inspect more suggested matches from the ID algorithm, particularly for small datasets. False negatives (i.e., individual was resighted but erroneously marked as a first capture) strongly predicted estimation error. A 2% increase in the false negative rate translated to a 5% increase in the relative bias in abundance estimates. Our framework can be used to estimate expected error of the abundance estimate, project labor effort, and find the optimal strategy for a dataset and algorithm. We recommend estimating a strategy's false negative rate before implementing the strategy in a population assessment. Our framework provides organizations with insights into the conservation benefits and consequences of automation as conservation enters a new era of artificial intelligence for population assessments.

Survival and cause-specific mortality rates are vital for evidence-based population forecasting and conservation, particularly for large carnivores, whose populations are often vulnerable to human-caused mortalities. It is therefore important to know the relationship between anthropogenic and natural mortality causes to evaluate whether they are additive or compensatory. Further, the relation between survival and environmental covariates could reveal whether specific landscape characteristics influence demographic performance. We used telemetry data on 681 Eurasian lynx (Lynx lynx), a model apex predator with large spatial requirements, that were tracked across their European distribution. Through time-to-event analyses, we sought to determine the variables associated with differences in their survival. Illegal killing was the main cause of mortality (33.8%), and mortality rates were similar in protected and hunted populations (8.6% and 7.0% per year, respectively). Survival varied greatly across populations (70-95% per year). Across all study sites, higher hunting and anthropogenic mortality rates were partially compensated by lower rates of other mortality causes but not by natural mortality alone. Variation in survival depended on sex (female survival was 1.5 times greater than male survival) and seasonality (highest risk during hunting season and winter), and lower survival rates were correlated with higher human modification of landscapes at both coarse (home range composition) and fine (habitat use within home range) scales. Some variation in survival was driven by unobserved factors, which, given the high rates of human-caused mortalities, including illegal killing, are of foremost concern. Due to the low natural mortality rates in protected and hunted populations, we conclude that anthropogenic causes of mortality are likely close to additive, such that maintaining or increasing refuge habitat with little human disturbance is critical to lynx conservation.

Marine protected areas (MPAs) are widely implemented tools for long-term ocean conservation and resource management. Assessments of MPA performance have largely focused on specific ecosystems individually and have rarely evaluated performance across multiple ecosystems either in an individual MPA or across an MPA network. We evaluated the conservation performance of 59 MPAs in California's large MPA network, which encompasses 4 primary ecosystems (surf zone, kelp forest, shallow reef, deep reef) and 4 bioregions, and identified MPA attributes that best explain performance. Using a meta-analytic framework, we evaluated the ability of MPAs to conserve fish biomass, richness, and diversity. At the scale of the network and for 3 of 4 regions, the biomass of species targeted by fishing was positively associated with the level of regulatory protection and was greater inside no-take MPAs, whereas species not targeted by fishing had similar biomass in MPAs and areas open to fishing. In contrast, species richness and diversity were not as strongly enhanced by MPA protection. The key features of conservation effectiveness included MPA age, preimplementation fisheries pressure, and habitat diversity. Important drivers of MPA effectiveness for single MPAs were consistent across MPAs in the network, spanning regions and ecosystems. With international targets aimed at protecting 30% of the world's oceans by 2030, MPA design and assessment frameworks should consider conservation performance at multiple ecologically relevant scales, from individual MPAs to MPA networks.

Ecosystems globally have reached critical tipping points because of climate change, urbanization, unsustainable resource consumption, and pollution. In response, international agreements have set targets for conserving 30% of global ecosystems and restoring 30% of degraded lands and waters by 2030 (30×30). In 2021, the United States set a target to jointly conserve and restore 30% of US lands and waters by 2030, with a specific goal to restore coastal ecosystems, namely wetlands, seagrasses, coral and oyster reefs, and mangrove and kelp forests, to increase resilience to climate change. Although US efforts to conserve and restore coastal ecosystems have increased in recent decades, critical knowledge gaps about the effectiveness of past and current efforts remain. To address key knowledge gaps, we first collated information on current and historic extent and drivers of change for wetlands, seagrasses, coral and oyster reefs, and mangrove and kelp forests in the United States. We then synthesized guiding principles from the literature for restoration practitioners to evaluate ecosystem trade-offs, sustain and enhance ecosystem connectivity, bolster climate resilience, and promote social equity. Significant investment in standardized ecosystem mapping and monitoring and multispecies, landscape-scale restoration efforts can improve resilience of coastal ecosystems to climate change and help the United States achieve its 30×30 target.

Identifying and assessing the magnitude of direct threats to ecosystems and species are critical steps to prioritizing, planning, implementing, and assessing conservation actions. Just as medical clinicians and researchers need a standard way to talk about human diseases, conservation practitioners and scientists need a common and comprehensive language to talk about the threats they are facing to facilitate joint action, evaluation, and learning. To meet this need, in 2008 the IUCN Species Survival Commission and the Conservation Measures Partnership produced the first version of a common threats classification with the understanding that it would be periodically updated to take into account new information and learning. We present version 4.0 of this classification. For this latest update, we reviewed existing versions and derivatives of the original classification, over 1000 citations of the classification, threats data from over 2900 real-world conservation projects, and comments from many users. Based on our findings, we made changes to the threats classification scheme, including addition of a level 0 threat class, refinement of levels 1 and 2 threat categories, and addition of the threat "Fencing & walls" to level 2. Also added were level 3 threat types and modifiers that provide a more detailed description of different types of direct threats and thus allow users to fine-tune analyses and actions. The update also clarifies how to treat various stressors, including natural disaster events and climate change. As a result of these changes, we revised the formal definition of direct threats. They include human actions that are the direct cause of ecosystem or species-population degradation and loss, such as agriculture, transport, natural resource use, and ecosystem management. They also include ultimate stressors in natural systems whose dynamics have been altered by the effects of current or historical human actions, such as invasive or problematic native species, pollution, natural disasters, and climate change.

Action-oriented conservation sciences are crippled by 3 false assumptions. First, although it is recognized in theory that natural and anthropic components of ecosystems are tightly intertwined, in practice, many conservation policies and actions are still based on the assumption that human and nonhuman stakes should be dealt with in deeply different ways. Second, although the anchorage of environmental sciences in values is amply demonstrated, many conservation scientists still assume they will lose their scientific credentials if they actively participate in decision-making. Finally, although there is much scientific evidence of the permeability-to both protected entities and threats-of static geographic frontiers delimiting protected areas, many conservation policies are still based on the assumption that these frontiers in themselves produce relevant protections. To overcome these false assumptions, it is useful to articulate them in terms of frontiers based on 2 ideas associated with the term. As a synonym of border, frontier materializes a limit whose crossing can have high stakes. As used in phrases such as frontiers of knowledge, the term also refers to the ever-moving horizon of what should be overcome. These 2 ideas capture the reasons current attempts at overcoming the 3 assumptions remain unsatisfactory. They are also useful for elaborating a new vision of conservation to simultaneously break from the 3 assumptions. Instead of taking fixed geographic frontiers of protected areas for granted, conservation scientists should participate, along with stakeholders and Indigenous peoples, in the collective identification of the conservation problems that need to be addressed. For these problems, decision committees that include representatives of concerned humans and representatives of concerned nonhumans should be formed to determine the temporal and spatial scope of relevant conservation actions. The result would be multidimensional protected areas dynamically fine-tuned to the conservation issues they address and to changing environmental conditions.

Mangrove area loss is increasing globally, and drivers of loss differ depending not only on natural conditions but also on national and regional policies. Some countries with the most mangrove area, for instance, Brazil, lack broad systematic quantification of specific drivers of mangrove land-use and land-cover (LULC) change dynamics. We investigated the direct conversion (i.e., replacement) of mangrove forests due to changes in 21 types of LULC across Brazil from 2000 to 2020 based on annual LULC maps developed by the MapBiomas project. We quantified the area changes at national, regional, and state scales. We also determined and quantified mangrove forest conversion for each of the 21 LULC types with a pixel comparison analysis and identified temporal trends with a time-series analysis. The total conversion of mangrove area (3429 km²) was offset by a gain that was twice as large (6776 km²). Forest formations and water bodies, which may be interpreted as natural or indirect anthropogenic changes, were associated with most of the areas where mangrove cover was lost. Land-use modifications, mainly creation of pastures, accounted for 4% of direct mangrove conversions. We found that changes in LULC categories and patterns of gain and loss of mangrove areas differed among Brazilian states and regions. Based on other research, they also differ between Brazil and other countries. Thus, integrated mangrove forest conservation and management efforts that transcend political boundaries are essential to effectively address negative impacts on mangrove forests. We provide an interactive map to allow qualitative assessments of mangrove conversion drivers by different stakeholders, such as managers, policymakers, and nongovernmental organizations.

Habitat loss and fragmentation have independent impacts on biodiversity; thus, field studies are needed to distinguish their impacts. Moreover, species with different locomotion rates respond differently to fragmentation, complicating direct comparisons of the effects of habitat loss and fragmentation across differing taxa and landscapes. To overcome these challenges, we combined mechanistic mathematical modeling and laboratory experiments to compare how species with different locomotion rates were affected by low (∼80% intact) and high (∼30% intact) levels of habitat loss. In our laboratory experiment, we used Caenorhabditis elegans strains with different locomotion rates and subjected them to the different levels of habitat loss and fragmentation by placing Escherichia coli (C. elegans food) over different proportions of the Petri dish. We developed a partial differential equation model that incorporated spatial and biological phenomena to predict the impacts of habitat arrangement on populations. Only species with low rates of locomotion declined significantly in abundance as fragmentation increased in areas with low (p = 0.0270) and high (p = 0.0243) levels of habitat loss. Despite that species with high locomotion rates changed little in abundance regardless of the spatial arrangement of resources, they had the lowest abundance and growth rates in all environments because the negative effect of fragmentation created a mismatch between the population distribution and the resource distribution. Our findings shed new light on incorporating the role of locomotion in determining the effects of habitat fragmentation.