Balancing making a difference with making a living in the conservation sector

Goals play important roles in people's lives because they focus attention, mobilize effort, and sustain motivation. Understanding conservationists’ satisfaction with goal progress may provide insights into real-world environmental trends and flag risks to their well-being and motivation. We asked 2694 conservationists working globally how satisfied they were with progress toward goals important to them. We then explored how this satisfaction varied among groups, including demographic and occupational. Finally, we looked at respondents' experiences associated with goal-progress satisfaction. Many (94.0%) indicated that making a meaningful contribution to conservation was an important goal for them, and over half were satisfied or very satisfied in this area (52.5%). However, respondents were generally dissatisfied with progress on collective conservation goals (e.g., stopping species loss). Some groups were more likely to report dissatisfaction than others. For instance, those in conservation for longer tended to be less satisfied with collective goal progress (log odds –0.21, 95% credibility interval [CI] –0.32 to –0.10), but practitioners reported greater satisfaction (log odds 0.38, 95% CI 0.15–0.60). Likewise, those who were more optimistic in life (log odds 0.24, 95% CI 0.17–0.32), male (log odds 0.25, 95% CI 0.10–0.41), and working in conservation practice (log odds 0.25, 95% CI 0.08–0.43) reported greater satisfaction with individual goal progress. Free-text responses suggested widespread dissatisfaction with livelihood goals, particularly related to job security and adequate compensation. Although contributing to conservation appeared to be a source of satisfaction, slow goal progress in other areas––particularly around making a living––looked to be a source of distress and demotivation. Employers, funders, professional societies, and others should consider ways to help those in the sector make a difference while making a satisfactory living by, for example, prioritizing conservationists′ well-being when allocating funding. This support could include avoiding exploitative practices, fostering supportive work environments, and celebrating positive outcomes.     

Abundance of small cetaceans in waters of the central Spanish Mediterranean

Seasonal aerial surveys were conducted in the waters of the central Spanish Mediterranean from 2001 to 2003 using the line transect sampling methodology to estimate cetacean abundance. The density of the three most abundant species, striped dolphin (Stenella coeruleoalba), bottlenose dolphin (Tursiops truncatus) and Risso’s dolphins (Grampus griseus), was estimated. In the case of the first two species, the density was estimated accounting for the proportion of submerged animals, while for Risso’s dolphin only the surface density could be estimated. The striped dolphin was the most abundant species in the study area with a mean density of 0.489 dolphins km⁻² (95% CI = 0.339–0.705) and a mean abundance of 15,778 dolphins (95% CI = 10,940–22,756). This density is comparable to that obtained in the International Ligurian Sea Cetacean Sanctuary. Striped dolphins were observed throughout the whole year and no seasonal changes in the density were detected. The mean density of bottlenose dolphins was an order of magnitude lower than that of striped dolphins (0.041 dolphins km⁻²; 95% CI = 0.023–0.075) with a mean abundance of 1,333 dolphins (95% CI = 739–2,407). The Risso’s dolphin had a surface estimated density of 0.015 dolphins km⁻² (95% CI = 0.005–0.046) and a mean abundance of 493 dolphins (95% CI = 162–1,498). These results provide valuable biological information useful to develop conservation plans and establish a baseline for future population trend studies.     

Improving protected area effectiveness through consideration of different human-pressure baselines

Previous assessments of the effectiveness of protected areas (PAs) focused primarily on changes in human pressure over time and did not consider the different human-pressure baselines of PAs, thereby potentially over- or underestimating PA effectiveness. We developed a framework that considers both human-pressure baseline and change in human pressure over time and assessed the effectiveness of 338 PAs in China from 2010 to 2020. The initial state of human pressure on PAs was taken as the baseline, and changes in human pressure index (HPI) were further analyzed under different baselines. We used the random forest models to identify the management measures that most improved effectiveness in resisting human pressure for the PAs with different baselines. Finally, the relationships between the changes in the HPI and the changes in natural ecosystems in PAs were analyzed with different baselines. Of PAs with low HPI baselines, medium HPI baselines, and high HPI baselines, 76.92% (n=150), 11.11% (n=12), and 22.86% (n=8) , respectively, showed positive effects in resisting human pressure. Overall, ignoring human-pressure baselines somewhat underestimated the positive effects of PAs, especially for those with low initial human pressure. For PAs with different initial human pressures, different management measures should be taken to improve effectiveness and reduce threats to natural ecosystems. We believe our framework is useful for assessing the effectiveness of PAs globally, and we recommend it be included in the Convention on Biological Diversity Post-2020 Strategy.     

A counterfactual approach to measure the impact of wet grassland conservation on U.K. breeding bird populations

Wet grassland populations of wading birds in the United Kingdom have declined severely since 1990. To help mitigate these declines, the Royal Society for the Protection of Birds has restored and managed lowland wet grassland nature reserves to benefit these and other species. However, the impact of these reserves on bird population trends has not been evaluated experimentally due to a lack of control populations. We compared population trends from 1994 to 2018 among 5 bird species of conservation concern that breed on these nature reserves with counterfactual trends created from matched breeding bird survey observations. We compared reserve trends with 3 different counterfactuals based on different scenarios of how reserve populations could have developed in the absence of conservation. Effects of conservation interventions were positive for all 4 targeted wading bird species: Lapwing (Vanellus vanellus), Redshank (Tringa totanus), Curlew (Numenius arquata), and Snipe (Gallinago gallinago). There was no positive effect of conservation interventions on reserves for the passerine, Yellow Wagtail (Motacilla flava). Our approach using monitoring data to produce valid counterfactual controls is a broadly applicable method allowing large-scale evaluation of conservation impact.     

Comparing wildlife habitat suitability models based on expert opinion with camera trap detections

Expert knowledge is used in the development of wildlife habitat suitability models (HSMs) for management and conservation decisions. However, the consistency of such models has been questioned. Focusing on 1 method for elicitation, the analytic hierarchy process, we generated expert-based HSMs for 4 felid species: 2 forest specialists (ocelot [Leopardus pardalis] and margay [Leopardus wiedii]) and 2 habitat generalist species (Pampas cat [Leopardus colocola] and puma [Puma concolor]). Using these HSMs, species detections from camera-trap surveys, and generalized linear models, we assessed the effect of study species and expert attributes on the correspondence between expert models and camera-trap detections. We also examined whether aggregation of participant responses and iterative feedback improved model performance. We ran 160 HSMs and found that models for specialist species showed higher correspondence with camera-trap detections (AUC [area under the receiver operating characteristic curve] >0.7) than those for generalists (AUC < 0.7). Model correspondence increased as participant years of experience in the study area increased, but only for the understudied generalist species, Pampas cat (β = 0.024 [SE 0.007]). No other participant attribute was associated with model correspondence. Feedback and revision of models improved model correspondence, and aggregating judgments across multiple participants improved correspondence only for specialist species. The average correspondence of aggregated judgments increased as group size increased but leveled off after 5 experts for all species. Our results suggest that correspondence between expert models and empirical surveys increases as habitat specialization increases. We encourage inclusion of participants knowledgeable of the study area and model validation for expert-based modeling of understudied and generalist species.     

Optimizing conservation in species-specific agricultural landscapes

Recovery of grassland birds in agricultural landscapes is a global imperative. Agricultural landscapes are complex, and the value of resource patches may vary substantially among species. The spatial extent at which landscape features affect populations (i.e., scale of effect) may also differ among species. There is a need for regional-scale conservation planning that considers landscape-scale and species-specific responses of grassland birds to environmental change. We developed a spatially explicit approach to optimizing grassland conservation in the context of species-specific landscapes and prioritization of species recovery and applied it to a conservation program in Kentucky (USA). We used a hierarchical distance-sampling model with an embedded scale of effect predictor to estimate the relationship between landscape structure and abundance of eastern meadowlarks (Sturnella magna), field sparrows (Spizella pusilla), and northern bobwhites (Colinus virginianus). We used a novel spatially explicit optimization procedure rooted in multi-attribute utility theory to design alternative conservation strategies (e.g., prioritize only northern bobwhite recovery or assign equal weight to each species’ recovery). Eastern meadowlarks and field sparrows were more likely to respond to landscape-scale resource patch adjacencies than landscape-scale patch densities. Northern bobwhite responded to both landscape-scale resource patch adjacencies and densities and responded strongly to increased grassland density. Effects of landscape features on local abundance decreased as distance increased and had negligible influence at 0.8 km for eastern meadowlarks (0.7–1.2 km 95% Bayesian credibility intervals [BCI]), 2.5 km for field sparrows (1.5–5.8 km 95% BCI), and 8.4 km for bobwhite (6.4–26 km 95% BCI). Northern bobwhites were predicted to benefit greatly from future grassland conservation regardless of conservation priorities, but eastern meadowlark and field sparrow were not. Our results suggest similar species can respond differently to broad-scale conservation practices because of species-specific, distance-dependent relationships with landscape structure. Our framework is quantitative, conceptually simple, customizable, and predictive and can be used to optimize conservation in heterogeneous ecosystems while considering landscape-scale processes and explicit prioritization of species recovery.     

Meta-analysis of the effects of upstream land cover on stream recovery

Unpredictable or variable ecosystem recovery from disturbance presents a challenge to conservation, particularly as the scale of human disturbance continues to increase. Theory suggests land-cover and disturbance characteristics affect recovery, but individual studies of disturbance and recovery frequently struggle to uncover generalizable patterns because of high levels of site-specific variation. To understand how land-cover, disturbance type, and disturbance duration influence ecosystem recovery, we used studies documenting recovery of 50 streams to perform a global meta-analysis of stream recovery from disturbances that affect water quality (e.g., oil spill, fire, wastewater). We extracted upstream natural and urban land-cover percentages for each site and performed model selection and averaging to identify influences on recovery completeness. Most streams improved following the end of a disturbance (median 240% of disturbed condition) but did not recover fully to baseline predisturbance condition within the studied period (median study period 2 years; median recovery 60% of baseline). Scale of disturbance in time and space did not predict recovery, but sites with higher percentages of upstream natural land cover had less complete recovery relative to sites with more urban or agricultural cover, possibly due to higher baseline conditions in these streams. Our findings suggest impacts to systems with low anthropogenic stress may be more irreversible than impacts to already modified systems. We call for more long-term evaluations of ecosystem response to disturbance and the inclusion of regional references and predisturbance reference conditions for comparison. A more thorough understanding of the role of the surrounding landscape in shaping stream response to disturbance can help managers calibrate expectations for recovery and prioritize protection.     

Eliciting expert knowledge in conservation science

Expert knowledge is used widely in the science and practice of conservation because of the complexity of problems, relative lack of data, and the imminent nature of many conservation decisions. Expert knowledge is substantive information on a particular topic that is not widely known by others. An expert is someone who holds this knowledge and who is often deferred to in its interpretation. We refer to predictions by experts of what may happen in a particular context as expert judgments. In general, an expert-elicitation approach consists of five steps: deciding how information will be used, determining what to elicit, designing the elicitation process, performing the elicitation, and translating the elicited information into quantitative statements that can be used in a model or directly to make decisions. This last step is known as encoding. Some of the considerations in eliciting expert knowledge include determining how to work with multiple experts and how to combine multiple judgments, minimizing bias in the elicited information, and verifying the accuracy of expert information. We highlight structured elicitation techniques that, if adopted, will improve the accuracy and information content of expert judgment and ensure uncertainty is captured accurately. We suggest four aspects of an expert elicitation exercise be examined to determine its comprehensiveness and effectiveness: study design and context, elicitation design, elicitation method, and elicitation output. Just as the reliability of empirical data depends on the rigor with which it was acquired so too does that of expert knowledge.     

Nonadditive effects among threats on rare plant species

The current loss of biodiversity has put 50,000 plant species at an elevated risk of extinction worldwide. Conserving at-risk species is often complicated by covariance or nonadditivity among threats, which makes it difficult to determine optimal management strategies. We sought to demographically quantify covariance and nonadditive effects of more threats on more rare plant species than ever attempted in a single analysis. We used 1082 population reports from 186 populations across 3 U.S. states of 27 rare, herbaceous plant species collected over 15 years by citizen scientists. We used a linear mixed-effects model with 4 threats and their interactions as fixed predictors, species as a random predictor, and annual growth rates as the response. We found a significant 3-way interaction on annual growth rates; rare plant population sizes were reduced by 46% during the time immediately after disturbance when populations were also browsed by deer (Odocoileus virginianus) and had high levels of encroachment by woody species. This nonadditive effect should be considered a major threat to the persistence of rare plant species. Our results highlight the need for comprehensive, multithreat assessments to determine optimal conservation actions.     

A stochastic model for estimating sustainable limits to wildlife mortality in a changing world

Human-caused mortality of wildlife is a pervasive threat to biodiversity. Assessing the population-level impact of fisheries bycatch and other human-caused mortality of wildlife has typically relied upon deterministic methods. However, population declines are often accelerated by stochastic factors that are not accounted for in such conventional methods. Building on the widely applied potential biological removal (PBR) equation, we devised a new population modeling approach for estimating sustainable limits to human-caused mortality and applied it in a case study of bottlenose dolphins affected by capture in an Australian demersal otter trawl fishery. Our approach, termed sustainable anthropogenic mortality in stochastic environments (SAMSE), incorporates environmental and demographic stochasticity, including the dependency of offspring on their mothers. The SAMSE limit is the maximum number of individuals that can be removed without causing negative stochastic population growth. We calculated a PBR of 16.2 dolphins per year based on the best abundance estimate available. In contrast, the SAMSE model indicated that only 2.3–8.0 dolphins could be removed annually without causing a population decline in a stochastic environment. These results suggest that reported bycatch rates are unsustainable in the long term, unless reproductive rates are consistently higher than average. The difference between the deterministic PBR calculation and the SAMSE limits showed that deterministic approaches may underestimate the true impact of human-caused mortality of wildlife. This highlights the importance of integrating stochasticity when evaluating the impact of bycatch or other human-caused mortality on wildlife, such as hunting, lethal control measures, and wind turbine collisions. Although population viability analysis (PVA) has been used to evaluate the impact of human-caused mortality, SAMSE represents a novel PVA framework that incorporates stochasticity for estimating acceptable levels of human-caused mortality. It offers a broadly applicable, stochastic addition to the demographic toolbox to evaluate the impact of human-caused mortality on wildlife.     

Scaling up private land conservation to meet recovery goals for grassland birds

Long-term population declines have elevated recovery of grassland avifauna to among the highest conservation priorities in North America. Because most of the Great Plains is privately owned, recovery of grassland bird populations depends on voluntary conservation with strong partnerships between private landowners and resource professionals. Despite large areas enrolled in voluntary practices through U.S. Department of Agriculture's Lesser Prairie-chicken (Tympanuchus pallidicinctus) Initiative (LPCI), the effectiveness of Farm Bill investments for meeting wildlife conservation goals remains an open question. Our objectives were to evaluate extents to which Conservation Reserve Program (CRP) and LPCI-grazing practices influence population densities of grassland birds; estimate relative contributions of practices to regional bird populations; and evaluate percentages of populations conserved relative to vulnerability of species. We designed a large-scale impact-reference study and used the Integrated Monitoring in Bird Conservation Regions program to evaluate bird population targets of the Playa Lakes Joint Venture. We used point transect distance sampling to estimate density and population size for 35 species of grassland birds on private lands enrolled in native or introduced CRP plantings and LPCI-prescribed grazing. Treatment effects indicated CRP plantings increased densities of three grassland obligates vulnerable to habitat loss, and LPCI grazing increased densities of four species requiring heterogeneity in dense, tall-grass structure (α = 0.1). Population estimates in 2016 indicated the practices conserved breeding habitat for 4.5 million birds (90% CI: 4.0–5.1), and increased population sizes of 16 species , totaling 1.8 million birds (CI: 1.4–2.4). Conservation practices on private land benefited the most vulnerable grassland obligate species (AIC_c weight = 0.53). By addressing habitat loss and degradation in agricultural landscapes, conservation on private land provides a solution to declining avifauna of North America and scales up to meet population recovery goals for the most imperiled grassland birds.     

Use of opportunistic sightings and expert knowledge to predict and compare Whooping Crane stopover habitat

Predicting a species’ distribution can be helpful for evaluating management actions such as critical habitat designations under the U.S. Endangered Species Act or habitat acquisition and rehabilitation. Whooping Cranes (Grus americana) are one of the rarest birds in the world, and conservation and management of habitat is required to ensure their survival. We developed a species distribution model (SDM) that could be used to inform habitat management actions for Whooping Cranes within the state of Nebraska (U.S.A.). We collated 407 opportunistic Whooping Crane group records reported from 1988 to 2012. Most records of Whooping Cranes were contributed by the public; therefore, developing an SDM that accounted for sampling bias was essential because observations at some migration stopover locations may be under represented. An auxiliary data set, required to explore the influence of sampling bias, was derived with expert elicitation. Using our SDM, we compared an intensively managed area in the Central Platte River Valley with the Niobrara National Scenic River in northern Nebraska. Our results suggest, during the peak of migration, Whooping Crane abundance was 262.2 (90% CI 40.2?3144.2) times higher per unit area in the Central Platte River Valley relative to the Niobrara National Scenic River. Although we compared only 2 areas, our model could be used to evaluate any region within the state of Nebraska. Furthermore, our expert‐informed modeling approach could be applied to opportunistic presence‐only data when sampling bias is a concern and expert knowledge is available.     

Using expert knowledge to support Endangered Species Act decision-making for data-deficient species

Many questions relevant to conservation decision-making are characterized by extreme uncertainty due to lack of empirical data and complexity of the underlying ecologic processes, leading to a rapid increase in the use of structured protocols to elicit expert knowledge. Published ecologic applications often employ a modified Delphi method, where experts provide judgments anonymously and mathematical aggregation techniques are used to combine judgments. The Sheffield elicitation framework (SHELF) differs in its behavioral approach to synthesizing individual judgments into a fully specified probability distribution for an unknown quantity. We used the SHELF protocol remotely to assess extinction risk of three subterranean aquatic species that are being considered for listing under the U.S. Endangered Species Act. We provided experts an empirical threat assessment for each known locality over a video conference and recorded judgments on the probability of population persistence over four generations with online submission forms and R-shiny apps available through the SHELF package. Despite large uncertainty for all populations, there were key differences between species’ risk of extirpation based on spatial variation in dominant threats, local land use and management practices, and species’ microhabitat. The resulting probability distributions provided decision makers with a full picture of uncertainty that was consistent with the probabilistic nature of risk assessments. Discussion among experts during SHELF's behavioral aggregation stage clearly documented dominant threats (e.g., development, timber harvest, animal agriculture, and cave visitation) and their interactions with local cave geology and species’ habitat. Our virtual implementation of the SHELF protocol demonstrated the flexibility of the approach for conservation applications operating on budgets and time lines that can limit in-person meetings of geographically dispersed experts.     

Assessing conservation status with extensive but low-resolution data: Application of frequentist and Bayesian models to endangered Athabasca River rainbow trout

Use of extensive but low-resolution abundance data is common in the assessment of species at-risk status based on quantitative decline criteria under International Union for Conservation of Nature (IUCN) and national endangered species legislation. Such data can be problematic for 3 reasons. First, statistical power to reject the null hypothesis of no change is often low because of small sample size and high sampling uncertainty leading to a high frequency of type II errors. Second, range-wide assessments composed of multiple site-specific observations do not effectively weight site-specific trends into global trends. Third, uncertainty in site-specific temporal trends and relative abundance are not propagated at the appropriate spatial scale. A common result is the propensity to underestimate the magnitude of declines and therefore fail to identify the appropriate at-risk status for a species. We used 3 statistical approaches, from simple to more complex, to estimate temporal decline rates for a designatable unit (DU) of rainbow trout in the Athabasca River watershed in western Canada. This DU is considered a native species for purposes of listing because of its genetic composition characterized as >0.95 indigenous origin in the face of continuing introgressive hybridization with introduced populations in the watershed. Analysis of abundance trends from 57 time series with a fixed-effects model identified 33 sites with negative trends, but only 2 were statistically significant. By contrast, a hierarchical linear mixed model weighted by site-specific abundance provided a DU-wide decline estimate of 16.4% per year and a 3-generation decline of 93.2%. A hierarchical Bayesian mixed model yielded a similar 3-generation decline trend of 91.3% and the posterior distribution showed that the estimate had a >99% probability of exceeding thresholds for an endangered listing. We conclude that the Bayesian approach was the most useful because it provided a probabilistic statement of threshold exceedance in support of an at-risk status recommendation.     

Validating graph-based connectivity models with independent presence–absence and genetic data sets

Habitat connectivity is a key objective of current conservation policies and is commonly modeled by landscape graphs (i.e., sets of habitat patches [nodes] connected by potential dispersal paths [links]). These graphs are often built based on expert opinion or species distribution models (SDMs) and therefore lack empirical validation from data more closely reflecting functional connectivity. Accordingly, we tested whether landscape graphs reflect how habitat connectivity influences gene flow, which is one of the main ecoevolutionary processes. To that purpose, we modeled the habitat network of a forest bird (plumbeous warbler [Setophaga plumbea]) on Guadeloupe with graphs based on expert opinion, Jacobs’ specialization indices, and an SDM. We used genetic data (712 birds from 27 populations) to compute local genetic indices and pairwise genetic distances. Finally, we assessed the relationships between genetic distances or indices and cost distances or connectivity metrics with maximum-likelihood population-effects distance models and Spearman correlations between metrics. Overall, the landscape graphs reliably reflected the influence of connectivity on population genetic structure; validation R² was up to 0.30 and correlation coefficients were up to 0.71. Yet, the relationship among graph ecological relevance, data requirements, and construction and analysis methods was not straightforward because the graph based on the most complex construction method (species distribution modeling) sometimes had less ecological relevance than the others. Cross-validation methods and sensitivity analyzes allowed us to make the advantages and limitations of each construction method spatially explicit. We confirmed the relevance of landscape graphs for conservation modeling but recommend a case-specific consideration of the cost-effectiveness of their construction methods. We hope the replication of independent validation approaches across species and landscapes will strengthen the ecological relevance of connectivity models.     

Applying science to pressing conservation needs for penguins

More than half of the world's 18 penguin species are declining. We, the Steering Committee of the International Union for Conservation of Nature Species Survival Commission Penguin Specialist Group, determined that the penguin species in most critical need of conservation action are African penguin (Spheniscus demersus), Galápagos penguin (Spheniscus mendiculus), and Yellow-eyed penguin (Megadyptes antipodes). Due to small or rapidly declining populations, these species require immediate scientific collaboration and policy intervention. We also used a pairwise-ranking approach to prioritize research and conservation needs for all penguins. Among the 12 cross-taxa research areas we identified, we ranked quantifying population trends, estimating demographic rates, forecasting environmental patterns of change, and improving the knowledge of fisheries interactions as the highest priorities. The highest ranked conservation needs were to enhance marine spatial planning, improve stakeholder engagement, and develop disaster-management and species-specific action plans. We concurred that, to improve the translation of science into effective conservation for penguins, the scientific community and funding bodies must recognize the importance of and support long-term research; research on and conservation of penguins must expand its focus to include the nonbreeding season and juvenile stage; marine reserves must be designed at ecologically appropriate spatial and temporal scales; and communication between scientists and decision makers must be improved with the help of individual scientists and interdisciplinary working groups.     

A global community-sourced assessment of the state of conservation technology

Conservation technology holds the potential to vastly increase conservationists’ ability to understand and address critical environmental challenges, but systemic constraints appear to hamper its development and adoption. Understanding of these constraints and opportunities for advancement remains limited. We conducted a global online survey of 248 conservation technology users and developers to identify perceptions of existing tools’ current performance and potential impact, user and developer constraints, and key opportunities for growth. We also conducted focus groups with 45 leading experts to triangulate findings. The technologies with the highest perceived potential were machine learning and computer vision, eDNA and genomics, and networked sensors. A total of 95%, 94%, and 92% respondents, respectively, rated them as very helpful or game changers. The most pressing challenges affecting the field as a whole were competition for limited funding, duplication of efforts, and inadequate capacity building. A total of 76%, 67%, and 55% respondents, respectively, identified these as primary concerns. The key opportunities for growth identified in focus groups were increasing collaboration and information sharing, improving the interoperability of tools, and enhancing capacity for data analyses at scale. Some constraints appeared to disproportionately affect marginalized groups. Respondents in countries with developing economies were more likely to report being constrained by upfront costs, maintenance costs, and development funding (p = 0.048, odds ratio [OR] = 2.78; p = 0.005, OR = 4.23; p = 0.024, OR = 4.26), and female respondents were more likely to report being constrained by development funding and perceived technical skills (p = 0.027, OR = 3.98; p = 0.048, OR = 2.33). To our knowledge, this is the first attempt to formally capture the perspectives and needs of the global conservation technology community, providing foundational data that can serve as a benchmark to measure progress. We see tremendous potential for this community to further the vision they define, in which collaboration trumps competition; solutions are open, accessible, and interoperable; and user-friendly processing tools empower the rapid translation of data into conservation action. Article impact statement: Addressing financing, coordination, and capacity-building constraints is critical to the development and adoption of conservation technology.     

Fragmentation effects on an endangered species across a gradient from the interior to edge of its range

Understanding how habitat fragmentation affects individual species is complicated by challenges associated with quantifying species-specific habitat and spatial variability in fragmentation effects within a species’ range. We aggregated a 29-year breeding survey data set for the endangered marbled murrelet (Brachyramphus marmoratus) from >42,000 forest sites throughout the Pacific Northwest (Oregon, Washington, and northern California) of the United States. We built a species distribution model (SDM) in which occupied sites were linked with Landsat imagery to quantify murrelet-specific habitat and then used occupancy models to test the hypotheses that fragmentation negatively affects murrelet breeding distribution and that these effects are amplified with distance from the marine foraging habitat toward the edge of the species’ nesting range. Murrelet habitat declined in the Pacific Northwest by 20% since 1988, whereas the proportion of habitat comprising edges increased by 17%, indicating increased fragmentation. Furthermore, fragmentation of murrelet habitat at landscape scales (within 2 km of survey stations) negatively affected occupancy of potential breeding sites, and these effects were amplified near the range edge. On the coast, the odds of occupancy decreased by 37% (95% confidence interval [CI] –54 to 12) for each 10% increase in edge habitat (i.e., fragmentation), but at the range edge (88 km inland) these odds decreased by 99% (95% CI 98 to 99). Conversely, odds of murrelet occupancy increased by 31% (95% CI 14 to 52) for each 10% increase in local edge habitat (within 100 m of survey stations). Avoidance of fragmentation at broad scales but use of locally fragmented habitat with reduced quality may help explain the lack of murrelet population recovery. Further, our results emphasize that fragmentation effects can be nuanced, scale dependent, and geographically variable. Awareness of these nuances is critical for developing landscape-level conservation strategies for species experiencing broad-scale habitat loss and fragmentation.     

Boosting freshwater fish conservation with high-resolution distribution mapping across a large territory

The lack of high-resolution distribution maps for freshwater species across large extents fundamentally challenges biodiversity conservation worldwide. We devised a simple framework to delineate the distributions of freshwater fishes in a high-resolution drainage map based on stacked species distribution models and expert information. We applied this framework to the entire Chinese freshwater fish fauna (>1600 species) to examine high-resolution biodiversity patterns and reveal potential conflicts between freshwater biodiversity and anthropogenic disturbances. The correlations between spatial patterns of biodiversity facets (species richness, endemicity, and phylogenetic diversity) were all significant (r = 0.43–0.98, p < 0.001). Areas with high values of different biodiversity facets overlapped with anthropogenic disturbances. Existing protected areas (PAs), covering 22% of China's territory, protected 25–29% of fish habitats, 16–23% of species, and 30–31% of priority conservation areas. Moreover, 6–21% of the species were completely unprotected. These results suggest the need for extending the network of PAs to ensure the conservation of China's freshwater fishes and the goods and services they provide. Specifically, middle to low reaches of large rivers and their associated lakes from northeast to southwest China hosted the most diverse species assemblages and thus should be the target of future expansions of the network of PAs. More generally, our framework, which can be used to draw high-resolution freshwater biodiversity maps combining species occurrence data and expert knowledge on species distribution, provides an efficient way to design PAs regardless of the ecosystem, taxonomic group, or region considered.     

Mitigation translocation as a management tool

Mitigation translocation is a subgroup of conservation translocation, categorized by a crisis-responsive time frame and the immediate goal of relocating individuals threatened with death. However, the relative successes of conservation translocations with longer time frames and broader metapopulation- and ecosystem-level considerations have been used to justify the continued implementation of mitigation translocations without adequate post hoc monitoring to confirm their effectiveness as a conservation tool. Mitigation translocations now outnumber other conservation translocations, and understanding the effectiveness of mitigation translocations is critical given limited global conservation funding especially if the mitigation translocations undermine biodiversity conservation by failing to save individuals. We assessed the effectiveness of mitigation translocations by conducting a quantitative review of the global literature. A total of 59 mitigation translocations were reviewed for their adherence to the adaptive scientific approach expected of other conservation translocations and for the testing of management options to continue improving techniques for the future. We found that mitigation translocations have not achieved their potential as an effective applied science. Most translocations focused predominantly on population establishment- and persistence-level questions, as is often seen in translocations more broadly, and less on metapopulation and ecosystem outcomes. Questions regarding the long-term impacts to the recipient ecosystem (12% of articles) and the carrying capacity of translocation sites (24% of articles) were addressed least often, despite these factors being more likely to influence ultimate success. Less than half (47%) of studies included comparison of different management techniques to facilitate practitioners selecting the most effective management actions for the future. To align mitigation translocations with the relative success of other conservation translocations, it is critical that future mitigation translocations conform to an established experimental approach to improve their effectiveness. Effective mitigation translocations will require significantly greater investment of time, expertise, and resources in the future.