Minimizing the cost of translocation failure with decision‐tree models that predict species’ behavioral response in translocation sites

The high number of failures is one reason why translocation is often not recommended. Considering how behavior changes during translocations may improve translocation success. To derive decision‐tree models for species’ translocation, we used data on the short‐term responses of an endangered Australian skink in 5 simulated translocations with different release conditions. We used 4 different decision‐tree algorithms (decision tree, decision‐tree parallel, decision stump, and random forest) with 4 different criteria (gain ratio, information gain, gini index, and accuracy) to investigate how environmental and behavioral parameters may affect the success of a translocation. We assumed behavioral changes that increased dispersal away from a release site would reduce translocation success. The trees became more complex when we included all behavioral parameters as attributes, but these trees yielded more detailed information about why and how dispersal occurred. According to these complex trees, there were positive associations between some behavioral parameters, such as fight and dispersal, that showed there was a higher chance, for example, of dispersal among lizards that fought than among those that did not fight. Decision trees based on parameters related to release conditions were easier to understand and could be used by managers to make translocation decisions under different circumstances. Minimizar el Costo del Fracaso de la Reubicación con Modelos de Árboles de Decisión que Predigan la Respuesta Conductual de la Especie en los Sitios de Reubicación     

Using abiotic variables to predict importance of sites for species representation

In systematic conservation planning, species distribution data for all sites in a planning area are used to prioritize each site in terms of the site's importance toward meeting the goal of species representation. But comprehensive species data are not available in most planning areas and would be expensive to acquire. As a shortcut, ecologists use surrogates, such as occurrences of birds or another well‐surveyed taxon, or land types defined from remotely sensed data, in the hope that sites that represent the surrogates also represent biodiversity. Unfortunately, surrogates have not performed reliably. We propose a new type of surrogate, predicted importance, that can be developed from species data for a q% subset of sites. With species data from this subset of sites, importance can be modeled as a function of abiotic variables available at no charge for all terrestrial areas on Earth. Predicted importance can then be used as a surrogate to prioritize all sites. We tested this surrogate with 8 sets of species data. For each data set, we used a q% subset of sites to model importance as a function of abiotic variables, used the resulting function to predict importance for all sites, and evaluated the number of species in the sites with highest predicted importance. Sites with the highest predicted importance represented species efficiently for all data sets when q = 25% and for 7 of 8 data sets when q = 20%. Predicted importance requires less survey effort than direct selection for species representation and meets representation goals well compared with other surrogates currently in use. This less expensive surrogate may be useful in those areas of the world that need it most, namely tropical regions with the highest biodiversity, greatest biodiversity loss, most severe lack of inventory data, and poorly developed protected area networks.     

Use of genetic,climatic, and microbiological data to inform reintroduction of a regionally extinct butterfly

Species reintroductions are increasingly used as means of mitigating biodiversity loss. Besides habitat quality at the site targeted for reintroduction, the choice of source population can be critical for success. The butterfly Melanargia russiae (Esper´s marbled white) was extirpated from Hungary over 100 years ago, and a reintroduction program has recently been approved. We used museum specimens of this butterfly, mitochondrial DNA data (mtDNA), endosymbiont screening, and climatic‐similarity analyses to determine which extant populations should be used for its reintroduction. The species displayed 2 main mtDNA lineages across its range: 1 restricted to Iberia and southern France (Iberian lineage) and another found throughout the rest of its range (Eurasian lineage). These 2 lineages possessed highly divergent wsp alleles of the bacterial endosymbiont Wolbachia. The century‐old Hungarian specimens represented an endemic haplotype belonging to the Eurasian lineage, differing by one mutation from the Balkan and eastern European populations. The Hungarian populations of M. russiae occurred in areas with a colder and drier climate relative to most sites with extant known populations. Our results suggest the populations used for reintroduction to Hungary should belong to the Eurasian lineage, preferably from eastern Ukraine (genetically close and living in areas with the highest climatic similarity). Materials stored in museum collections can provide unique opportunities to document historical genetic diversity and help direct conservation.     

Quantifying progress toward a conservation assessment for all plants

The Global Strategy for Plant Conservation (GSPC) set an ambitious target to achieve a conservation assessment for all known plant species by 2020. We consolidated digitally available plant conservation assessments and reconciled their scientific names and assessment status to predefined standards to provide a quantitative measure of progress toward this target. The 241,919 plant conservation assessments generated represent 111,824 accepted land plant species (vascular plants and bryophytes, not algae). At least 73,081 and up to 90,321 species have been assessed at the global scale, representing 21–26% of known plant species. Of these plant species, at least 27,148 and up to 32,542 are threatened. Eighty plant families, including some of the largest, such as Asteraceae, Orchidaceae, and Rubiaceae, are underassessed and should be the focus of assessment effort if the GSPC target is to be met by 2020. Our data set is accessible online (ThreatSearch) and is a baseline that can be used to directly support other GSPC targets and plant conservation action. Although around one‐quarter of a million plant assessments have been compiled, the majority of plants are still unassessed. The challenge now is to build on this progress and redouble efforts to document conservation status of unassessed plants to better inform conservation decisions and conserve the most threatened species.     

Prevalence and perspectives of illegal trade in cacti and succulent plants in the collector community

Although illegal wildlife trade (IWT) represents a serious threat to biodiversity, research into the prevalence of illegal plant collection and trade remains scarce. Because cacti and succulents are heavily threatened by overcollection for often illegal, international ornamental trade, we surveyed 441 members of the cacti and succulent hobbyist collector community with a mixed quantitative and qualitative approach. We sought to understand collector perspectives on the Convention on the International Trade in Endangered Species of Wild Flora and Fauna (CITES) and on the threats IWT poses to cactus and succulent conservation. Most respondents (74% of 401 respondents) stated that illegal collection in cacti and succulents represents a “very serious problem” and that the problem of wild plant collection is increasing (72% of 319 respondents). Most forms of illegal collection and trade were seen as very unacceptable by respondents. Self-reported noncompliance with CITES rules was uncommon (11.2% of 418 respondents); it remains a persistent problem in parts of the cacti and succulent hobbyist community. People engaging in rule breaking, such as transporting plants without required CITES documents, generally did so knowingly. Although 60.6% of 381 respondents regarded CITES as a very important tool for conservation, sentiment toward CITES and its efficacy in helping species conservation was mixed. Collectors in our survey saw themselves as potentially playing important roles in cactus and succulent conservation, but this potential resource remains largely untapped. Our results suggest the need for enhanced consultation with stakeholders in CITES decision-making. For challenging subjects like IWT, developing evidence-based responses demands deep interdisciplinary engagement, including assessing the conservation impact of species listings on CITES appendices.     

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.     

Assessing citizen contributions to butterfly monitoring in two large cities

Citizen science may be especially effective in urban landscapes due to the large pool of potential volunteers. However, there have been few evaluations of the contributions of citizen scientists to knowledge of biological communities in and around cities. To assess the effectiveness of citizen scientists' monitoring of species in urban areas, we compared butterfly data collected over 10 years in Chicago, Illinois (U.S.A.), and New York City, New York (U.S.A.). The dates, locations, and methods of data collection in Chicago were standardized, whereas data from New York were collected at any location at any time. For each city, we evaluated whether the number of observers, observation days (days on which observations were reported), and sampling locations were associated with the reported proportion of the estimated regional pool of butterfly species. We also compared the number of volunteers, duration of volunteer involvement, and consistency of sampling efforts at individual locations within each city over time. From 2001 to 2010, there were 73 volunteers in Chicago and 89 in New York. During this period, volunteers observed 86% and 89% of the estimated number of butterfly species present in Chicago and New York, respectively. Volunteers in New York reported a greater proportion of the estimated pool of butterfly species per year. In addition, more species were observed per volunteer and observation day in New York, largely due to the unrestricted sampling season in New York. Chicago volunteers were active for more years and monitored individual locations more consistently over time than volunteers in New York. Differences in monitoring protocol--especially length of sampling season and selection protocol for monitoring locations--influenced the relationship between species accrual and sampling effort, which suggests these factors are important in volunteer-based species-monitoring programs.     

Inadvertent advocacy

Policy advocacy is an issue regularly debated among conservation scientists. These debates have focused on intentional policy advocacy by scientists, but advocacy can also be unintentional. I define inadvertent policy advocacy as the act of unintentionally expressing personal policy preferences or ethical judgments in a way that is nearly indistinguishable from scientific judgments. A scientist may be well intentioned and intellectually honest but still inadvertently engage in policy advocacy. There are two ways to inadvertently engage in policy advocacy. First, a scientist expresses an opinion that she or he believes is a scientific judgment but it is actually an ethical judgment or personal policy preference. Second, a scientist expresses an opinion that he or she knows is an ethical judgment or personal policy preference but inadvertently fails to effectively communicate the nature of the opinion to policy makers or the public. I illustrate inadvertent advocacy with three examples: recovery criteria in recovery plans for species listed under the U.S. Endangered Species Act, a scientific peer review of a recovery plan for the Northern Spotted Owl (Strix occidentalis caurina), and the International Union for Conservation of Nature's definition of threatened. In each example, scientists expressed ethical judgments or policy preferences, but their value judgments were not identified as such, and, hence, their value judgments were opaque to policy makers and the public. Circumstances suggest their advocacy was inadvertent. I believe conservation scientists must become acutely aware of the line between science and policy and avoid inadvertent policy advocacy because it is professional negligence, erodes trust in scientists and science, and perpetuates an ethical vacuum that undermines the rational political discourse necessary for the evolution of society's values. The principal remedy for inadvertent advocacy is education of conservation scientists in an effort to help them understand how science and values interact to fulfill the mission of conservation science.     

Evaluating unintended consequences of intentional species introductions and eradications for improved conservation management

Increasingly intensive strategies to maintain biodiversity and ecosystem function are being deployed in response to global anthropogenic threats, including intentionally introducing and eradicating species via assisted migration, rewilding, biological control, invasive species eradications, and gene drives. These actions are highly contentious because of their potential for unintended consequences. We conducted a global literature review of these conservation actions to quantify how often unintended outcomes occur and to elucidate their underlying causes. To evaluate conservation outcomes, we developed a community assessment framework for systematically mapping the range of possible interaction types for 111 case studies. Applying this tool, we quantified the number of interaction types considered in each study and documented the nature and strength of intended and unintended outcomes. Intended outcomes were reported in 51% of cases, a combination of intended outcomes and unintended outcomes in 26%, and strictly unintended outcomes in 10%. Hence, unintended outcomes were reported in 36% of all cases evaluated. In evaluating overall conservations outcomes (weighing intended vs. unintended effects), some unintended effects were fairly innocuous relative to the conservation objective, whereas others resulted in serious unintended consequences in recipient communities. Studies that assessed a greater number of community interactions with the target species reported unintended outcomes more often, suggesting that unintended consequences may be underreported due to insufficient vetting. Most reported unintended outcomes arose from direct effects (68%) or simple density-mediated or indirect effects (25%) linked to the target species. Only a few documented cases arose from more complex interaction pathways (7%). Therefore, most unintended outcomes involved simple interactions that could be predicted and mitigated through more formal vetting. Our community assessment framework provides a tool for screening future conservation actions by mapping the recipient community interaction web to identify and mitigate unintended outcomes from intentional species introductions and eradications for conservation.     

Scaling range sizes to threats for robust predictions of risks to biodiversity

Assessments of risk to biodiversity often rely on spatial distributions of species and ecosystems. Range‐size metrics used extensively in these assessments, such as area of occupancy (AOO), are sensitive to measurement scale, prompting proposals to measure them at finer scales or at different scales based on the shape of the distribution or ecological characteristics of the biota. Despite its dominant role in red‐list assessments for decades, appropriate spatial scales of AOO for predicting risks of species’ extinction or ecosystem collapse remain untested and contentious. There are no quantitative evaluations of the scale‐sensitivity of AOO as a predictor of risks, the relationship between optimal AOO scale and threat scale, or the effect of grid uncertainty. We used stochastic simulation models to explore risks to ecosystems and species with clustered, dispersed, and linear distribution patterns subject to regimes of threat events with different frequency and spatial extent. Area of occupancy was an accurate predictor of risk (0.81<|r|<0.98) and performed optimally when measured with grid cells 0.1–1.0 times the largest plausible area threatened by an event. Contrary to previous assertions, estimates of AOO at these relatively coarse scales were better predictors of risk than finer‐scale estimates of AOO (e.g., when measurement cells are <1% of the area of the largest threat). The optimal scale depended on the spatial scales of threats more than the shape or size of biotic distributions. Although we found appreciable potential for grid‐measurement errors, current IUCN guidelines for estimating AOO neutralize geometric uncertainty and incorporate effective scaling procedures for assessing risks posed by landscape‐scale threats to species and ecosystems.