Detecting Rare Species with Random or Subjective Sampling: a Case Study of Red-Listed Saproxylic Beetles in Boreal Sweden

Abstract:  Efficient sampling design in field studies is important for economical and statistical reasons. We compared two ways to distribute sampling effort over an area, either randomly or subjectively. We searched for red-listed saproxylic (wood-living) beetles in 30 spruce stands in boreal Sweden by sifting wood from dead trees. We randomly selected positions within each stand with a geographic positioning system and sampled the nearest dead tree (random sample). In the same stand we also sampled dead trees that, based on literature, were likely to host such species (subjective sampling). The subjective sampling (two to five samples per stand, depending on stand size) was compared with the higher, random sampling effort (fixed level of 12 samples/stand). Subjective sampling was significantly more efficient. Red-listed species were found in 36% of the subjective samples and in 16% of the random samples. Nevertheless, the larger random effort resulted in a comparable number of red-listed species per stand and in 13 detected species in total (vs. 12 species with subjective sampling). Random sampling was less efficient, but provided an unbiased alternative more suitable for statistical purposes, as needed in, for example, monitoring programs. Moreover, new species-specific knowledge can be gained through random searches.     

Using Scalar Models for Precautionary Assessments of Threatened Species

Abstract:  Scalar population models, commonly referred to as count-based models, are based on time-series data of population sizes and may be useful for screening-level ecological risk assessments when data for more complex models are not available. Appropriate use of such models for management purposes, however, requires understanding inherent biases that may exist in these models. Through a series of simulations, which compared predictions of risk of decline of scalar and matrix-based models, we examined whether discrepancies may arise from different dynamics displayed due to age structure and generation time. We also examined scalar and matrix-based population models of 18 real populations for potential patterns of bias in population viability estimates. In the simulation study, precautionary bias (i.e., overestimating risks of decline) of scalar models increased as a function of generation time. Models of real populations showed poor fit between scalar and matrix-based models, with scalar models predicting significantly higher risks of decline on average. The strength of this bias was not correlated with generation time, suggesting that additional sources of bias may be masking this relationship. Scalar models can be useful for screening-level assessments, which should in general be precautionary, but the potential shortfalls of these models should be considered before using them as a basis for management decisions.     

Assessing the Effectiveness of Reserve Acquisition Programs in Protecting Rare and Threatened Species

Abstract:  Measuring the effectiveness of reserve networks is essential to ensure that conservation objectives such as species persistence are being met. We devised a new approach for measuring the effectiveness of land conservation in protecting rare and threatened species and applied it to an ecosystem of global significance. We compiled detailed global distributional data for 36 rare and threatened plants and animals found in the Lake Wales Ridge ecosystem in central Florida (U.S.A.). For each species, we developed a set of protection indices based in part on criteria used to categorize species for the World Conservation Union's Red List. We calculated protection indexes under three different conservation scenarios: a past scenario, which assumed recent, major land-acquisition efforts never occurred; a current scenario, which assumed no additional areas are saved beyond what is currently protected; and a targeted scenario, which assumed all of the remaining areas targeted for protection are eventually acquired. This approach enabled us to quantify the progress, in terms of reduced risk of extinction, that conservationists have made in protecting target species. It also revealed the limited success these land-acquisition efforts have had in reducing those extinction risks associated with loss of habitat or small geographic ranges. Many species of the Lake Wales Ridge will remain at high risk of extinction even if planned land-acquisition efforts are completely successful. By calculating protection indexes with and without each site for all imperiled species, we also quantified the contribution of each protected area to the conservation of each species, enabling local conservation decisions to be made in the context of a larger (global) perspective. The protection index approach can be adapted readily to other ecosystems with multiple rare and threatened species.     

Integrating the Metapopulation and Habitat Paradigms for Understanding Broad-Scale Declines of Species

Abstract:  Caughley (1994) argued that researchers working on threatened populations tended to follow the "small population paradigm" or the "declining population paradigm," and that greater integration of these paradigms was needed. Here I suggest that two related paradigms exist at the broader spatial scale, namely the metapopulation paradigm and habitat paradigm, and that these two paradigms also need to be integrated if we are to provide sound management advice. This integration is not trivial, and I outline five problems that need to be addressed: (1) habitat variables may not measure habitat quality, so site-specific data on vital rates are needed to resolve the effects of habitat quality and metapopulation dynamics; (2) measurements of vital rates may be confounded by movements; (3) vital rates may be density dependent; (4) vital rates may be affected by genotype; and (5) vital rates cannot be measured in unoccupied patches. I reviewed papers published in Conservation Biology from 1994 to 2003 and found 41 studies that analyzed data from 10 or more sites to understand the factors limiting species' distributions. Five of the analyses presented were purely within the metapopulation paradigm, 14 were purely within the habitat paradigm, 17 involved elements of both paradigms, and 7 were theoretically ambiguous (2 papers presented 2 distinct analyses and were counted twice). This suggests that many researchers appreciate the need to integrate the paradigms. Only one study, however, used data on vital rates to resolve the effects of habitat quality and metapopulation dynamics (problem 1), and this study did not address problems 2–5. I conclude that more intensive research incorporating site-specific data on vital rates and movement is needed to complement the numerous analyses of distributional data being produced.     

南亚热带森林3层次物种多度之广义泊松分布模型

生物群落中物种多度分布(species abundance distribution)呈典型的倒J形,即其中存在许多稀有种、少量常见种.物种多度分布模型研究有助于解决森林生态恢复中的物种配置等实际问题.本研究考察了一种过分散(over-dispersion,或称超分布,即方差大于均值)的离散型分布,即具有λ和α两个参数...     

Invasive Species Research to Meet the Needs of Resource Management and Planning

Abstract: As zebra mussels (Dreissena polymorpha) continue to spread among inland lakes of the United States and Canada, there is growing interest from professionals, citizens, and other stakeholders to know which lakes are likely to be colonized by zebra mussels. Thus, we developed a classification of lake suitability for zebra mussels on the basis of measured or estimated concentrations of dissolved calcium in lake water and applied the classification to >11,500 lakes in Wisconsin and the Upper Peninsula of Michigan. The majority of lakes (58%) were classified as unsuitable (<10 mg/L Ca) for survival and reproduction of zebra mussels, 27% were identified as suitable (≥21 mg/L Ca), and 15% were classified as borderline suitable (≥10 and <21 mg/L Ca). Of the 77 inland lakes with confirmed zebra mussel records for which data on dissolved calcium were available, our method classified 74 as suitable and 3 as borderline suitable. To communicate this lake‐specific suitability information and to help prioritize regional efforts to monitor and prevent the expansion of zebra mussels and other invasive species, we developed a web‐based interface (available from http://www.aissmartprevention.wisc.edu/ ). Although we are still uncertain of how access to suitability information ultimately affects decision making, we believe this is a useful case study of building communication channels among researchers, practitioners, and the public.     

Use of Surrogates to Predict the Stressor Response of Imperiled Species

Abstract: Rare or narrowly distributed species may be threatened by stressors to which they have never been exposed or for which data are very limited. In such cases the species response cannot be predicted on the basis of directly measured data, but may be inferred from the response of one or more appropriate surrogate species. Here, I propose a practical way to use the stressor response of one or more surrogate species to develop a working hypothesis or model of the stressor response of the target species. The process has 4 steps: (1) identify one or more candidate surrogate species, (2) model the relationship between the stressor and the response variable of interest for the surrogate species, (3) adapt the stressor–response relationship from the surrogate species to a model for the target species, possibly using Bayesian methods, and (4) incorporate additional data as they become available and adjust the response model of the target species appropriately. I applied the approach to an endangered fish species, the amber darter (Percina antesella), which is potentially threatened by urbanization. I used a Bayesian approach to combine data from a surrogate species (the bronze darter[Percina palmaris]) with available data for the amber darter to produce a model of expected amber darter response. Although this approach requires difficult decisions on the part of the manager, especially in the selection of surrogate species, its value lies in the fact that all assumptions are clearly stated in the form of hypotheses, which may be scrutinized and tested. It therefore provides a rational basis for instituting management policy even in the face of considerable uncertainty.     

物种敏感度分布(SSD)方法在农药环境风险评估中的应用

物种敏感度分布法(Species Sensitive Distribution,SSD)能够依据不同物种对农药等胁迫因素的敏感度服从一定的累积概率分布,以统计形式将多种非靶标物种的实验室数据进行汇总分析,获得物种对农药的敏感度差异,作为效应评估指标应用于农药风险评估。本文综述了SSD概念、方法原理、国内外研究和应用进展,并以毒死蜱为例进行了数据分析。由此建议继续关注国际上对SSD及更复杂模型模拟研究进展,以便应用于我国农药环境风险评估,推动我国农药管理的持续发展。     

Quantitative tools for implementing the new definition of significant portion of the range in the U.S. Endangered Species Act

In 2014, the Fish and Wildlife Service (FWS) and National Marine Fisheries Service announced a new policy interpretation for the U.S. Endangered Species Act (ESA). According to the act, a species must be listed as threatened or endangered if it is determined to be threatened or endangered in a significant portion of its range (SPR). The 2014 policy seeks to provide consistency by establishing that a portion of the range should be considered significant if the associated individuals’ “removal would cause the entire species to become endangered or threatened.” We reviewed 20 quantitative techniques used to assess whether a portion of a species’ range is significant according to the new guidance. Our assessments are based on the 3R criteria—redundancy (i.e., buffering from catastrophe), resiliency (i.e., ability to withstand stochasticity), and representation (i.e., ability to evolve)—that the FWS uses to determine if a species merits listing. We identified data needs for each quantitative technique and considered which methods could be implemented given the data limitations typical of rare species. We also identified proxies for the 3Rs that may be used with limited data. To assess potential data availability, we evaluated 7 example species by accessing data in their species status assessments, which document all the information used during a listing decision. In all species, an SPR could be evaluated with at least one metric for each of the 3Rs robustly or with substantial assumptions. Resiliency assessments appeared most constrained by limited data, and many species lacked information on connectivity between subpopulations, genetic variation, and spatial variability in vital rates. These data gaps will likely make SPR assessments for species with complex life histories or that cross national boundaries difficult. Although we reviewed techniques for the ESA, other countries require identification of significant areas and could benefit from this research.     

Using Modeling to Improve Monitoring of Structured Populations: Are We Collecting the Right Data?

Abstract:  Population monitoring is central to most demographic studies and conservation efforts, but it may not always be directed at the most appropriate life stage. We used stochastic simulation modeling to evaluate the effectiveness of a monitoring program for a well-studied population of Eastern Imperial Eagles ( Aquila heliaca ) in Kazakhstan. Specifically, we asked whether the most appropriate data were being collected to understand system state and population dynamics. Our models were parameterized with data collected over the course of 25 years of study of this population. We used the models to conduct simulation experiments to evaluate relationships between monitored or potentially monitored parameters and the demographic variables of interest—population size ( N ) and population growth (λ). Static analyses showed that traditional territory-based monitoring was a poor indicator of eagle population size and growth and that monitoring survivorship would provide more information about these parameters. Nevertheless, these same traditionally monitored territory-based parameters had greater power to detect long-term changes in population size than did survivorship or population structure. Regardless of the taxa considered, threats can have immediate impacts on population size and growth or longer-term impacts on population dynamics. Prudently designed monitoring programs for any species will detect the demographic effects of both types of threats.     

The Value of Using Feasibility Models in Systematic Conservation Planning to Predict Landholder Management Uptake

Understanding the social dimensions of conservation opportunity is crucial for conservation planning in multiple‐use landscapes. However, factors that influence the feasibility of implementing conservation actions, such as the history of landscape management, and landholders’ willingness to engage are often difficult or time consuming to quantify and rarely incorporated into planning. We examined how conservation agencies could reduce costs of acquiring such data by developing predictive models of management feasibility parameterized with social and biophysical factors likely to influence landholders’ decisions to engage in management. To test the utility of our best‐supported model, we developed 4 alternative investment scenarios based on different input data for conservation planning: social data only; biological data only; potential conservation opportunity derived from modeled feasibility that incurs no social data collection costs; and existing conservation opportunity derived from feasibility data that incurred collection costs. Using spatially explicit information on biodiversity values, feasibility, and management costs, we prioritized locations in southwest Australia to control an invasive predator that is detrimental to both agriculture and natural ecosystems: the red fox (Vulpes vulpes). When social data collection costs were moderate to high, the most cost‐effective investment scenario resulted from a predictive model of feasibility. Combining empirical feasibility data with biological data was more cost‐effective for prioritizing management when social data collection costs were low (<4% of the total budget). Calls for more data to inform conservation planning should take into account the costs and benefits of collecting and using social data to ensure that limited funding for conservation is spent in the most cost‐efficient and effective manner.     

Geography and Recovery under the U.S. Endangered Species Act

Abstract: The U.S. Endangered Species Act (ESA) defines an endangered species as one “at risk of extinction throughout all or a significant portion of its range.” The prevailing interpretation of this phrase, which focuses exclusively on the overall viability of listed species without regard to their geographic distribution, has led to development of listing and recovery criteria with fundamental conceptual, legal, and practical shortcomings. The ESA's concept of endangerment is broader than the biological concept of extinction risk in that the “esthetic, ecological, educational, historical, recreational, and scientific” values provided by species are not necessarily furthered by a species mere existence, but rather by a species presence across much of its former range. The concept of “significant portion of range” thus implies an additional geographic component to recovery that may enhance viability, but also offers independent benefits that Congress intended the act to achieve. Although the ESA differs from other major endangered‐species protection laws because it acknowledges the distinct contribution of geography to recovery, it resembles the “representation, resiliency, and redundancy” conservation‐planning framework commonly referenced in recovery plans. To address representation, listing and recovery standards should consider not only what proportion of its former range a species inhabits, but the types of habitats a species occupies and the ecological role it plays there. Recovery planning for formerly widely distributed species (e.g., the gray wolf [Canis lupus]) exemplifies how the geographic component implicit in the ESA's definition of endangerment should be considered in determining recovery goals through identification of ecologically significant types or niche variation within the extent of listed species, subspecies, or “distinct population segments.” By linking listing and recovery standards to niche and ecosystem concepts, the concept of ecologically significant type offers a scientific framework that promotes more coherent dialogue concerning the societal decisions surrounding recovery of endangered species.     

Using experimental reintroductions to resolve the roles of habitat quality and metapopulation dynamics on patch occupancy in fragmented landscapes

Declines of species in fragmented landscapes can potentially be reversed either by restoring connectivity or restoring local habitat quality. Models fitted to snapshot occupancy data can be used to predict the effectiveness of these actions. However, such inferences can be misleading if the reliability of the habitat and landscape metrics used is unknown. The only way to unambiguously resolve the roles of habitat quality and metapopulation dynamics is to conduct experimental reintroductions to unoccupied patches so that habitat quality can be measured directly from data on vital rates. We, therefore, conducted a 15-year study that involved reintroducing a threatened New Zealand bird to unoccupied forest fragments to obtain reliable data on their habitat quality and reassess initial inferences made by modeling occupancy against habitat and landscape metrics. Although reproductive rates were similar among fragments, subtle differences in adult survival rates resulted in λ (finite rate of increase) estimations of <0.9 for 9 of the 12 fragments that were previously unoccupied. This was the case for only 1 of 14 naturally occupied fragments. This variation in λ largely explained the original occupancy pattern, reversing our original conclusion from occupancy modeling that this occupancy pattern was isolation driven and suggesting that it would be detrimental to increase connectivity without improving local habitat quality. These results illustrate that inferences from snapshot occupancy should be treated with caution and subjected to testing through experimental reintroductions in selected model systems.     

Use of Community‐Composition Data to Predict the Fecundity and Abundance of Species

Abstract: Species distribution models are critical tools for the prediction of invasive species spread and conservation of biodiversity. The majority of species distribution models have been built with environmental data. Community ecology theory suggests that species co‐occurrence data could also be used to predict current and potential distributions of species. Species assemblages are the products of biotic and environmental constraints on the distribution of individual species and as a result may contain valuable information for niche modeling. We compared the predictive ability of distribution models of annual grassland plants derived from either environmental or community‐composition data. Composition‐based models were built with the presence or absence of species at a site as predictors of site quality, whereas environment‐based models were built with soil chemistry, moisture content, above‐ground biomass, and solar radiation as predictors. The reproductive output of experimentally seeded individuals of 4 species and the abundance of 100 species were used to evaluate the resulting models. Community‐composition data were the best predictors of both the site‐specific reproductive output of sown individuals and the site‐specific abundance of existing populations. Successful community‐based models were robust to omission of data on the occurrence of rare species, which suggests that even very basic survey data on the occurrence of common species may be adequate for generating such models. Our results highlight the need for increased public availability of ecological survey data to facilitate community‐based modeling at scales relevant to conservation.     

Using the past to contextualize anthropogenic impacts on the present and future distribution of an endemic Caribbean mammal

Island species are difficult to conserve because they face the synergy of climate change, invasive species, deforestation, and increasing human population densities in areas where land mass is shrinking. The Caribbean island of Hispaniola presents particular challenges because of geopolitical complexities that span 2 countries and hinder coordinated management of species across the island. We employed species distribution modeling to evaluate the impacts of climatic change and anthropogenic activities on the distribution of an endemic mammal of conservation concern, the Hispaniolan solenodon (Solenodon paradoxus). We aggregated occurrence points for this poorly known species for the Last Glacial Maximum (LGM) and the present (1975–2016) based on museum collections, online biodiversity databases, and new field surveys. We quantified degree of overlap between periods and scenarios with Schoener's D. Through a conservation paleobiology lens, we found that over time humans played an increasing role in shaping the distribution of S. paradoxus, thus, providing a foundation for developing conservation strategies on appropriate spatiotemporal scales. Human population density was the single most important predictor of S. paradoxus occurrence. Densities >166 people/km² corresponded to a near-zero probability of occurrence. Models that accounted for climate but not anthropogenic variables falsely identified suitable habitat in Haiti, where on-the-ground surveys confirm habitat is unavailable. Climate-only models also significantly overestimated the potential for habitat connectivity between isolated populations. Our work highlights that alternative fates for S. paradoxus in the Anthropocene exist across the political border between the Dominican Republic and Haiti due to the fundamentally different economic and political realities of each country. Relationships in the fossil record confirm that Hispaniola's sociopolitical boundary is not biologically significant but instead represents one imposed on the island's fauna in the past 500 years by colonial activity. Our approach reveals how a paleontological perspective can contribute to concrete management insights.