Upper level set scan statistic for detecting arbitrarily shaped hotspots

A declared need is around for geoinformatic surveillance statistical science and software infrastructure for spatial and spatiotemporal hotspot detection. Hotspot means something unusual, anomaly, aberration, outbreak, elevated cluster, critical resource area, etc. The declared need may be for monitoring, etiology, management, or early warning. The responsible factors may be natural, accidental, or intentional. This proof-of-concept paper suggests methods and tools for hotspot detection across geographic regions and across networks. The investigation proposes development of statistical methods and tools that have immediate potential for use in critical societal areas, such as public health and disease surveillance, ecosystem health, water resources and water services, transportation networks, persistent poverty typologies and trajectories, environmental justice, biosurveillance and biosecurity, among others. We introduce, for multidisciplinary use, an innovation of the health-area-popular circle-based spatial and spatiotemporal scan statistic. Our innovation employs the notion of an upper level set, and is accordingly called the upper level set scan statistic, pointing to a sophisticated analytical and computational system as the next generation of the present day popular SaTScan. Success of surveillance rests on potential elevated cluster detection capability. But the clusters can be of any shape, and cannot be captured only by circles. This is likely to give more of false alarms and more of false sense of security. What we need is capability to detect arbitrarily shaped clusters. The proposed upper level set scan statistic innovation is expected to fill this need     

A decision framework for estimating the cost of marine plastic pollution interventions

Marine plastic pollution has emerged as one of the most pressing environmental challenges of our time. Although there has been a surge in global investment for implementing interventions to mitigate plastic pollution, there has been little attention given to the cost of these interventions. We developed a decision support framework to identify the economic, social, and ecological costs and benefits of plastic pollution interventions for different sectors and stakeholders. We calculated net cost as a function of six cost and benefit categories with the following equation: cost of implementing an intervention (direct, indirect, and nonmonetary costs) minus recovered costs and benefits (monetary and nonmonetary) produced by the interventions. We applied our framework to two quantitative case studies (a solid waste management plan and a trash interceptor) and four comparative case studies, evaluating the costs of beach cleanups and waste-to-energy plants in various contexts, to identify factors that influence the costs of plastic pollution interventions. The socioeconomic context of implementation, the spatial scale of implementation, and the time scale of evaluation all influence costs and the distribution of costs across stakeholders. Our framework provides an approach to estimate and compare the costs of a range of interventions across sociopolitical and economic contexts.     

Using simulation to explore the functional relationships of terrestrial carnivore population indices

Population indices based on visits to detection stations commonly are used to monitor wildlife populations. Inferences about populations are based on 1 of 2 measures: (1) change in the proportion of stations visited at least once or (2) change in the cumulative number of visits by unique individuals. The functional relationships between index responses and population density is poorly understood and can lead to misinterpretation of index data when an incorrect functional relationship (e.g. linear) is assumed. We created a flexible simulation environment to study the response of detection-based population indices under a wide variety of conditions meant to reflect species life history and study design. Proportional indices exhibited non-linear saturating responses to changes in population density while cumulative indices responded linearly. Shapes of responses were functions of home range sizes, individual detection probabilities, and spatial arrangement of animals and sampling stations. Non-linear relationships of proportional indices lead to under-estimation of mean population density when data are aggregated from multiple detection stations deployed in a heterogeneous landscape. Cumulative indices have significant statistical advantages over proportional indices including smaller sample sizes required to detect density change, linearity, consistent index responses across a wide range of densities, and ability to aggregate data to meet minimum sample size requirements. Our simulation provides a flexible tool for the interpretation of station-based population indices.     

Estimating population impacts via dynamic occupancy analysis of Before-After Control-Impact studies

Estimating environmental impacts on populations is one of the main goals of wildlife monitoring programs, which are often conducted in conjunction with management actions or following natural disturbances. In this study we investigate the statistical power of dynamic occupancy models to detect changes in local survival and colonization from detection-nondetection data, while accounting for imperfect detection probability, in a Before-After Control-Impact (BACI) framework. We simulated impacts on local survival and/or detection probabilities, and asked questions related to: (1) costs and benefits of different analysis models, (2) confounding changes in detection with changes in local survival, (3) sampling design trade-offs, and (4) species with low vs. high rates of turnover. Estimating seasonal effects on local survival and colonization, as opposed to estimating Before-After effects, had little effect on the power to detect changes in local survival. Estimating a parameter that accounted for pretreatment differences in local survival between Control and Impact sites decreased power by 50%, but it was critical to include when such differences existed. When the experimental treatment had a negative impact on species detectability but analysis assumed constant detection, the Type I error rates were dramatically inflated (0.20 0.33). In general, there was low power (< 0.5) to detect a 50% decrease in local survival for all combinations of sites (N = 50 vs. 100), seasons sampled (8 vs. 12), and visits per site per season (4 vs. 6). Unbalanced designs performed worse than balanced designs, with the exception of the case of treatments being implemented in different seasons at different sites. Adding more control sites improved the ability to detect changes in local survival. Surveying more seasons after impact resulted in modest power gains, but at least three seasons before impact were required to successfully implement BACI occupancy studies. Turnover rates had a low impact on power. Occupancy studies conducted in a BACI design offer the opportunity to detect environmental impacts on wildlife populations without the costs of intensive studies. However, given the low power to detect small changes (20%) in local survival, these studies should be used when researchers are confident that major treatment impacts will occur or very large sample sizes are obtainable.     

Economic costs of protecting islands from invasive alien species

Biological invasions represent a key threat to insular systems and have pronounced impacts across environments and economies. The ecological impacts have received substantial focus, but the socioeconomic impacts are poorly synthesized across spatial and temporal scales. We used the InvaCost database, the most comprehensive assessment of published economic costs of invasive species, to assess economic impacts on islands worldwide. We analyzed socioeconomic costs across differing expenditure types and examined temporal trends across islands that differ in their political geography—island nation states, overseas territories, and islands of continental countries. Over US$36 billion in total costs (including damages and management) has occurred on islands from 1965 to 2020 due to invasive species’ impacts. Nation states incurred the greatest total and management costs, and islands of continental countries incurred costs of similar magnitude, both far higher than those in overseas territories. Damage-loss costs were significantly lower, but with qualitatively similar patterns across differing political geographies. The predominance of management spending differs from the pattern found for most countries examined and suggests important knowledge gaps in the extent of many damage-related socioeconomic impacts. Nation states spent the greatest proportion of their gross domestic products countering these costs, at least 1 order of magnitude higher than other locations. Most costs were borne by authorities and stakeholders, demonstrating the key role of governmental and nongovernmental bodies in addressing island invasions. Temporal trends revealed cost increases across all island types, potentially reflecting efforts to tackle invasive species at larger, more socially complex scales. Nevertheless, the already high total economic costs of island invasions substantiate the role of biosecurity in reducing and preventing invasive species arrivals to reduce strains on limited financial resources and avoid threats to sustainable development goals.     

A meta-BACI approach for evaluating management intervention on chronic wasting disease in mule deer.

Advances in acquiring and analyzing the spatial attributes of data have greatly enhanced the potential utility of wildlife disease surveillance data for addressing problems of ecological or economic importance. We present an approach for using wildlife disease surveillance data to identify areas for (or of) intervention, to spatially delineate paired treatment and control areas, and then to analyze these nonrandomly selected sites in a meta-analysis framework via before-after-control impact (BACI) estimates of effect size. We apply these methods to evaluate the effectiveness of attempts to reduce chronic wasting disease (CWD) prevalence through intensive localized culling of mule deer (Odocoileus hemionus) in north-central Colorado, USA. Areas where surveillance data revealed high prevalence or case clusters were targeted by state wildlife management agency personnel for focal scale (on average <17 km2) culling, primarily via agency sharpshooters. Each area of sustained culling that we could also identify as unique by cluster analysis was considered a potential treatment area. Treatment areas, along with spatially paired control areas that we constructed post hoc in a case-control design (collectively called "management evaluation sites"), were then delineated using home range estimators. Using meta-BACI analysis of CWD prevalence data for all management evaluation sites, the mean effect size (change of prevalence on treatment areas minus change in prevalence on their paired control areas) was 0.03 (SE = 0.03); mean effect size on treatment areas was not greater than on paired control areas. Excluding cull samples from prevalence estimates or allowing for an equal or greater two-year lag in system responses to management did not change this outcome. We concluded that management benefits were not evident, although whether this represented true ineffectiveness or was a result of lack of data or insufficient duration of treatment could not be discerned. Based on our observations, we offer recommendations for designing a management experiment with 80% power to detect a 0.10 drop in prevalence over a 6-12-year period.     

Primate home-range size and metabolic needs

Summary We test the hypothesis that cross-species variation in home range size across primates is determined by the metabolic needs of the animals occupying the home range and by their diet. Metabolic needs are calculated from published records of group structure, time spent in different activities and the metabolic costs of those activities. Data from 20 species demonstrate clear relationships between home range, diet and metabolic needs. Although correlations are in the expected directions, simple models relating diet to home range size and metabolic needs do not predict the functional relationships found. This may be because the data are inadequate or because the models are wrong. An empirical relationship between relative home-range size and diet distinguishes between the arboreal and terrestrial species in the sample.     

Quantifying the probability of detection of wild ungulates with the Judas technique

The Judas technique is often used in control or eradication of particular vertebrate pests. The technique exploits the tendency of individuals to form social groups. A radio collar is affixed to an individual and its subsequent monitoring facilitates the detection of other conspecifics. Efficacy of this technique would be improved if managers could estimate the probability that a Judas individual would detect conspecifics. To calculate this probability, we estimated association rates of Judas individuals with other Judas individuals, given the length of time the Judas has been deployed. We developed a simple model of space-use for individual Judas animals and constrained detection probabilities to those specific areas. We then combined estimates for individual Judas animals to infer the probability that a wild individual could be detected in an area of interest via Judas surveillance. We illustrated the method by using data from a feral goat eradication program on Isla Santiago, Galápagos, and a feral pig eradication program on Santa Cruz Island, California. Association probabilities declined as the proximity between individual areas of use of a Judas pair decreased. Unconditional probabilities of detection within individual areas of use averaged 0.09 per month for feral pigs and 0.11 per month for feral goats. Probabilities that eradication had been achieved, given no detections of wild conspecifics, and an uninformative prior probability of eradication were 0.79 (90% CI 0.22–0.99) for feral goats and 0.87 (90% CI 0.44–1.0) for feral pigs. We envisage several additions to the analyses used that could improve estimates of Judas detection probability. Analyses such as these can help managers increase the efficacy of eradication efforts, leading to more effective effects to restore native biodiversity.     

Quantifying the conservation gains from shared access to linear infrastructure

The proliferation of linear infrastructure such as roads and railways is a major global driver of cumulative biodiversity loss. One strategy for reducing habitat loss associated with development is to encourage linear infrastructure providers and users to share infrastructure networks. We quantified the reductions in biodiversity impact and capital costs under linear infrastructure sharing of a range of potential mine to port transportation links for 47 mine locations operated by 28 separate companies in the Upper Spencer Gulf Region of South Australia. We mapped transport links based on least‐cost pathways for different levels of linear‐infrastructure sharing and used expert‐elicited impacts of linear infrastructure to estimate the consequences for biodiversity. Capital costs were calculated based on estimates of construction costs, compensation payments, and transaction costs. We evaluated proposed mine‐port links by comparing biodiversity impacts and capital costs across 3 scenarios: an independent scenario, where no infrastructure is shared; a restricted‐access scenario, where the largest mining companies share infrastructure but exclude smaller mining companies from sharing; and a shared scenario where all mining companies share linear infrastructure. Fully shared development of linear infrastructure reduced overall biodiversity impacts by 76% and reduced capital costs by 64% compared with the independent scenario. However, there was considerable variation among companies. Our restricted‐access scenario showed only modest biodiversity benefits relative to the independent scenario, indicating that reductions are likely to be limited if the dominant mining companies restrict access to infrastructure, which often occurs without policies that promote sharing of infrastructure. Our research helps illuminate the circumstances under which infrastructure sharing can minimize the biodiversity impacts of development.     

Detection and delineation of critical areas using echelons and spatial scan statistics with synoptic cellular data

Geographical surveillance for hotspot detection and delineation has become an important area of investigation both in geospatial ecosystem health and in geospatial public health. In order to find critical areas based on synoptic cellular data, geospatial ecosystem health investigations apply recently discovered echelon tools. In order to find elevated rate areas based on synoptic cellular data, geospatial public health investigations apply recently discovered spatial scan statistic tools. The purpose of this paper is to conceptualize a joint role for these together in the spirit of a cross-disciplinary cross-fertilization to accomplish more effective and efficient geographical surveillance for hotspot detection and delineation, and early warning system.     

Indigenous People's Detection of Rapid Ecological Change

When sudden catastrophic events occur, it becomes critical for coastal communities to detect and respond to environmental transformations because failure to do so may undermine overall ecosystem resilience and threaten people's livelihoods. We therefore asked how capable of detecting rapid ecological change following massive environmental disruptions local, indigenous people are. We assessed the direction and periodicity of experimental learning of people in the Western Solomon Islands after a tsunami in 2007. We compared the results of marine science surveys with local ecological knowledge of the benthos across 3 affected villages and 3 periods before and after the tsunami. We sought to determine how people recognize biophysical changes in the environment before and after catastrophic events such as earthquakes and tsunamis and whether people have the ability to detect ecological changes over short time scales or need longer time scales to recognize changes. Indigenous people were able to detect changes in the benthos over time. Detection levels differed between marine science surveys and local ecological knowledge sources over time, but overall patterns of statistically significant detection of change were evident for various habitats. Our findings have implications for marine conservation, coastal management policies, and disaster‐relief efforts because when people are able to detect ecological changes, this, in turn, affects how they exploit and manage their marine resources. Detección del Cambio Ecológico Rápido por la Población Indígena     

A review of predator diet effects on prey defensive responses

Numerous studies have examined how predator diets influence prey responses to predation risk, but the role predator diet plays in modulating prey responses remains equivocal. We reviewed 405 predator–prey studies in 109 published articles that investigated changes in prey responses when predators consumed different prey items. In 54 % of reviewed studies, prey responses were influenced by predator diet. The value of responding based on a predator’s recent diet increased when predators specialized more strongly on particular prey species, which may create patterns in diet cue use among prey depending upon whether they are preyed upon by generalist or specialist predators. Further, prey can alleviate costs or accrue greater benefits using diet cues as secondary sources of information to fine tune responses to predators and to learn novel risk cues from exotic predators or alarm cues from sympatric prey species. However, the ability to draw broad conclusions regarding use of predator diet cues by prey was limited by a lack of research identifying molecular structures of the chemicals that mediate these interactions. Conclusions are also limited by a narrow research focus. Seventy percent of reviewed studies were performed in freshwater systems, with a limited range of model predator–prey systems, and 98 % of reviewed studies were performed in laboratory settings. Besides identifying the molecules prey use to detect predators, future studies should strive to manipulate different aspects of prey responses to predator diet across a broader range of predator–prey species, particularly in marine and terrestrial systems, and to expand studies into the field.     

Hierarchical Bayesian modelling of early detection surveillance for plant pest invasions

Early detection surveillance programs aim to find invasions of exotic plant pests and diseases before they are too widespread to eradicate. However, the value of these programs can be difficult to justify when no positive detections are made. To demonstrate the value of pest absence information provided by these programs, we use a hierarchical Bayesian framework to model estimates of incursion extent with and without surveillance. A model for the latent invasion process provides the baseline against which surveillance data are assessed. Ecological knowledge and pest management criteria are introduced into the model using informative priors for invasion parameters. Observation models assimilate information from spatio-temporal presence/absence data to accommodate imperfect detection and generate posterior estimates of pest extent. When applied to an early detection program operating in Queensland, Australia, the framework demonstrates that this typical surveillance regime provides a modest reduction in the estimate that a surveyed district is infested. More importantly, the model suggests that early detection surveillance programs can provide a dramatic reduction in the putative area of incursion and therefore offer a substantial benefit to incursion management. By mapping spatial estimates of the point probability of infestation, the model identifies where future surveillance resources can be most effectively deployed.     

Rapidly assessing cobenefits to advance threat-management alliances

Conservation strategies aimed at reducing threats to biodiversity can have significant implications for multiple sectors in a socioeconomic system, but these cobenefits are often poorly understood. For example, many of the threats to native species also impede agricultural production, yet agriculture is typically perceived as in competition with conservation objectives. Although a comprehensive, multiobjective decision analysis is usually beyond the scope and capacity of conservation decision makers, failing to incorporate key socioeconomic costs and benefits into conservation decision-making processes can result in missed opportunities for diversifying outcomes and creating cost-sharing multisectoral partnerships. We devised a straightforward and readily interpretable approach to incorporate cobenefits into a threat-management prioritization approach. We used it to analyze the agricultural cobenefits of implementing 9 invasive animal management strategies designed to ensure the persistence of 148 threatened species across Australia's Lake Eyre Basin over 50 years. A structured elicitation process with 24 participants (scientists, land managers, agriculturalists, and other stakeholders) was used to collect information on each strategy, including costs, technical and social feasibility, benefits to native threatened species, and cobenefits to agricultural production systems. The costs of targeted invasive animal management to save threatened species across the basin (AU$33 million/year) outweighed the overall benefits to the agricultural industry (estimated AU$226 million/year). The return on investment for these management strategies varied substantially when agricultural cobenefits were considered alongside threatened species benefits and showed synergies and challenges. Our approach demonstrates the value of incorporating cobenefits of conservation actions into cost-effectiveness analyses to guide potential investment and partnerships and to diversify implementation pathways.     

Costs of expanding the network of protected areas as a response to climate change in the Cape Floristic Region

The expansion of protected areas is a critical component of strategies to promote the continued existence of biodiversity (i.e., life at all levels of biological organization) as climate changes, but scientific, social, and economic uncertainties associated with climate change are some of the major obstacles preventing such expansion. New models of climate change and species distribution and new methods of conservation planning now make it possible to explore the uncertainties associated with climate changes and species responses. Yet few reliable estimates of the costs of expanding protected areas and methods for determining these costs exist, largely because of the many (and uncertain) determinants of these costs. We developed a cost-accounting model to estimate the range in costs of various options for expanding protected areas and to explore the variables that drive these costs. Model development was informed by an existing plan to expand protected areas in the Cape Floristic Region of South Africa to address species conservation under a scenario of climate change. The 50-year present value of total costs varied from US$260 million ($1077/ha) for an off-reserve option that involves agreements with landowners and no compensation of forgone production and associated revenue to $1020 million ($4228/ha) for an on-reserve option that involves land acquisition and protection. The costs of acquiring land or compensating landowners for forgone production and development opportunities were the major drivers of the total costs across all options because most of the area identified in the protected-area expansion plan consisted of urban and high-quality agricultural lands. Total costs were also affected by changes in protected area extent and discount rate. Model-generated outputs such as these may be useful for informing implementation strategies and the allocation of future efforts in monitoring, data collection, and model development.     

Factors associated with preemptive conservation under the U.S. Endangered Species Act

In recent decades, there has been an increasing emphasis on proactive efforts to conserve species being considered for listing under the U.S. Endangered Species Act (ESA) before they are listed (i.e., preemptive conservation). These efforts, which depend on voluntary actions by public and private land managers across the species’ range, aim to conserve species while avoiding regulatory costs associated with ESA listing. We collected data for a set of social, economic, environmental, and institutional factors that we hypothesized would influence voluntary decisions to promote or inhibit preemptive conservation of species under consideration for ESA listing. We used logistic regression to estimate the association of these factors with preemptive conservation outcomes based on data for a set of species that entered the ESA listing process and were either officially listed (n = 314) or preemptively conserved (n = 73) from 1996 to 2018. Factors significantly associated with precluded listing due to preemptive conservation included high baseline conservation status, low proportion of private land across the species’ range, small total range size, exposure to specific types of threats, and species’ range extending over several states. These results highlight strategies that can help improve conservation outcomes, such as allocating resources for imperiled species earlier in the listing process, addressing specific threats, and expanding incentives and coordination mechanisms for conservation on private lands.     

ATOMI射频氦等离子体原子发射光谱用于毛细管气相色谱检测(英文)

1　IntroductionInmodernanalyticalchemistry ,chromatographyandemissionspectroscopyandtheircombinedusearebecominganincreasinglyimportanttechniqueforthemeasurementofenvironmentalpollu tants.AtomicemissiondetectorusedinGCcanprovidehighlysensitiveandselectiver…     

射频氦等离子体原子发射光谱用于毛细管气相色谱检测

1　IntroductionInmodernanalyticalchemistry ,chromatographyandemissionspectroscopyandtheircombinedusearebecominganincreasinglyimportanttechniqueforthemeasurementofenvironmentalpollu tants.AtomicemissiondetectorusedinGCcanprovidehighlysensitiveandselectiveresponsewithwidedynamicrangeforvariouselementsinelutingcompounds[1—4 ].Itcanalsoprovidespectrumofelementssimultaneously ,sotheycouldbeusedforempiricalformuladetermination .Wehavedevelopedanatomicemissiondetectorusingradiofrequencydischargepla…     

Spatially Explicit Power Analyses for Occupancy‐Based Monitoring of Wolverine in the U.S. Rocky Mountains

Conservation scientists and resource managers often have to design monitoring programs for species that are rare or patchily distributed across large landscapes. Such programs are frequently expensive and seldom can be conducted by one entity. It is essential that a prospective power analysis be undertaken to ensure stated monitoring goals are feasible. We developed a spatially based simulation program that accounts for natural history, habitat use, and sampling scheme to investigate the power of monitoring protocols to detect trends in population abundance over time with occupancy‐based methods. We analyzed monitoring schemes with different sampling efforts for wolverine (Gulo gulo) populations in 2 areas of the U.S. Rocky Mountains. The relation between occupancy and abundance was nonlinear and depended on landscape, population size, and movement parameters. With current estimates for population size and detection probability in the northern U.S. Rockies, most sampling schemes were only able to detect large declines in abundance in the simulations (i.e., 50% decline over 10 years). For small populations reestablishing in the Southern Rockies, occupancy‐based methods had enough power to detect population trends only when populations were increasing dramatically (e.g., doubling or tripling in 10 years), regardless of sampling effort. In general, increasing the number of cells sampled or the per‐visit detection probability had a much greater effect on power than the number of visits conducted during a survey. Although our results are specific to wolverines, this approach could easily be adapted to other territorial species. Poder de Análisis Espacialmente Explícito para el Monitoreo Basado en Ocupación del Glotón (Gulo gulo) en las Montañas Rocallosas de Estados Unidos     

The short-run impact of environmental protection costs on U.S. product prices

Using an input-output framework, this paper investigates the magnitude of the impact that environmental protection costs had on prices in the United States in 1977. With the imposition of environmental protection costs, the projected total price increases for individual industries range from 0.12% to 6.58%. Due to data limitations, the constraints of input-output analysis, and the structural changes that occurred in the economy from 1972 to 1977, the results should not be taken as definitive. However, the results do indicate the typical sort of variation in impact likely to occur across industries and that the average impact on prices was modest.