Space-time modeling for the Missouri Turkey Hunting Survey

The Missouri Turkey Hunting Survey (MTHS) is a postseason mail survey conducted by the Missouri Department of Conservation. The 1996 MTHS provides information concerning the number of turkeys harvested by hunters on each day and the total number of trips made to the counties by these hunters on each day of the hunting season. The success rates are then found from this information. Small sample sizes produce large standard errors for the estimates at the county level. We use a Bayesian hierarchical generalized linear model to estimate daily hunting success rates at the county level. The model includes an autoregressive process for the days of the hunting season and spatially correlated random geographic effects. The computations are performed using Gibbs sampling and adaptive rejection sampling techniques. Results show that there are significant spatial corelations between counties and correlations between days of the hunting season. The estimates are close to the frequency estimates at the state level and much more stable at the county level.     

Multimethod,multistate Bayesian hierarchical modeling approach for use in regional monitoring of wolves

In many cases, the first step in large‐carnivore management is to obtain objective, reliable, and cost‐effective estimates of population parameters through procedures that are reproducible over time. However, monitoring predators over large areas is difficult, and the data have a high level of uncertainty. We devised a practical multimethod and multistate modeling approach based on Bayesian hierarchical‐site‐occupancy models that combined multiple survey methods to estimate different population states for use in monitoring large predators at a regional scale. We used wolves (Canis lupus) as our model species and generated reliable estimates of the number of sites with wolf reproduction (presence of pups). We used 2 wolf data sets from Spain (Western Galicia in 2013 and Asturias in 2004) to test the approach. Based on howling surveys, the naïve estimation (i.e., estimate based only on observations) of the number of sites with reproduction was 9 and 25 sites in Western Galicia and Asturias, respectively. Our model showed 33.4 (SD 9.6) and 34.4 (3.9) sites with wolf reproduction, respectively. The number of occupied sites with wolf reproduction was 0.67 (SD 0.19) and 0.76 (0.11), respectively. This approach can be used to design more cost‐effective monitoring programs (i.e., to define the sampling effort needed per site). Our approach should inspire well‐coordinated surveys across multiple administrative borders and populations and lead to improved decision making for management of large carnivores on a landscape level. The use of this Bayesian framework provides a simple way to visualize the degree of uncertainty around population‐parameter estimates and thus provides managers and stakeholders an intuitive approach to interpreting monitoring results. Our approach can be widely applied to large spatial scales in wildlife monitoring where detection probabilities differ between population states and where several methods are being used to estimate different population parameters.     

A framework for adapting survey design through time for wildlife population assessment

Sampling strategies for monitoring the status and trends in wildlife populations are often determined before the first survey is undertaken. However, there may be little information about the distribution of the population and so the sample design may be inefficient. Through time, as data are collected, more information about the distribution of animals in the survey region is obtained but it can be difficult to incorporate this information in the survey design. This paper introduces a framework for monitoring motile wildlife populations within which the design of future surveys can be adapted using data from past surveys whilst ensuring consistency in design-based estimates of status and trends through time. In each survey, part of the sample is selected from the previous survey sample using simple random sampling. The rest is selected with inclusion probability proportional to predicted abundance. Abundance is predicted using a model constructed from previous survey data and covariates for the whole survey region. Unbiased design-based estimators of status and trends and their variances are derived from two-phase sampling theory. Simulations over the short and long-term indicate that in general more precise estimates of status and trends are obtained using this mixed strategy than a strategy in which all of the sample is retained or all selected with probability proportional to predicted abundance. Furthermore the mixed strategy is robust to poor predictions of abundance. Estimates of status are more precise than those obtained from a rotating panel design.     

Modeling species-habitat relationships with spatially autocorrelated observation data.

Spatial autocorrelation in wildlife observation data arises when extrinsic environmental processes and patterns that influence the spatial distribution of wildlife are themselves spatially structured, or when species are subject to intrinsic population processes, causing contagion or dispersion effects. Territoriality, Allee effects, dispersal limitations, and social clustering are examples of intrinsic processes. Both forms of autocorrelation can violate the assumptions of generalized linear regression models, resulting in biased estimation of model coefficients and diminished predictive performance. Such consequences may be avoided for extrinsic autocorrelation when autocorrelated environmental variables are available for use as model covariates, whereas intrinsic spatial autocorrelation requires an alternative modeling approach. The autologistic model provides an approach suited to the binary observations often obtained in wildlife surveys, but its performance has not been tested across widely varying sampling intensities or strengths of intrinsic spatial structure. Here we use simulated data to test the autologistic model under a range of sampling conditions. The autologistic model obtains better fits and substantially better predictive performance than the standard logistic regression model over the full range of sampling designs and intensities tested. We provide a simple Bayesian implementation of the autologistic model, which until now has not been achieved with standard statistical software alone. A step-by-step procedure is given for characterizing and modeling spatial autocorrelation in binary observation data, along with computer code for fitting autologistic models in WinBUGS, a freeware Bayesian analysis package. This approach avoids normal approximations to the pseudo-likelihood, in contrast to previous Bayesian applications of the autologistic model. We provide a sample application of the autologistic model, fitted to survey data for a gliding marsupial in southeastern Australia.     

Habitat Mosaic, Wildlife Availability, and Hunting in the Tropical Forest of Calakmul, Mexico

Abstract: Habitat loss and subsistence hunting are two of the main activities that affect wildlife in frontier areas. We compared subsistence hunting patterns in four villages with different ethnic composition and degree of habitat disturbance in the vicinity of Calakmul Biosphere Reserve, Campeche, Mexico. We also compared differences between some of these villages in harvest composition and prey availability to determine hunting preferences. We used a Landsat TM satellite image to analyze the degree of disturbance around the villages. We conducted periodic surveys of subsistence hunting and prey availability. Wildlife availability was assessed monthly on nine transects (3000 m) established in the vicinity of three villages. The relative amount of disturbed habitat was smaller in an indigenous Maya village ( IV ) and larger in a mestizo village ( MV ). The two mixed-composition villages ( MCVs) had intermediate levels of disturbance. Ten species, four large and six small, of birds and mammals accounted for 97% of the hunting records. Hunting was more intense in IV and less intense in MCV1. The three village types had different hunting preferences. The habitat-mosaic composition in the vicinity of the villages influenced prey availability and subsistence-hunting preferences. Changes in the habitat mosaic were caused by the size of the holding and by ethnic composition. In spite of longer settlement time, the habitat mosaic in the vicinity of IV was less transformed than that of the other sites. Their larger holding size and greater diversity of economic activities may explain why the Mayas at IV have transformed the landscape less than the other groups and can hunt more and larger prey.     

Rural Development and Sustainable Wildlife Use in Peru

Abstract: Tropical conservation has seen a convergence between conservation projects and rural development, with both approaches promoting participation of local people in sustainable resource use. But there is a discord between rural development and sustainable use of wildlife. Implementing more sustainable use of wildlife usually means decreased economic benefits for rural people, especially over the short term. In contrast, rural-development projects are often mandated to generate income for rural people over the short term. We examined this dilemma through an integrated economic and harvest analysis of the costs associated with converting unsustainable hunting to more sustainable hunting in the Peruvian Amazon. Our analysis suggests that a change in hunting practice would have significant economic costs for rural people and would result in a 36% decrease in the economic benefits they derive from wildlife hunting. In contrast, converting unsustainable hunting to more sustainable hunting would have little effect on meat markets in the urban center of Iquitos, Peru, with markets losing only 3.6% of their economic value. There would be no economic costs for the international pelt trade. If rural-development projects absorb the short-term economic costs, they can help people convert unsustainable wildlife use to more sustainable use and assist rural people in realizing the long-term benefits of more sustainable hunting. But many rural-development projects would need to change their mandate for short-term income generation to incorporate the realities of sustainability.     

Effects of Trophy Hunting on Lion and Leopard Populations in Tanzania

Abstract: Tanzania holds most of the remaining large populations of African lions (Panthera leo) and has extensive areas of leopard habitat (Panthera pardus), and both species are subjected to sizable harvests by sport hunters. As a first step toward establishing sustainable management strategies, we analyzed harvest trends for lions and leopards across Tanzania's 300,000 km² of hunting blocks. We summarize lion population trends in protected areas where lion abundance has been directly measured and data on the frequency of lion attacks on humans in high‐conflict agricultural areas. We place these findings in context of the rapidly growing human population in rural Tanzania and the concomitant effects of habitat loss, human‐wildlife conflict, and cultural practices. Lion harvests declined by 50% across Tanzania between 1996 and 2008, and hunting areas with the highest initial harvests suffered the steepest declines. Although each part of the country is subject to some form of anthropogenic impact from local people, the intensity of trophy hunting was the only significant factor in a statistical analysis of lion harvest trends. Although leopard harvests were more stable, regions outside the Selous Game Reserve with the highest initial leopard harvests again showed the steepest declines. Our quantitative analyses suggest that annual hunting quotas be limited to 0.5 lions and 1.0 leopard/1000 km² of hunting area, except hunting blocks in the Selous Game Reserve, where harvests should be limited to 1.0 lion and 3.0 leopards/1000 km².     

Modeling the impacts of hunting on the population dynamics of red howler monkeys (Alouatta seniculus)

Overexploitation of wildlife populations occurs across the humid tropics and is a significant threat to the long-term survival of large-bodied primates. To investigate the impacts of hunting on primates and ways to mitigate them, we developed a spatially explicit, individual-based model for a landscape that included hunted and un-hunted areas. We used the large-bodied neotropical red howler monkey (Alouatta seniculus) as our case study species because its life history characteristics make it vulnerable to hunting. We modeled the influence of different rates of harvest and proportions of landscape dedicated to un-hunted reserves on population persistence, population size, social dynamics, and hunting yields of red howler monkeys. In most scenarios, the un-hunted populations maintained a constant density regardless of hunting pressure elsewhere, and allowed the overall population to persist. Therefore, the overall population was quite resilient to extinction; only in scenarios without any un-hunted areas did the population go extinct. However, the total and hunted populations did experience large declines over 100 years under moderate and high hunting pressure. In addition, when reserve area decreased, population losses and losses per unit area increased disproportionately. Furthermore, hunting disrupted the social structure of troops. The number of male turnovers and infanticides increased in hunted populations, while birth rates decreased and exacerbated population losses due to hunting. Finally, our results indicated that when more than 55% of the landscape was harvested at high (30%) rates, hunting yields, as measured by kilograms of biomass, were less than those obtained from moderate harvest rates. Additionally, hunting yields, expressed as the number of individuals hunted/year/km², increased in proximity to un-hunted areas, and suggested that dispersal from un-hunted areas may have contributed to hunting sustainability. These results indicate that un-hunted areas serve to enhance hunting yields, population size, and population persistence in hunted landscapes. Therefore, spatial regulation of hunting via a reserve system may be an effective management strategy for sustainable hunting, and we recommend it because it may also be more feasible to implement than harvest quotas or restrictions on season length.     

Designing an efficient adaptive cluster sample

The choice of neighborhood definition and critical value in adaptive cluster sampling is critical for designing an efficient survey. In designing an efficient adaptive cluster sample one should aim for a small difference between the initial and final sample size, and a small difference between the within-network and population variances. However, the two aims can be at odds with each other because small differences between initial and final sample size usually means small within-network variance. One way to help in designing an efficient survey is to think in terms of small network sizes since the network size is a function of both critical value and neighborhood definition. One should aim for networks that are small enough to ensure the final sample size is not excessively large compared with the initial sample size but large enough to ensure the within-network variance is a reasonable fraction of the population variance. In this study surveys that had networks that were two to four units in size were the most efficient.     

Antipoaching standards in onshore hydrocarbon concessions drawn from a Central African case study

Unsustainable hunting outside protected areas is threatening tropical biodiversity worldwide and requires conservationists to engage increasingly in antipoaching activities. Following the example of ecocertified logging companies, we argue that other extractive industries managing large concessions should engage in antipoaching activities as part of their environmental management plans. Onshore hydrocarbon concessions should also adopt antipoaching protocols as a standard because they represent a biodiversity threat comparable to logging. We examined the spatiotemporal patterns of small‐ and large‐mammal poaching in an onshore oil concession in Gabon, Central Africa, with a Bayesian occupancy model based on signs of poaching collected from 2010 to 2015 on antipoaching patrols. Patrol locations were initially determined based on local intelligence and past patrol successes (adaptive management) and subsequently with a systematic sampling of the concession. We generated maps of poaching probability in the concession and determined the temporal trends of this threat over 5 years. The spatiotemporal patterns of large‐ and small‐mammal poaching differed throughout the concession, and likely these groups will need different management strategies. By elucidating the relationship between site‐specific sampling effort and detection probability, the Bayesian method allowed us to set goals for future antipoaching patrols. Our results indicate that a combination of systematic sampling and adaptive management data is necessary to infer spatiotemporal patterns with the statistical method we used. On the basis of our case study, we recommend hydrocarbon companies interested in implementing efficient antipoaching activities in their onshore concessions to lay the foundation of long‐needed industry standards by: adequately measuring antipoaching effort; mixing adaptive management and balanced sampling; setting goals for antipoaching effort; pairing patrols with large‐mammal monitoring; supporting antipoaching patrols across the landscape; restricting access to their concessions; performing random searches for bushmeat and mammal products at points of entry; controlling urban and agricultural expansion; supporting bushmeat alternatives; and supporting land‐use planning.     

Campesino hunting and conservation in Latin America

Hunting presents a paradox for biodiversity conservation. It is both a problem and a solution to species declines and poverty. Yet, conservation scientists hold different assumptions about the significance and sustainability of hunting based on the cultures and identities of hunters. In Latin America, conservationists largely sort hunters as either indigenous or campesino. Indigenous hunters are often characterized as culturally driven stewards of wildlife sustainability. Campesino hunters, by contrast, are described as peasants—cultureless, uneducated, and uncaring toward wildlife sustainability. Although such ethnically fueled hunting discourse promotes hunting research, campesino hunters remain underrepresented in most comparative hunting reviews. Moreover, there are no targeted syntheses on the current state of knowledge about campesino hunting, nothing to guide conservation research and practice with and for the largest group of hunters in Latin America. We reviewed 334 articles published from 1937 to 2018 in English (55%) and Spanish (45%)—mostly published in 145 peer-reviewed journals—on the meanings, motivations, and sustainability of campesino hunting in Latin America. Although studies spanned 17 countries, 7 ecosystems, and >75 indigenous and nonindigenous demographics in 30 research contexts, they predominantly focused on nonindigenous campesinos for species-specific conservation and protected area management in tropical broadleaf forests of Mexico, Peru, and Colombia. Authors used 12 methods to collect campesino hunting data, primarily interviews, surveys, and questionnaires, and drew from 10 local and traditional knowledge themes about wildlife trends and uses. Eighteen drivers, 14 constraints, and 10 conflicts—mainly subsistence, income, ethics, regulations, and crop or livestock protection—shaped whether campesino hunters pursued 799 species, 70% of which were least concern species. Yet, only 25 studies (8%) empirically assessed sustainability. Our results show the need for increased interdisciplinary and geographic engagement with campesino hunting across Latin America.     

Application of k-means clustering to environmental risk zoning of the chemical industrial area

The homogeneous risk characteristics within a sub-area and the heterogeneous from one sub-area to another are unclear using existing environmental risk zoning methods. This study presents a new zoning method by determining and categorizing the risk characteristics using the k-means clustering data mining technology. The study constructs indices and develops index quantification models for environmental risk zoning by analyzing the mechanism of environmental risk occurrence. We calculate the source risk index, air risk field index, water risk field index, and target vulnerability of the study area with Nanjing Chemical Industrial Park using a 100 m - 100 m mesh grid as the basic zoning unit, and then use k-means clustering to analyze the environmental risk in the area. We obtain the optimal clustering number with the largest average silhouette coefficient by calculating the average silhouette coefficients of clustering at different k-values. The clustering result with the optimal clustering number is then used for the environmental risk zoning, and the zoning result is mapped using the geographic information system. The study area is divided into five sub-areas. The common environmental risk characteristics within the same sub-area, as well as the differences between sub- areas, are presented. The zoning is helpful in risk management and is convenient for decision makers to distribute limited resources to different sub-areas in the design of risk reducing intervention.     

Impacts of hunting on tropical forests in Southeast Asia

Although deforestation and forest degradation have long been considered the most significant threats to tropical biodiversity, across Southeast Asia (Northeast India, Indochina, Sundaland, Philippines) substantial areas of natural habitat have few wild animals (>1 kg), bar a few hunting‐tolerant species. To document hunting impacts on vertebrate populations regionally, we conducted an extensive literature review, including papers in local journals and reports of governmental and nongovernmental agencies. Evidence from multiple sites indicated animal populations declined precipitously across the region since approximately 1980, and many species are now extirpated from substantial portions of their former ranges. Hunting is by far the greatest immediate threat to the survival of most of the region's endangered vertebrates. Causes of recent overhunting include improved access to forests and markets, improved hunting technology, and escalating demand for wild meat, wildlife‐derived medicinal products, and wild animals as pets. Although hunters often take common species, such as pigs or rats, for their own consumption, they take rarer species opportunistically and sell surplus meat and commercially valuable products. There is also widespread targeted hunting of high‐value species. Consequently, as currently practiced, hunting cannot be considered sustainable anywhere in the region, and in most places enforcement of protected‐area and protected‐species legislation is weak. The international community's focus on cross‐border trade fails to address overexploitation of wildlife because hunting and the sale of wild meat is largely a local issue and most of the harvest is consumed in villages, rural towns, and nearby cities. In addition to improved enforcement, efforts to engage hunters and manage wildlife populations through sustainable hunting practices are urgently needed. Unless there is a step change in efforts to reduce wildlife exploitation to sustainable levels, the region will likely lose most of its iconic species, and many others besides, within the next few years.     

A Novel Approach to Assessing the Prevalence and Drivers of Illegal Bushmeat Hunting in the Serengeti

Assessing anthropogenic effects on biological diversity, identifying drivers of human behavior, and motivating behavioral change are at the core of effective conservation. Yet knowledge of people's behaviors is often limited because the true extent of natural resource exploitation is difficult to ascertain, particularly if it is illegal. To obtain estimates of rule‐breaking behavior, a technique has been developed with which to ask sensitive questions. We used this technique, unmatched‐count technique (UCT), to provide estimates of bushmeat poaching, to determine motivation and seasonal and spatial distribution of poaching, and to characterize poaching households in the Serengeti. We also assessed the potential for survey biases on the basis of respondent perceptions of understanding, anonymity, and discomfort. Eighteen percent of households admitted to being involved in hunting. Illegal bushmeat hunting was more likely in households with seasonal or full‐time employment, lower household size, and longer household residence in the village. The majority of respondents found the UCT questions easy to understand and were comfortable answering them. Our results suggest poaching remains widespread in the Serengeti and current alternative sources of income may not be sufficiently attractive to compete with the opportunities provided by hunting. We demonstrate that the UCT is well suited to investigating noncompliance in conservation because it reduces evasive responses, resulting in more accurate estimates, and is technically simple to apply. We suggest that the UCT could be more widely used, with the trade‐off being the increased complexity of data analyses and requirement for large sample sizes. Una Aproximación Novedosa para Evaluar la Prevalencia y Factores de la Cacería Ilegal en el Serengueti     

Risk Analysis of Hunting of Seal Populations in the Baltic

Vulnerabilities of grey seal ( Halichoerus grypus) and ringed seal ( Phoca hispida) populations in the Baltic Sea were evaluated for potential opening of the populations for hunting. We used ecological risk analysis to assess the effects of environmental and demographic stochasticity and uncertain and partly missing population data on the modeled outcomes. The impact of different harvesting strategies on the long-term sustainability of seal populations was analyzed with four different models with increasing complexity and population detail. It appears the simpler the population model used, the more overconfident results it gave with regard to the hunting policy to be adopted. Therefore, it proves risky in population management decisions to rely on simplistic calculations based on growth rate and estimated population size alone. This is even more so if the population estimates have a wide error margin. Due to an unknown, but presumably positive number of seal kills in the Baltic at present, the sustainable harvest is likely to be close to zero for both seal species. Our risk analysis strongly suggests refraining from Baltic seal hunting now, with their current population sizes, and in the future if the development of population numbers cannot be assessed accurately enough.     

Effects of Private‐Land Use,Livestock Management,and Human Tolerance on Diversity,Distribution, and Abundance of Large African Mammals

Successful conservation of large terrestrial mammals (wildlife) on private lands requires that landowners be empowered to manage wildlife so that benefits outweigh the costs. Laikipia County, Kenya, is predominantly unfenced, and the land uses in the area allow wide‐ranging wildlife to move freely between different management systems on private land. We used camera traps to sample large mammals associated with 4 different management systems (rhinoceros sanctuaries, no livestock; conservancies, intermediate stocking level; fenced ranches, high stocking level; and group ranches, high stocking level, no fencing, pastoralist clan ownership) to examine whether management and stocking levels affect wildlife. We deployed cameras at 522 locations across 8 properties from January 2008 through October 2010 and used the photographs taken during this period to estimate richness, occupancy, and relative abundance of species. Species richness was highest in conservancies and sanctuaries and lowest on fenced and group ranches. Occupancy estimates were, on average, 2 and 5 times higher in sanctuaries and conservancies as on fenced and group ranches, respectively. Nineteen species on fenced ranches and 25 species on group ranches were considered uncommon (occupancy < 0.1). The relative abundance of most species was highest or second highest in sanctuaries and conservancies. Lack of rights to manage and utilize wildlife and uncertain land tenure dampen many owners’ incentives to tolerate wildlife. We suggest national conservation strategies consider landscape‐level approaches to land‐use planning that aim to increase conserved areas by providing landowners with incentives to tolerate wildlife. Possible incentives include improving access to ecotourism benefits, forging agreements to maintain wildlife habitat and corridors, resolving land‐ownership conflicts, restoring degraded rangelands, expanding opportunities for grazing leases, and allowing direct benefits to landowners through wildlife harvesting. Efectos del Uso Privado de Suelo, Manejo de Ganado y la Tolerancia Humana sobre la Diversidad, Distribución y Abundancia de Mamíferos Mayores Africanos     

Population viability and harvest sustainability for Madagascar lemurs

Subsistence hunting presents a conservation challenge by which biodiversity preservation must be balanced with safeguarding of human livelihoods. Globally, subsistence hunting threatens primate populations, including Madagascar's endemic lemurs. We used population viability analysis to assess the sustainability of lemur hunting in Makira Natural Park, Madagascar. We identified trends in seasonal hunting of 11 Makira lemur species from household interview data, estimated local lemur densities in populations adjacent to focal villages via transect surveys, and quantified extinction vulnerability for these populations based on species-specific demographic parameters and empirically derived hunting rates. We compared stage-based Lefkovitch with periodic Leslie matrices to evaluate the impact of regional dispersal on persistence trajectories and explored the consequences of perturbations to the timing of peak hunting relative to the lemur birth pulse, under assumptions of density-dependent reproductive compensation. Lemur hunting peaked during the fruit-abundant wet season (March–June). Estimated local lemur densities were roughly inverse to body size across our study area. Life-history modeling indicated that hunting most severely threatened the species with the largest bodies (i.e., Hapalemur occidentalis, Avahi laniger, Daubentonia madagascariensis, and Indri indi), characterized by late-age reproductive onsets and long interbirth intervals. In model simulations, lemur dispersal within a regional metapopulation buffered extinction threats when a majority of local sites supported growth rates above the replacement level but drove regional extirpations when most local sites were overharvested. Hunt simulations were most detrimental when timed to overlap lemur births (a reality for D. madagascariensis and I. indri). In sum, Makira lemurs were overharvested. Regional extirpations, which may contribute to broad-scale extinctions, will be likely if current hunting rates persist. Cessation of anthropogenic lemur harvest is a conservation priority, and development programs are needed to help communities switch from wildlife consumption to domestic protein alternatives.     

Using spatial patterns in illegal wildlife uses to reveal connections between subsistence hunting and trade

Although most often considered independently, subsistence hunting, domestic trade, and international trade as components of illegal wildlife use (IWU) may be spatially correlated. Understanding how and where subsistence and commercial uses may co‐occur has important implications for the design and implementation of effective conservation actions. We analyzed patterns in the joint geographical distribution of illegal commercial and subsistence use of multiple wildlife species in Venezuela and evaluated whether available data were sufficient to provide accurate estimates of the magnitude, scope, and detectability of IWU. We compiled records of illegal subsistence hunting and trade from several sources and fitted a random‐forest classification model to predict the spatial distribution of IWUs. From 1969 to 2014, 404 species and 8,340,921 specimens were involved in IWU, for a mean extraction rate of 185,354 individuals/year. Birds were the most speciose group involved (248 spp.), but reptiles had the highest extraction rates (126,414 individuals/year vs. 3,133 individuals/year for birds). Eighty‐eight percent of international trade records spatially overlapped with domestic trade, especially in the north and along the coast but also in western inland areas. The distribution of domestic trade was broadly distributed along roads, suggesting that domestic trade does not depend on large markets in cities. Seventeen percent of domestic trade records overlapped with subsistence hunting, but the spatial distribution of this overlap covered a much larger area than between commercial uses. Domestic trade seems to respond to demand from rural more than urban communities. Our approach will be useful for understanding how IWU works at national scales in other parts of the world.     

Moral Hazard, Externalities, and Compensation for Crop Damages from Wildlife

A principal–multiple agent model is used to examine wildlife damage abatement and compensation programs in a setting in which farmers suffer damages and hunters use the wildlife for recreational purposes. In addition to externalities inherent in abatement, abatement/compensation policy confronts the issue of moral hazard. By representing the principal as a wildlife management authority who acts on behalf of hunters, we investigate contracts in which transfers of more or less severe hunting regulations, a public good that aids in dispersing wildlife, and monetary payments from hunting license fees can be used to overcome moral hazard.     

Nonparametric spatial regression of survival probability: visualization of population sinks in Eurasian woodcock

Both evolutionary ecologists and wildlife managers make inference based on how fitness and demography vary in space. Spatial variation in survival can be difficult to assess in the wild because (1) multisite study designs are not well suited to populations that are continuously distributed across a large area and (2) available statistical models accounting for detectability less than 1.0 do not easily cope with geographical coordinates. Here we use penalized splines within a Bayesian state-space modeling framework to estimate and visualize survival probability in two dimensions. The approach is flexible in that no parametric form for the relationship between survival and coordinates need be specified a priori. To illustrate our method, we study a game species, the Eurasian Woodcock Scolopax rusticola, based on band recovery data (5000 individuals) collected over a > 50 000-km2 area in west-central France with contrasted habitats and hunting pressures. We find that spatial variation in survival probability matches an index of hunting pressure and creates a mosaic of population sources and sinks. Such analyses could provide guidance concerning the spatial management of hunting intensity or could be used to identify pathways of spatial variation in fitness, for example, to study adaptation to changing landscape and climate.