A spatial approach to combatting wildlife crime

Poaching can have devastating impacts on animal and plant numbers, and in many countries has reached crisis levels, with illegal hunters employing increasingly sophisticated techniques. We used data from an 8‐year study in Savé Valley Conservancy, Zimbabwe, to show how geographic profiling—a mathematical technique originally developed in criminology and recently applied to animal foraging and epidemiology—can be adapted for use in investigations of wildlife crime. The data set contained information on over 10,000 incidents of illegal hunting and the deaths of 6,454 wild animals. We used a subset of data for which the illegal hunters’ identities were known. Our model identified the illegal hunters’ home villages based on the spatial locations of the hunting incidences (e.g., snares). Identification of the villages was improved by manipulating the probability surface inside the conservancy to reflect the fact that although the illegal hunters mostly live outside the conservancy, the majority of hunting occurs inside the conservancy (in criminology terms, commuter crime). These results combined with rigorous simulations showed for the first time how geographic profiling can be combined with GIS data and applied to situations with more complex spatial patterns, for example, where landscape heterogeneity means some parts of the study area are less likely to be used (e.g., aquatic areas for terrestrial animals) or where landscape permeability differs (e.g., forest bats tend not to fly over open areas). More broadly, these results show how geographic profiling can be used to target antipoaching interventions more effectively and more efficiently and to develop management strategies and conservation plans in a range of conservation scenarios.     

Rank aggregation of local expert knowledge for conservation planning of the critically endangered saola

There has been much recent interest in using local knowledge and expert opinion for conservation planning, particularly for hard‐to‐detect species. Although it is possible to ask for direct estimation of quantities such as population size, relative abundance is easier to estimate. However, an expert's knowledge is often geographically restricted relative to the area of interest. Combining (or aggregating) experts’ assessments of relative abundance is difficult when each expert only knows a part of the area of interest. We used Google's PageRank algorithm to aggregate ranked abundance scores elicited from local experts through a rapid rural‐appraisal method. We applied this technique to conservation planning for the saola (Pseudoryx nghetinhensis), a poorly known bovid. Near a priority landscape for the species, composed of 3 contiguous protected areas, we asked groups of local people to indicate relative abundances of saola and other species by placing beans on community maps. For each village, we used this information to rank areas within the knowledge area of that village for saola abundance. We used simulations to compare alternative methods to aggregate the rankings from the different villages. The best‐performing method was then used to produce a single map of relative abundance across the entire landscape, an area larger than that known to any one village. This map has informed prioritization of surveys and conservation action in the continued absence of direct information about the saola.     

A multiscale hierarchical Markov transition matrix model for generating and analyzing thematic raster maps

A model is described for generating hierarchically scaled spatial pattern as represented in a thematic raster map. The model involves a series of Markov transition matrices, one for each level in the scaling hierarchy. In full generality, the model allows the transition matrices to be different at each level, potentially making available a large number of parameters for landscape characterization. The model is self-similar when the transition matrices are all equal. A method is presented for fitting the model to data that take the form of a single-resolution thematic raster map. Explicit analytic solutions are obtained for the fitted parameters. The fitting method is based on a relationship between the hierarchical transitions in the model and spatial transitions at varying distance scales in the data map, a categorical analogy of the geostatistical variogram.     

Use of Inverse Spatial Conservation Prioritization to Avoid Biological Diversity Loss Outside Protected Areas

Globally expanding human land use sets constantly increasing pressure for maintenance of biological diversity and functioning ecosystems. To fight the decline of biological diversity, conservation science has broken ground with methods such as the operational model of systematic conservation planning (SCP), which focuses on design and on‐the‐ground implementation of conservation areas. The most commonly used method in SCP is reserve selection that focuses on the spatial design of reserve networks and their expansion. We expanded these methods by introducing another form of spatial allocation of conservation effort relevant for land‐use zoning at the landscape scale that avoids negative ecological effects of human land use outside protected areas. We call our method inverse spatial conservation prioritization. It can be used to identify areas suitable for economic development while simultaneously limiting total ecological and environmental effects of that development at the landscape level by identifying areas with highest economic but lowest ecological value. Our method is not based on a priori targets, and as such it is applicable to cases where the effects of land use on, for example, individual species or ecosystem types are relatively small and would not lead to violation of regional or national conservation targets. We applied our method to land‐use allocation to peat mining. Our method identified a combination of profitable production areas that provides the needed area for peat production while retaining most of the landscape‐level ecological value of the ecosystem. The results of this inverse spatial conservation prioritization are being used in land‐use zoning in the province of Central Finland.     

Winners and losers: analysing post‐disaster spatial economic demand shift

Disasters produce winners and losers. This paper evaluates such winners and losers in a spatial context. The hypothesis is that, because of severe damage to the core disaster area and the constraints associated with the cost of transportation, economic demand would shift to the immediate edge of the disaster zone where either minor or no damage is observed. Empirical analysis of growth patterns in counties/parishes in the states of Alabama, Louisiana, and Mississippi in the United States after Hurricane Katrina (August 2005) verified the spatial demand shift hypothesis. The study found that the post‐Katrina core disaster area became a ‘doughnut hole’ of low income and employment growth, surrounded by a ring of high growth counties/parishes on the edge of the hole. The short‐run adjustment in growth rates may have altered permanently the spatial distribution of employment and income both at the core and in the areas at the edge.     

Ozone Dry Deposition Velocities for Coastal Waters

Air-sea exchange rates for ozone were measured by the eddy correlation technique at a site on the north Norfolk coast in the UK. The average surface resistance to ozone uptake was found to be, r_s(O₃) = 1,000 ± 100 s m^-1. Micrometeorological measurements of trace gas fluxes to ocean surfaces are rare but a review of available measurements suggests that we can constrain sea water surface resistance for ozone to between 1,000 (Regener (1974), and this work) and 1,890 s m^-1 (Lenschow et al., 1982), yielding surface deposition velocities between 0.53 and 1.0 mm s^-1. These values are more than an order of magnitude greater than can be explained by laboratory determined mass accommodation coefficients for ozone to water. The importance of dry deposition with respect to process air-sea exchange models is highlighted. A trend in surface deposition velocity with wind speed was also observed supporting a surface chemical enhancement mechanism of ozone uptake which in turn is enhanced by near surface mixing processes.     

The Capacity of Australia's Protected‐Area System to Represent Threatened Species

Abstract: The acquisition or designation of new protected areas is usually based on criteria for representation of different ecosystems or land‐cover classes, and it is unclear how well‐threatened species are conserved within protected‐area networks. Here, we assessed how Australia's terrestrial protected‐area system (89 million ha, 11.6% of the continent) overlaps with the geographic distributions of threatened species and compared this overlap against a model that randomly placed protected areas across the continent and a spatially efficient model that placed protected areas across the continent to maximize threatened species’ representation within the protected‐area estate. We defined the minimum area needed to conserve each species on the basis of the species’ range size. We found that although the current configuration of protected areas met targets for representation of a given percentage of species’ ranges better than a random selection of areas, 166 (12.6%) threatened species occurred entirely outside protected areas and target levels of protection were met for only 259 (19.6%) species. Critically endangered species were among those with the least protection; 12 (21.1%) species occurred entirely outside protected areas. Reptiles and plants were the most poorly represented taxonomic groups, and amphibians the best represented. Spatial prioritization analyses revealed that an efficient protected‐area system of the same size as the current protected‐area system (11.6% of the area of Australia) could meet representation targets for 1272 (93.3%) threatened species. Moreover, the results of these prioritization analyses showed that by protecting 17.8% of Australia, all threatened species could reach target levels of representation, assuming all current protected areas are retained. Although this amount of area theoretically could be protected, existing land uses and the finite resources available for conservation mean land acquisition may not be possible or even effective for the recovery of threatened species. The optimal use of resources must balance acquisition of new protected areas, where processes that threaten native species are mitigated by the change in ownership or on‐ground management jurisdiction, and management of threatened species inside and outside the existing protected‐area system.     

The Importance of Being Spatial (and Reserved): Assessing Northern Spotted Owl Habitat Relationships with Hierarchical Bayesian Models

Abstract:  Regional conservation planning increasingly draws on habitat suitability models to support decisions regarding land allocation and management. Nevertheless, statistical techniques commonly used for developing such models may give misleading results because they fail to account for 3 factors common in data sets of species distribution: spatial autocorrelation, the large number of sites where the species is absent (zero inflation), and uneven survey effort. We used spatial autoregressive models fit with Bayesian Markov Chain Monte Carlo techniques to assess the relationship between older coniferous forest and the abundance of Northern Spotted Owl nest and activity sites throughout the species' range. The spatial random-effect term incorporated in the autoregressive models successfully accounted for zero inflation and reduced the effect of survey bias on estimates of species–habitat associations. Our results support the hypothesis that the relationship between owl distribution and older forest varies with latitude. A quadratic relationship between owl abundance and older forest was evident in the southern portion of the range, and a pseudothreshold relationship was evident in the northern portion of the range. Our results suggest that proposed changes to the network of owl habitat reserves would reduce the proportion of the population protected by up to one-third, and that proposed guidelines for forest management within reserves underestimate the proportion of older forest associated with maximum owl abundance and inappropriately generalize threshold relationships among subregions. Bayesian spatial models can greatly enhance the utility of habitat analysis for conservation planning because they add the statistical flexibility necessary for analyzing regional survey data while retaining the interpretability of simpler models.     

漫湾电站库区降雨侵蚀力时空变化

漫湾水电站是澜沧江水能梯级开发的第一个干流大型水电站，加强库区水土流失治理与监督监测尤为必要，而降雨侵蚀力的时空分布规律研究则是实现区域土壤侵蚀定量监测预报的重要基础。根据有关降雨侵蚀力的计算方法，利用漫湾电站库区4个测站1980～2000年的逐月平均降雨资料，估算了其降雨侵蚀力R值的时空分布规律及其变化特征。结果表明：漫湾电站库区多年平均降雨侵蚀力在1 9336～3 9727 MJ·mm/hm2·h；R值的年内变化显著，且较大值集中分布在雨季的5月～10月，平均R值占全年的867%，尤其6～8月连续3个月的降雨侵蚀力平均占全年侵蚀力的一半以上；R值的年际变化显示20世纪90年代漫湾电站库区降雨侵蚀力比80年代平均增加2835 MJ·mm/hm2·h；R值的空间分布上以凤庆站点的年降雨侵蚀力最大；南涧站点的年降雨侵蚀力最小，但是其年际波动幅度较大。全面地分析了漫湾电站库区降雨侵蚀力R值的时空变化特征，为该地区有效防止与监测水土流失情况、更好地安置水电站工程移民提供参考。     

Tracking the response of industrial fishing fleets to large marine protected areas in the Pacific Ocean

Large marine protected areas (MPAs) of unprecedented size have recently been established across the global oceans, yet their ability to meet conservation objectives is debated. Key areas of debate include uncertainty over nations’ abilities to enforce fishing bans across vast, remote regions and the intensity of human impacts before and after MPA implementation. We used a recently developed vessel tracking data set (produced using Automatic Identification System detections) to quantify the response of industrial fishing fleets to 5 of the largest MPAs established in the Pacific Ocean since 2013. After their implementation, all 5 MPAs successfully kept industrial fishing effort exceptionally low. Detected fishing effort was already low in 4 of the 5 large MPAs prior to MPA implementation, particularly relative to nearby regions that did not receive formal protection. Our results suggest that these large MPAs may present major conservation opportunities in relatively intact ecosystems with low immediate impact to industrial fisheries, but the large MPAs we considered often did not significantly reduce fishing effort because baseline fishing was typically low. It is yet to be determined how large MPAs may shape global ocean conservation in the future if the footprint of human influence continues to expand. Continued improvement in understanding of how large MPAs interact with industrial fisheries is a crucial step toward defining their role in global ocean management.