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.     

水下振动台关键技术的研究

本文从理论和实践两方面分析研究了水下振动台的若干关键技术问题,主要包括运动部件的设计、冷却系统的设计、密封系统的设计、压力平衡系统的设计等。解决了水下振动台设计所存在的难题。     

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.     

Practical actions for applied systematic conservation planning

Systematic conservation planning is intended to inform spatially explicit decision making. Doing so requires that it be integrated into complex regulatory and governance processes, and there are limited instances where this has been achieved effectively. South Africa is a global leader in the application of conservation plans, the outputs of which are widely used for spatial planning and decision making in many spheres of government. We aimed to determine how conservation planning in the country progressed from theory to implementation, and to identify practical actions that enabled this transition, by assessing temporal trends in the characteristics of conservation plans (1990–2017, n = 94). Since 2010 conservation planning has entered an operational period characterized by government leadership of plans, administrative rather than ecological planning domains, decreasing size of planning units, increasing emphasis on end-user products, and scheduled revision of plans. Key actions that enabled this progression include transitioning leadership of plans from scientists to practitioners, building capacity within implementing agencies, creating opportunities to integrate plans in legislative processes, establishing a strong community of practice, adopting implementation-focused methods, and balancing standardization with innovation. Learning from this model will allow other countries, particularly those with a similar megadiverse, developing context, to operationalize conservation planning into spatial planning and decision making.     

Understanding the effects of different social data on selecting priority conservation areas

Conservation success is contingent on assessing social and environmental factors so that cost‐effective implementation of strategies and actions can be placed in a broad social–ecological context. Until now, the focus has been on how to include spatially explicit social data in conservation planning, whereas the value of different kinds of social data has received limited attention. In a regional systematic conservation planning case study in Australia, we examined the spatial concurrence of a range of spatially explicit social values and land‐use preferences collected using a public participation geographic information system and biological data. We used Zonation to integrate the social data with the biological data in a series of spatial‐prioritization scenarios to determine the effect of the different types of social data on spatial prioritization compared with biological data alone. The type of social data (i.e., conservation opportunities or constraints) significantly affected spatial prioritization outcomes. The integration of social values and land‐use preferences under different scenarios was highly variable and generated spatial prioritizations 1.2–51% different from those based on biological data alone. The inclusion of conservation‐compatible values and preferences added relatively few new areas to conservation priorities, whereas including noncompatible economic values and development preferences as costs significantly changed conservation priority areas (48.2% and 47.4%, respectively). Based on our results, a multifaceted conservation prioritization approach that combines spatially explicit social data with biological data can help conservation planners identify the type of social data to collect for more effective and feasible conservation actions.     

The Effectiveness of Surrogate Taxa for the Representation of Biodiversity

Abstract: Biodiversity is too complex to measure directly, so conservation planning must rely on surrogates to estimate the biodiversity of sites. The species richness of selected taxa is often used as a surrogate for the richness of other taxa. Surrogacy values of taxa have been evaluated in diverse contexts, yet broad trends in their effectiveness remain unclear. We reviewed published studies testing the ability of species richness of surrogate taxa to capture the richness of other (target) taxa. We stratified studies into two groups based on whether a complementarity approach (surrogates used to select a combination of sites that together maximize total species richness for the taxon) or a richness‐hotspot approach (surrogates used to select sites containing the highest species richness for the taxon) was used. For each comparison of one surrogate taxon with one target, we used the following predictor variables: biome, spatial extent of study area, surrogate taxon, and target taxon. We developed a binary response variable based on whether the surrogate taxon provided better than random representation of the target taxon. For studies that used an evaluation approach that was not based on better than random representation of target taxa, we based the response variable on the interpretation of results in the original study. We performed a categorical regression to elucidate trends in the effectiveness of surrogate taxa with regard to each of the predictor variables. A surrogate was 25% more likely to be effective with a complementarity approach than with a hotspot approach. For hotspot‐based approaches, biome, extent of study, surrogate taxon, and target taxon significantly influenced effectiveness of the surrogate. For complementarity‐based approaches, biome, extent, and surrogate taxon significantly influenced effectiveness of the surrogate. For all surrogate evaluations, biome explained the greatest amount of variation in surrogate effectiveness. From most to least, extent, surrogate taxon, and target taxon explained the most variation after biome. Surrogate taxa were most effective in grasslands and in some cases boreal zones, deserts, and tropical forests; surrogate taxa also were more effective in studies examining larger areas. Herpetofauna were the most effective taxon as both surrogate and target when a richness‐hotspot approach was used; however, herpetofauna were analyzed in fewer studies, so this result is tentative. For complementarity approaches, taxa that are easy to measure and tend to have a large number of habitat specialists distributed collectively across broad environmental gradients (e.g., plants, birds, and mammals) were the most effective surrogates.