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

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

广东省土地利用驱动下红树林潜在生境预测

为探索土地利用变化对红树林潜在生境分布的影响,融合MaxEnt模型和Dyna-CLUE模型,建立了土地利用驱动下红树林生境变化的定量预测方法.以中国红树林分布面积最大的广东省作为研究区,利用MaxEnt模型模拟红树林在自然条件下的理论适生区,采用Dyna-CLUE模型预测2030年的三种土地利用变化情景,最后将模拟的土地利用格局作为限制条件估算未来可供红树林生境分布的空间.结果表明,2020年广东省红树林潜在生境面积约34531hm²,2030年趋势情景下湿地将减少58.61%,红树林潜在生境面积将退化至24375hm²;可持续发展情景下通过改进土地利用策略并开展一定规模的退塘还湿,红树林潜在生境面积将增加至38125hm²;生态保护情景下,如能开展全面的生态保护和恢复,红树林潜在生境面积可达到47525hm².本研究的研究方法可有效预测不同海岸带土地利用驱动下红树林潜在生境的空间变化.研究结果发现,不同土地利用政策会对红树林潜在生境分布造成明显影响;通过改进政策,可显著提升红树林潜在生境的面积和完整性.本结论可为区域红树林保护与生境修复的空间规划及政策制定等提供科学支持.     

Null models reveal preferential sampling, spatial autocorrelation and overfitting in habitat suitability modelling

Nowadays, species are driven to extinction at a high rate. To reduce this rate it is important to delineate suitable habitats for these species in such a way that these areas can be suggested as conservation areas. The use of habitat suitability models (HSMs) can be of great importance for the delineation of such areas. In this study MaxEnt, a presence-only modelling technique, is used to develop HSMs for 223 nematode species of the Southern Bight of the North Sea. However, it is essential that these models are beyond discussion and they should be checked for potential errors. In this study we focused on two categories (1) errors which can be attributed to the database such as preferential sampling and spatial autocorrelation and (2) errors induced by the modelling technique such as overfitting, In order to quantify these adverse effects thousands of nulls models were created. The effect of preferential sampling (i.e. some areas where visited more frequenty than others) was investigated by comparing model outcomes based from null models sampling the actual sampling stations and null models sampling the entire mapping area (Raes and ter Steege, 2007). Overfitting is exposed by a fivefold cross-validation and the influence of spatial autocorrelation is assessed by separating test and training sets in space. Our results clearly show that all these effects are present: preferential sampling has a strong effect on the selection of non-random species models. Crossvalidation seems to have less influence on the model selection and spatial autocorrelation is also strongly present. It is clear from this study that predefined thresholds are not readily applicable to all datasets and additional tests are needed in model selection.     

气候变化背景下京津冀地区濒危水鸟潜在适宜区模拟及保护空缺分析

明确濒危水鸟栖息地分布并加以保护对于维持水鸟物种多样性和提高湿地环境质量具有重要意义.自1980年以来京津冀地区水鸟数量出现较大波动,为了分析濒危水鸟潜在分布区域及其变化特征,借助GIS平台和MaxEnt模型,基于2015年濒危水鸟"出现点"信息,定量识别了影响京津冀地区濒危水鸟分布的主要驱动因素和贡献率,并预测了2050年RCP2.6、RCP4.5、RCP8.5（依次代表低、中、高3种CO₂浓度排放模式）3种气候情景下濒危水鸟的潜在适宜区分布和保护空缺规律.结果表明:①京津冀地区濒危水鸟共有9种,东方白鹳、遗鸥和黑鹳3种濒危水鸟潜在适宜区面积较大.东方白鹳和遗鸥适宜区主要集中于环渤海湾沿岸和北京市中南部,黑鹳则主要集中于北京市南部房山区和东北部.②与2015年相比,2050年RCP2.6、RCP4.5和RCP8.5三种气候情景下濒危水鸟适宜区面积均较大,相应适宜区面积增幅依次为96.24%、103.94%和65.51%,适宜区空间分布上向西南和东北方向扩张.③国家自然保护区对濒危水鸟潜在适宜区和热点区的覆盖率较低,相较天津市,河北省和北京市对这两个区域的覆盖不足.④在京津冀地区尺度下,不同情景下保护区覆盖濒危水鸟适宜区比例依次为基准情景（1.26%）> RCP8.5情景（1.11%）> RCP2.6情景（0.70%）> RCP4.5情景（0.29%）,保护区覆盖热点区比例依次为RCP4.5情景（0.83%）>基准情景（0.77%）> RCP8.5情景（0.08%）> RCP2.6情景（0）.研究显示,以单个水鸟为单位分析濒危水鸟潜在适宜区分布格局,能够精准有效地揭示国家自然保护区对濒危水鸟的覆盖情况.      

Current and future effectiveness of the Natura 2000 network for protecting plant species in Sardinia: a nice and complex strategy in its raw state?

Sardinia hosts 186 endemic plant species and represents an important centre for Mediterranean biodiversity. In view of the threats facing its flora, 27 terrestrial vascular plants have been listed in international regulations and 124 sites designated for species and habitat conservation. This study analyses gaps in the Natura 2000 network and the current and future distribution of four representative plants. Each plant population was georeferenced and the effectiveness of the Natura 2000 network was compared according to conservation status and distribution. Future species distributions were modelled by considering current climatic conditions and future scenarios. In apparent discordance with other results, we found that the Natura 2000 network represents most plant species well. This research shows a forward-looking survey on the regional effectiveness of protection measures which led us to confirm the need to enhance the current state of the Natura 2000 network by implementing local legislation and regulations.     

川西高原积雪稳定性分布格局及其驱动因子分析

在气候变暖的背景下,川西高原积雪出现剧烈变化,对地区水循环过程、生态系统以及社会经济带来严重影响。基于MODIS积雪遥感数据以及环境因子数据,通过构建稳定度指标及最大熵模型探讨川西高原不同稳定性积雪的空间分布格局及其驱动因子,并对不同稳定性积雪的适宜分布区进行分析,结果表明：（1）川西高原大多数地区的积雪属于高度不稳定性积雪,其他稳定性积雪在川西高原分布面积较小;（2）川西高原积雪在海拔越高的地方稳定性越好;（3）不同稳定性积雪分布格局的影响因素存在差异,海拔和降水是影响稳定性积雪分布格局的主要因素。     

Role of Tibetan Buddhist Monasteries in Snow Leopard Conservation

The snow leopard (Panthera uncia) inhabits the rugged mountains in 12 countries of Central Asia, including the Tibetan Plateau. Due to poaching, decreased abundance of prey, and habitat degradation, it was listed as endangered by the International Union for Conservation of Nature in 1972. Current conservation strategies, including nature reserves and incentive programs, have limited capacities to protect snow leopards. We investigated the role of Tibetan Buddhist monasteries in snow leopard conservation in the Sanjiangyuan region in China's Qinghai Province on the Tibetan Plateau. From 2009 to 2011, we systematically surveyed snow leopards in the Sanjiangyuan region. We used the MaxEnt model to determine the relation of their presence to environmental variables (e.g., elevation, ruggedness) and to predict snow leopard distribution. Model results showed 89,602 km² of snow leopard habitat in the Sanjiangyuan region, of which 7674 km² lay within Sanjiangyuan Nature Reserve's core zones. We analyzed the spatial relation between snow leopard habitat and Buddhist monasteries and found that 46% of monasteries were located in snow leopard habitat and 90% were within 5 km of snow leopard habitat. The 336 monasteries in the Sanjiangyuan region could protect more snow leopard habitat (8342 km²) through social norms and active patrols than the nature reserve's core zones. We conducted 144 household interviews to identify local herders’ attitudes and behavior toward snow leopards and other wildlife. Most local herders claimed that they did not kill wildlife, and 42% said they did not kill wildlife because it was a sin in Buddhism. Our results indicate monasteries play an important role in snow leopard conservation. Monastery‐based snow leopard conservation could be extended to other Tibetan Buddhist regions that in total would encompass about 80% of the global range of snow leopards. Papel de los Monasterios Budistas Tibetanos en la Conservación del Leopardo de las Nieves     

Ecological‐Niche Modeling and Prioritization of Conservation‐Area Networks for Mexican Herpetofauna

Abstract: One of the most important tools in conservation biology is information on the geographic distribution of species and the variables determining those patterns. We used maximum‐entropy niche modeling to run distribution models for 222 amphibian and 371 reptile species (49% endemics and 27% threatened) for which we had 34,619 single geographic records. The planning region is in southeastern Mexico, is 20% of the country's area, includes 80% of the country's herpetofauna, and lacks an adequate protected‐area system. We used probabilistic data to build distribution models of herpetofauna for use in prioritizing conservation areas for three target groups (all species and threatened and endemic species). The accuracy of species‐distribution models was better for endemic and threatened species than it was for all species. Forty‐seven percent of the region has been deforested and additional conservation areas with 13.7% to 88.6% more native vegetation (76% to 96% of the areas are outside the current protected‐area system) are needed. There was overlap in 26 of the main selected areas in the conservation‐area network prioritized to preserve the target groups, and for all three target groups the proportion of vegetation types needed for their conservation was constant: 30% pine and oak forests, 22% tropical evergreen forest, 17% low deciduous forest, and 8% montane cloud forests. The fact that different groups of species require the same proportion of habitat types suggests that the pine and oak forests support the highest proportion of endemic and threatened species and should therefore be given priority over other types of vegetation for inclusion in the protected areas of southeastern Mexico.