Modelling potential biotope composition on a regional scale revealed that climate variables are stronger drivers than soil variables

Aim

Environmental conditions define the suitability of an area for biotopes, and any area can be suitable for several biotopes. However, most previous studies modelled the distribution of single biotopes ignoring the potential co-occurrence of biotopes in one area, which limits the usefulness of such models for conservation and restoration planning. In this study, we described the potential biotope composition of an area in response to environmental conditions.

Location

Bavaria, Federal State of Germany.

Methods

Based on the Bavarian biotope mapping data, we modelled the distribution of 29 terrestrial biotopes based on six climate variables and six chemical and four physical soil properties using the species distribution modelling algorithm Maxent.

Results

For most biotopes, we found that climate variables were more important than soil variables for the biotope distribution and that the area of the predicted biotope distribution was larger than the observed distribution. The potential biotope composition illustrated that while 8% of the area in Bavaria was not sufficiently suitable for any analysed biotope, 92% of the modelled area in Bavaria was suitable for at least one biotope, 84% for two and 77% for at least three biotopes. The difference in suitability between the most suitable biotopes in composition was minor. Further, over one-quarter of the modelled area was suitable for 6–8 different biotopes.

Main Conclusions

Our study showed that considering a composition of potentially suitable biotopes in a raster cell, instead of only the most suitable biotope, provides valuable information to identify conservation priorities and restoration opportunities.     

基于Maxent模型的檵木分布格局模拟

应用最大熵模型(Maxent)模拟檵木(Loropetalum chinense)在末次间冰期(last inter glacial, LIG)、末次盛冰期(last glacial maximum, LGM)和当代(Present)等不同时期的中国潜在分布格局,分析影响其分布的主导生物气候因子。结果显示:(1)历史气候的变迁,檵木由末次间冰期经末次盛冰期进入当代,适生区面积呈现增加趋势。当代适生区面积占比最大,适生程度也较高;(2)训练数据和测试数据的AUC值分别为0.947和0.954,均达到了极高的精度;(3)刀切法检测表明,影响檵木分布的主导环境因子依次为bio14(最干月份平均降雨量)、bio17(极干季降雨量)、为bio19(极冷季平均降雨量)和bio15(湿度变化方差),其适生值范围分别是23—93 mm, 98—300 mm, 110—350 mm和42%—65%;(4)较纬度而言,经度是影响我国檵木分布格局的主要因子;(5)我国檵木当代的潜在地理分布主要在北回归线以北的区域,总面积为162.55万km²,占国土总面积的16.93%,高适生区集中于...     

中国五味子分布范围及气候变化影响预测

结合文献资料、标本记录和实际调查绘制了中国五味子分布图,并基于五味子分布范围和21个环境因子,运用Maxent软件预测了IPCC A2和A1B两种气候变化情景下21世纪50和80年代中国五味子分布范围.结果表明:五味子分布于中国15省/市(区),涉及151个县,随着纬度和经度的降低,面积逐渐减少,黑龙江、辽宁、内蒙古和吉林4省(区)是五味子主要分布区域;五味子在中国的潜在分布面积为145.12×104 km2,较好生境面积占48.6％,主要分布在长白山山脉、大兴安岭、小兴安岭以及河北省与辽宁省相邻区域;最佳生境面积仅占0.3％,主要分布在辽宁省的宽甸满族自治县、本溪满族自治县、桓仁满族自治县以及吉林省的安图县、和龙市和内蒙古自治区牙克石市.在A1B和A2两种情景下,未来五味子潜在分布区逐渐减少,A2情景的五味子潜在分布区下降比率大于AIB情景;至21世纪50年代,A1B和A2情景下五味子潜在分布区将缩减为当前潜在分布区面积的84.0％和81.5％;至21世纪80年代,A2情景下五味子潜在分布区仅为当前的0.5％,B2情景下五味子潜在分布区减至当前的1/2.     

气候变化情境下木荷潜在地理分布及生态适宜性分析

木荷（Schima superba）是中国南方常见的速生阔叶耐火树种之一,在生态修复和维持环境稳定方面具有重要作用,因而预测其潜在适生区变化具有重要意义。基于Maxent模型,结合158条木荷在中国的有效分布记录和筛选后的8个生物气候变量,预测木荷现代和2041-2060年3种气候排放浓度情景下木荷的潜在分布区。Maxent模型的可靠性以受试者工作特征曲线来判断,综合气候因子的贡献率、置换重要值和刀切法检验,来分析并探讨制约木荷地理分布的重要气候因子。结果表明：（1） Maxent模型训练和测试数据的AUC值分别为0.936±0.001和0.943±0.008,表明模型的预测精度极高;（2）现代木荷潜在地理分布的总适生区面积198.87×10⁴ km²,占中国国土面积的20.7%,主要位于在中国长江以南的大部分地区,包括福建、浙江、台湾、江西、湖南、广东、海南、广西、贵州、云南、重庆,以及四川、河南和安徽部分区域;（3）制约木荷潜在地理分布的重要生物气候因子为降水因子（最干月降水量26-214 mm、年降水量800-2500 mm和最湿季降水量590-1030 mm）和温度因子（气温年变化8.5-28℃）;（4）使用Maxent模型模拟的木荷适生区面积大于其实际分布面积,暗示着木荷人工林在未来有较大的发展潜力。本研究结果可为木荷种质资源收集和人工林种植奠定理论基础,对维持区域性生态系统安全和稳定、缓解气候变化和2060年实现碳中和目标具有战略性意义。     

基于MAXENT模型和Arc GIS预测蜡梅适生域在中国的潜在分布

蜡梅(Chimonanthus praecox)是我国二级濒危珍稀植物,是重要的冬季传统观花植物。利用已报道的246个分布点和worldclim中提取的19个气候因子,基于最大熵(Maxent)模型和地理信息系统(Arc Gis)对蜡梅在中国的潜在适生区分布进行预测分析,采用受试者工作特征(ROC)曲线对预测结果进行检验和评价。结果表明蜡梅的潜在适生范围相对集中,主要集中在西南的四川盆地、华中、华东及华北的中南部地区,其他地区则适应性较低。温度是影响蜡梅分布的决定性因子,其中,当最冷季度平均温度接近0℃,等温性范围为0—10℃,降雨量变异系数约为45时,蜡梅的分布概率最大。与原分布区相比较,蜡梅的适生区范围正向中国东部地区和北部地区迁移。ROC曲线检验评价结果表明,Maxent模型的ROC曲线分析法的面积(AUC)值为0.986,预测结果达到了极高精度。     

Dynamic distribution modelling of the swamp tigertail dragonfly Synthemis eustalacta (Odonata: Anisoptera: Synthemistidae) over a 20-year bushfire regime

1. Intensity and severity of bushfires in Australia have increased over the past few decades due to climate change, threatening habitat loss for numerous species. Although the impact of bushfires on vertebrates is well-documented, the corresponding effects on insect taxa are rarely examined, although they are responsible for key ecosystem functions and services. Understanding the effects of bushfire seasons on insect distributions could elucidate long-term impacts and patterns of ecosystem recovery.
2. Here, the authors investigated the effects of recent bushfires, land-cover change, and climatic variables on the distribution of a common and endemic dragonfly, the swamp tigertail (Synthemis eustalacta) (Burmeister, 1839), which inhabits forests that have recently undergone severe burning. The authors used a temporally dynamic species distribution modelling approach that incorporated 20 years of community-science data on dragonfly occurrence and predictors based on fire, land cover, and climate to make yearly predictions of suitability. The authors also compared this to an approach that combines multiple temporally static models that use annual data.
3. The authors found that for both approaches, fire-specific variables had negligible importance for the models, while the percentage of tree and non-vegetative cover were most important. The authors also found that the dynamic model outperformed the static ones, based on cross-validation omission rate. Model predictions indicated temporal variation in area and spatial arrangement of suitable habitat, but no patterns of habitat expansion, contraction, or shifting.
4. These results highlight not only the efficacy of dynamic modelling to capture spatiotemporal variables such as vegetation cover for an endemic insect species, but also provide a novel approach to mapping species distributions with sparse locality records.