Assessing New Zealand fern diversity from spatial predictions of species assemblages

The utility of explicit spatial predictions for biodiversity assessment is investigated with New Zealand fern flora. Distributions of 43 species were modelled from climatic and landform variables and predicted across New Zealand using generalised additive models (GAM). An original package of functions called generalised regression analysis and spatial prediction (GRASP) was developed to perform the analyses. On average, for the 43 models, the contributions of environmental variables indicate that mean annual temperature is the most important factor at this broad regional scale. Both annual solar radiation and its seasonality had higher correlations than temperature seasonality. Measures of water availability such as ratio of rainfall to potential evapotranspiration, air saturation deficit and soil water deficit presented significant contributions. Lithology was a better predictor than slope and drainage. These results are similar to those obtained from analyses of the distributions of New Zealand tree species and are consistent with the hypothesis that both tree and fern diversity are highest on sites conducive to high productivity. In order to identify hotspots of fern diversity, spatial predictions of individual species were summed up. The resulting map gave a very similar result to the direct prediction of their corresponding richness (number of species by plot out of 43 spp.). As a consequence, and where individual species models were not all available, the number of species within different species assemblages was directly modelled. Predicted richness hotspots of total species (out of 122 spp.), selected species (out of 43 and 21 spp.) and common species (out of 23 spp.) present very similar spatial patterns and are highly correlated. Richness of uncommon species (out of 39 spp.) was also accurately predicted, but presented a different spatial pattern. The number of rare species (out of 60 spp.) was not correctly modelled. Even though the lack of data for rare species clearly limits the application of this approach, fern community composition of more common species can be partially reconstructed from individual species predictions. This case study offers therefore a consistent approach not only for biodiversity hotspots identification, but also for setting targets to biodiversity assessment and restoration programs.     

Regression models for spatial prediction: their role for biodiversity and conservation

This paper is an introduction to a Special Issue on regression models for spatial predictions published in Biodiversity and Conservation following an international workshop held in Switzerland in 2001 (http://leba.unige.ch/workshop). This introduction describes how the exponential growth in computing power has improved our ability to reach spatially explicit assessment of biodiversity and to develop cost-effective conservation management. New questions arising from these modern approaches are listed, while papers presenting examples of applications are briefly introduced.     

内蒙古锡林河流域植被多样性特点及其与气候因子的关系

本文在地理信息系统技术支持下,利用景观生态学的原理和方法,研究了锡林河流域植被多样性的空间分布规律及其与气候因子的关系,得到了植被丰富度和Ｓｈａｎｎｏｎ－Ｗｉｅｎｅｒ植被多样性指数的空间分布图;对以上两个指标以及年均降雨量和年均积温进行趋势面分析的结果表明：１）锡林河流域植被丰富度和Ｓｈａｎｎｏｎ－Ｗｉｅｎｅｒ植被多样性指数呈明显的自东南往西北的减少趋势;２）水热因子是影响锡林河流域植被多样性空间分布格局的重要因子,其分布与年均降雨量在整个流域内存在较强的正效应关系,同年均积温的正效应关系局限在地势较平坦的西北部;３）锡林河流域水热因子的空间分布规律相似,皆呈现出从东南向西北减少的趋势,但二者对地形变化的反应不一样,温度比降水更为灵敏。     

Prediction of plant species distribution in lowland river valleys in Belgium: modelling species response to site conditions

In ecological modelling, limitations in data and their applicability for predictive modelling are more rule than exception. Often modelling has to be performed on sub-optimal data, as explicit and controlled collection of (more) appropriate data would not be feasible. An example of predictive ecological modelling is given with application of generalized additive and generalized linear models fitted to presence–absence records of plant species and site condition data from four nutrient-poor Flemish lowland valleys. Standard regression procedures are used for modelling, although explanatory and response data do not meet all the assumptions implicit in these procedures. Data were non-randomly collected and are spatially autocorrelated; model residuals retain part of that correlation. The scale of most site-condition records does not match the scale of the response variable (species distribution). Hence, interpolated and up-scaled explanatory variables are used. Data are aggregated from distinct phytogeographical regions to allow for generalized models, applicable to a wider population of river valleys in the same region. Nevertheless, ecologically sound models are obtained, which predict well the distribution of most plant species for the Flemish river valleys considered.     

东海水域中上层鱼类资源的空间异质性

定量描述鱼类分布的空间变异,有利于从生态学意义上理解其空间分布及其与环境的关系,本文利用地理信息系统将东海区中上层鱼类资源密度空间化,运用空间自相关指数Geary c和变异函数理论分析其空间自相关和空间变异,东海区中上层鱼类资源空间分布平均场的Geary c指数为0．25,各向同性随机变异占总变异的19．1％,表明其空间分布具有较高的自相关特性,空间分布上各向变异不一致,其中45°和135°方向上变异曲线斜率急剧变化,表明这两个方向上存在重要的环境动力过程,各年份平均资源密度与相关变异(C)正相关,而与随机变异(C0)不存在相关,表明年际密度变化主要由空间自相关引起,变异曲线分维数(D)与密度呈负相关,说明密度的增加是由于鱼类在空间上的集聚程度增高引起的。     

中国壳斗科植物空间多样性格局研究

采用地理信息系统技术,制作空间分布图、从空间上计算多样性格局指数,研究中国壳斗科植物属、种的空间多样性分布格局。结果显示,云南南部、广西北部和广东北部的属、种数量均较多,是中国壳斗科植物多样性的重要分布地区,甘肃南部、陕西南部、河南西部及南部是壳斗科植物向南、向北扩散的重要通道;从多样性指数来看,种的多样性指数值均比属的值高,但均匀度指数却是属的值高;当属或种的数量为1时,其所占面积、占景观的比例、斑块数量、最大斑块指数、景观形状指数均最大,随着属或种的数量逐渐增加,其多样性明显提高,但其各项指标基本呈依次降低的趋势。通过对壳斗科植物空间多样性格局进行量化研究,获取了中国壳斗科植物空间多样性分布规律及多样性格局数量特点,利用地理信息系统技术可以使多样性研究体现出空间性和定量化的特征。     

Colonization rules and spatial distributions in ecology

Because they are intuitive and mathematically straight-forward, colonization rules are often used to model spatial patterns in ecology. Colonization rules assign individuals to categories according to the locations of previous colonists. In this note, a compact introduction to colonization rules in ecology is presented with implications for autocorrelation and spatial distributions. I use the colonization rule approach to unify a diverse set of spatial and species diversity analyses, exploring future extensions to incorporate greater realism.     

芦芽山鬼箭锦鸡儿灌丛营养特征及土壤养分分布规律

研究了芦芽山自然保护区亚高山草甸带鬼箭锦鸡儿(Caragana jubata)灌丛营养成分季节性变化和土壤养分分布规律.结果表明,鬼箭锦鸡儿具有很高的营养价值,粗蛋白含量达20.27%,粗纤维含量33.83%,灰分5.12%,同时含有丰富的Ca、Fe、Mn等中微量元素,是亚高山草场家畜的优质饲料来源.鬼箭锦鸡儿营养成分呈明显的季节性变化规律:从5月开始,随着灌丛生长发育,体内粗蛋白、灰分和矿质元素含量呈上升趋势,7月(开花期)达到最高,然后逐步降低.为适应海拔高、气温低、土层薄的亚高山草甸带生境, 鬼箭锦鸡儿灌丛周围的土壤养分向灌丛中心聚集,灌丛中心的土壤电导率、有机质、全氮、速效磷和有效钾分别较灌丛边缘高18.8%、16.4%、18.7%、16.6%和8.4%,形成了明显的\"肥岛效应\".鬼箭锦鸡儿灌丛根际土壤有机质、全氮出现富集,有效磷、速效钾和速效铁、锰在根际周围出现明显亏缺,表明鬼箭锦鸡儿具有高效固氮和吸收利用土壤养分的能力.     

LIVES: a new habitat modelling technique for predicting the distribution of species’ occurrences using presence-only data based on limiting factor theory

Predictive modelling techniques using presence-only data have attracted increasing attention because they can provide information on species distributions and their potential habitat for conservation and ecosystem management. However, the existing predictive modelling techniques have several limitations. Here, we propose a novel predictive modelling technique, Limiting Variable and Environmental Suitability (LIVES), for predicting the distributions and potential habitats of species using presence-only data. It is based on limiting factor theory, which postulates that the occurrence of a species is only determined by the factor that most limits its distribution. LIVES predicts the suitability of a candidate grid cell for a species in terms of limiting environmental factor. It also predicts the most limiting factor or the potential limiting factor at the grid cell. The environmental factors can be climatic, geological, biological and any other relevant environmental factors, whether quantitative or qualitative. The predicted habitats consist of the current distribution of the species and the potentially suitable areas for the species where there is currently no record of occurrence. We also compare several properties of LIVES and other predictive modelling techniques. On the basis of 1,000 simulations, the average predictions of LIVES are more accurate than the two other commonly used modelling techniques (BIOCLIM and DOMAIN) for presence-only data.     

攀枝花苏铁种群生态地理分布、分布格局及采挖历史的研究

 对攀枝花苏铁(Cycas panzhihuaensis)种群的地理分布、数量特征、空间分布格局和毁坏历史进行了野外调查和研究。结果表明：攀枝花苏铁种群的自然栖息地是相互隔离和片断化的。已发现的13个自然种群中,8个分布在金沙江河谷,5个种群分布在金沙江支流河谷;最大的种群位于攀枝花市郊,占有面积约3.80km2。79年以来的商业采挖使8个种群灭绝,种群分布区从30700km2减少到8800km2,种群占有面积从11.50km2减少到6.30km2。3个被研究种群的分布格局为集群分布,以幼苗聚集程度最大,随着年龄的增加,聚集程度逐渐下降。     

印度块菌在未来气候变化情景下的空间分布模式——以云南省为例

以印度块菌（Tuber indicum）丰产区云南省为例,利用地理信息系统和物种分布模型,并通过影响印度块菌分布的主要环境因子和气候因子,共同模拟现在及未来生境分布模式。结果表明结合环境因子和气候因子,在建模过程中能提高模型预测准确度,在几类物种分布模型中,MAXENT模型具有最优的拟合效果。在大的空间尺度上,年降水,最湿季度降水,最冷月份最低温、地貌类型及土壤类型对印度块菌的生境分布影响最大。此外,在模型模拟的A2和B2未来气候变化情景下,印度块菌未来的新增生境均呈北上趋势,且B2情景下生境的适生程度低于A2情景。     

Regional vegetation mapping in Australia: a case study in the practical use of statistical modelling

Conservation evaluation of large areas ( > 10 000 km²) in Australia requires detailed mapping of vegetation types. Predicting the original vegetation cover of extensive cleared areas in an explicit, consistent and repeatable manner necessitates the use of statistical modelling. This paper describes an integrated approach to vegetation mapping in a region of New South Wales, Australia. The approach uses separate statistical models for each tree and shrub species to predict the vegetation composition in each grid cell in a geographic information system (GIS). Allocation of these grid cells to communities allows communities that no longer exist in the remaining remnants of woodland to be defined. Examples of use of this information for management are presented. This paper addresses the practical considerations which constrain the way statistical modelling can be used for vegetation mapping in an applied project. Constraints include: (1) data availability (use of sampling to fill gaps in existing data), (2) the effects of cover abundance values, (3) availability of GIS predictors, (4) data management, (5) current generalised additive model methods and (6) prediction methods. Careful attention to the practicality of all components of a vegetation mapping study is essential if modern methods are to be applied in regional studies which must provide functional products for land managers with limited resources, skills and finances at their disposal.