中国蚂蚁丰富度地理分布格局及其与环境因子的关系

物种丰富度分布格局及其形成机制的研究对于生物多样性保护具有重要意义。为了了解中国蚂蚁物种丰富度分布格局,利用中国省级尺度蚂蚁物种分布数据和环境信息,结合GIS和数理统计方法,探讨蚂蚁物种丰富度的地理分布格局与环境因子之间的关系。研究结果表明:(1)蚂蚁丰富度随纬度增加呈逐渐递减趋势,但缺乏显著的经度梯度。丰富度最高的地区主要集中在南方省份,我国北方、西北干旱区和青藏高原北部地区丰富度较低;(2)简单线性回归分析表明,能量、水分和季节性因素中,影响蚂蚁物种丰富度最强的因子分别为最冷月均温(TEMmin)(R2adj=0.532)、年均降水量(PREC)(R2adj=0.376)和年温度变化范围(TEMvar)(R2adj=0.539),而单个生境异质性因子对蚂蚁物种丰富度的影响均不显著;(3)最优模型由年均温(TEM)、海拔变化范围(ELErange)和年温度变化范围(TEMvar)组成,能够解释68.4%的蚂蚁丰富度地理分异。鉴于海拔变化范围更多地反映与温度相关的生境异质性,因此温度是限制中国蚂蚁分布的最重要因素。另外,分析结果还表明,海南、贵州、江西、四川、安徽和山西等6省蚂蚁区系调查最不充分,是未来发现蚂蚁新分布的热点地区。     

The relationship between wealth and biodiversity: A test of the Luxury Effect on bird species richness in the developing world

The Luxury Effect hypothesizes a positive relationship between wealth and biodiversity within urban areas. Understanding how urban development, both in terms of socio‐economic status and the built environment, affects biodiversity can contribute to the sustainable development of cities, and may be especially important in the developing world where current growth in urban populations is most rapid. We tested the Luxury Effect by analysing bird species richness in relation to income levels, as well as human population density and urban cover, in landscapes along an urbanization gradient in South Africa. The Luxury Effect was supported in landscapes with lower urbanization levels in that species richness was positively correlated with income level where urban cover was relatively low. However, the effect was reversed in highly urbanized landscapes, where species richness was negatively associated with income level. Tree cover was also positively correlated with species richness, although it could not explain the Luxury Effect. Species richness was negatively related to urban cover, but there was no association with human population density. Our model suggests that maintaining green space in at least an equal proportion to the built environment is likely to provide a development strategy that will enhance urban biodiversity, and with it, the positive benefits that are manifest for urban dwellers. Our findings can form a key contribution to a wider strategy to expand urban settlements in a sustainable way to provide for the growing urban population in South Africa, including addressing imbalances in environmental justice across income levels and racial groups.     

Quantifying biodiversity: procedures and pitfalls in the measurement and comparison of species richness

Species richness is a fundamental measurement of community and regional diversity, and it underlies many ecological models and conservation strategies. In spite of its importance, ecologists have not always appreciated the effects of abundance and sampling effort on richness measures and comparisons. We survey a series of common pitfalls in quantifying and comparing taxon richness. These pitfalls can be largely avoided by using accumulation and rarefaction curves, which may be based on either individuals or samples. These taxon sampling curves contain the basic information for valid richness comparisons, including category–subcategory ratios (species-to-genus and species-to-individual ratios). Rarefaction methods – both sample-based and individual-based – allow for meaningful standardization and comparison of datasets. Standardizing data sets by area or sampling effort may produce very different results compared to standardizing by number of individuals collected, and it is not always clear which measure of diversity is more appropriate. Asymptotic richness estimators provide lower-bound estimates for taxon-rich groups such as tropical arthropods, in which observed richness rarely reaches an asymptote, despite intensive sampling. Recent examples of diversity studies of tropical trees, stream invertebrates, and herbaceous plants emphasize the importance of carefully quantifying species richness using taxon sampling curves.     

Forecasting insect species richness scores in poorly surveyed territories: the case of the Portuguese dung beetles (Col. Scarabaeinae)

Large-scale biodiversity assessment of faunal distribution is needed in poorly sampled areas. In this paper, Scarabaeinae dung beetle species richness in Portugal is forecasted from a model built with a data set from areas identified as well sampled. Generalized linear models are used to relate the number of Scarabaeinae species in each Portuguese UTM 50 × 50 grid square with a set of 25 predictor variables (geographic, topographic, climatic and land cover) extracted from a geographic information system (GIS). Between-squares sampling effort unevenness, spatial autocorrelation of environmental data, non-linear relationships between variables and an assessment of the models' predictive power, the main shortcomings in geographic species richness modelling, are addressed. This methodological approach has proved to be reliable and accurate enough in estimating species richness distribution, thus providing a tool to identify areas as potential targets for conservation policies in poorly inventoried countries.     

The effects of pitfall trap diameter on ant species richness (Hymenoptera: Formicidae) and species composition of the catch in a semi-arid eucalypt woodland

Abstract Ants play an important role in Australian biodiversity and environmental impact assessments, with pitfall-trapping being the principal sampling method. However, the relationship between trap diameter and ant species catch has not been investigated in the context of survey design. Using four different trap diameters, each at a density of one trap per 100 m2, the present study asks three questions: (i) given an equal number of traps, do traps with larger diameters catch more species than smaller-diameter traps?; (ii) do traps with small diameters bias against large or rare species?; (iii) for equal area of the trap mouth, do small but more numerous traps catch more species than fewer but large traps? A total of 84 species were sampled within the 1600 m2 study site, with numbers of species for trap diameters of: 18mm (46 species), 42mm (56 species), 86mm (62 species) and 135mm (64 species). At equal trap density, 18 mm traps caught significantly fewer species than larger traps. Traps of 86 mm and 135mm were no more efficient than 42mm traps. Only 86mm and 135mm traps caught all species > 10mm in length (6 species). For equal area of the trap mouth, small traps were more efficient than large traps. Differences in the catch of the different-sized traps were due primarily to different capture rates of the rare species (40 species): 18mm traps caught 25% of rare species, 42 mm caught 41%, 86 mm caught 44% and 135 mm caught 52%. The role of rare ant species in environmental impact studies is discussed.     

Type and spatial structure of distribution data and the perceived determinants of geographical gradients in ecology: the species richness of African birds

Aim Studies exploring the determinants of geographical gradients in the occurrence of species or their traits obtain data by: (1) overlaying species range maps; (2) mapping survey‐based species counts; or (3) superimposing models of individual species’ distributions. These data types have different spatial characteristics. We investigated whether these differences influence conclusions regarding postulated determinants of species richness patterns. Location Our study examined terrestrial bird diversity patterns in 13 nations of southern and eastern Africa, spanning temperate to tropical climates. Methods Four species richness maps were compiled based on range maps, field‐derived bird atlas data, logistic and autologistic distribution models. Ordinary and spatial regression models served to examine how well each of five hypotheses predicted patterns in each map. These hypotheses propose productivity, temperature, the heat–water balance, habitat heterogeneity and climatic stability as the predominant determinants of species richness. Results The four richness maps portrayed broadly similar geographical patterns but, due to the nature of underlying data types, exhibited marked differences in spatial autocorrelation structure. These differences in spatial structure emerged as important in determining which hypothesis appeared most capable of explaining each map's patterns. This was true even when regressions accounted for spurious effects of spatial autocorrelation. Each richness map, therefore, identified a different hypothesis as the most likely cause of broad‐scale gradients in species diversity. Main conclusions Because the ‘true’ spatial structure of species richness patterns remains elusive, firm conclusions regarding their underlying environmental drivers remain difficult. More broadly, our findings suggest that care should be taken to interpret putative determinants of large‐scale ecological gradients in light of the type and spatial characteristics of the underlying data. Indeed, closer scrutiny of these underlying data — here the distributions of individual species — and their environmental associations may offer important insights into the ultimate causes of observed broad‐scale patterns.     

Macroevolution of hoverflies (Diptera: Syrphidae): the effect of using higher‐level taxa in studies of biodiversity,and correlates of species richness

We test a near‐complete genus level phylogeny of hoverflies (Diptera: Syrphidae) for consistency with a null model of clade growth having uniform probabilities of speciation and extinction among contemporaneous species. The phylogeny is too unbalanced for this null model. Importantly, the degree of imbalance in the phylogeny depends on whether the phylogeny is analysed at the genus level or species level, suggesting that genera ought not to be used uncritically as surrogates for species in large‐scale evolutionary analyses. Tests for a range of morphological, life‐history and ecological correlates of diversity give equivocal results, but suggest that high species‐richness may be associated with sexual selection and diet breadth. We find no correlation between species‐richness and either body size or reproductive rate.