A link between ecological diversity indices and measures of biodiversity

The practice of environmental planning and protection frequently necessitates the quantification of ecological diversity. Traditional ‘ecological diversity indices’ are based on the abundances of species present. However, such indices are insensitive to taxonomic or similar differences. With equal species abundances they measure the species richness (species number) only. Conversely, so-called ‘biodiversity indices’ are based on species differences, but are insensitive to the abundance conditions. The quadratic entropy index is the only ecological diversity index, the value of which reflects both the differences ‘and’ abundances of the species. When a species list is given without abundance data, then, using the quadratic entropy index and postulating equal abundances, one gets the only biodiversity index derived from a traditional ecological index of diversity. Its extensive form is identical with the sum of differences or distances between the species present. This index trivially satisfies set monotonicity, an important property for biodiversity indices.     

A new approach to spatial entropy measures

Entropy is widely employed in many applied sciences to measure the heterogeneity of observations. Recently, many attempts have been made to build entropy measures for spatial data, in order to capture the influence of space over the variable outcomes. The main limit of these developments is that all indices are computed conditional on a single distance and do not cover the whole spatial configuration of the phenomenon under study. Moreover, most of them do not satisfy the desirable additivity property between local and global spatial measures. This work reviews some recent developments, based on univariate distributions, and compares them to a new approach which considers the properties of entropy measures linked to bivariate distributions. This perspective introduces substantial innovations. Firstly, Shannon’s entropy may be decomposed into two terms: spatial mutual information, accounting for the role of space in determining the variable outcome, and spatial global residual entropy, summarizing the remaining heterogeneity carried by the variable itself. Secondly, these terms both satisfy the additivity property, being sums of partial entropies measuring what happens at different distance classes. The proposed indices are used for measuring the spatial entropy of a marked point pattern on rainforest tree species. The new entropy measures are shown to be more informative and to answer a wider set of questions than the current proposals of the literature.     

人类活动对上海市生物多样性空间格局的影响

为了揭示人类活动对城市化地区生物多样性空间格局的影响及其景观生态学机制,文章将上海市作为研究对象,选择3个人类活动指标、3个主要类型生态系统的4个景观特征指标与8个生物多样性指标,探讨人类活动强度、野生动植物生境景观特征及生物多样性三者之间的相互关系。结果显示,人口增长和城市扩张对上海市生物多样性的空间格局产生了显著影响。在上海地区,人口密度较高、交通较为发达的区域,湿地和农田的景观连续性较低,生物多样性也较低,外来入侵物种丰度较高。这表明在快速城市化过程中,人类活动通过改变野生动植物栖息地景观质量来对区域生物多样性产生影响。本研究还显示,经济发展并非一定对生物多样性具有负面影响。因此,在保持经济发展的同时,通过优化产业结构与加强生物多样性管理,可实现对生物多样性有效保护。     

Linkages between measures of biodiversity and community resilience in Pacific Island agroforests

Designing agroecosystems that are compatible with the conservation of biodiversity is a top conservation priority. However, the social variables that drive native biodiversity conservation in these systems are poorly understood. We devised a new approach to identify social–ecological linkages that affect conservation outcomes in agroecosystems and in social‐ecological systems more broadly. We focused on coastal agroforests in Fiji, which, like agroforests across other small Pacific Islands, are critical to food security, contain much of the country's remaining lowland forests, and have rapidly declining levels of native biodiversity. We tested the relationships among social variables and native tree species richness in agroforests with structural equation models. The models were built with data from ecological and social surveys in 100 agroforests and associated households. The agroforests hosted 95 native tree species of which almost one‐third were endemic. Fifty‐eight percent of farms had at least one species considered threatened at the national or international level. The best‐fit structural equation model (R² = 47.8%) showed that social variables important for community resilience—local ecological knowledge, social network connectivity, and livelihood diversity—had direct and indirect positive effects on native tree species richness. Cash‐crop intensification, a driver of biodiversity loss elsewhere, did not negatively affect native tree richness within parcels. Joining efforts to build community resilience, specifically by increasing livelihood diversity, local ecological knowledge, and social network connectivity, may help conservation agencies conserve the rapidly declining biodiversity in the region.     

Isomorphic chain graphs for modeling spatial dependence in ecological data

Graphical models (alternatively, Bayesian belief networks, path analysis models) are increasingly used for modeling complex ecological systems (e.g., Lee, In: Ferson S, Burgman M(eds) Quantative methods for conservation biology. Springer, Berlin Heilin Heideslperk New York, pp.127–147, 2000; Borsuk et al., J Water Res Plann Manage 129:271–282, 2003). Their implementation in this context leverages their utility in modeling interrelationships in multivariate systems, and in a Bayesian implementation, their intuitive appeal of yielding easily interpretable posterior probability estimates. However, methods for incorporating correlational structure to account for observations collected through time and/or space—features of most ecological data—have not been widely studied; Haas et al. (AI Appl 8:15–27, 1994) is one exception. In this paper, an “isomorphic” chain graph (ICG) model is introduced to account for correlation between samples by linking site-specific Bayes network models. Several results show that the ICG preserves many of the Markov properties (conditional and marginal dependencies) of the site-specific models. The ICG model is compared with a model that does not account for spatial correlation. Data from several stream networks in the Willamette River valley, Oregon (USA) are used. Significant correlation between sites within the same stream network is shown with an ICG model.     

Hierarchical spatial point process analysis for a plant community with high biodiversity

A complex multivariate spatial point pattern of a plant community with high biodiversity is modelled using a hierarchical multivariate point process model. In the model, interactions between plants with different post-fire regeneration strategies are of key interest. We consider initially a maximum likelihood approach to inference where problems arise due to unknown interaction radii for the plants. We next demonstrate that a Bayesian approach provides a flexible framework for incorporating prior information concerning the interaction radii. From an ecological perspective, we are able both to confirm existing knowledge on species’ interactions and to generate new biological questions and hypotheses on species’ interactions.

A state-space model approach to optimum spatial sampling design based on entropy

We consider the spatial sampling design problem for a random field X. This random field is in general assumed not to be directly observable, but sample information from a related variable Y is available. Our purpose in this paper is to present a state-space model approach to network design based on Shannon's definition of entropy, and describe its main points with regard to some of the most common practical problems in spatial sampling design. For applications, an adaptation of Ko et al.'s (1995) algorithm for maximum entropy sampling in this context is provided. We illustrate the methodology using piezometric data from the Velez aquifer (Malaga, Spain). © Rapid Science 1998     

A nearly neutral model of biodiversity

S. P. Hubbell's unified neutral theory of biodiversity has stimulated much new thinking about biodiversity. However, empirical support for the neutral theory is limited, and several observations are inconsistent with the predictions of the theory, including positive correlations between traits associated with competitive ability and species abundance and correlations between species diversity and ecosystem functioning. The neutral theory can be extended to explain these observations by allowing species to differ slightly in their competitive ability (fitness). Here, we show that even slight differences in fecundity can greatly reduce the time to extinction of competitors even when the community size is large and dispersal is spatially limited. In this case, species richness is dramatically reduced, and a markedly different species abundance distribution is predicted than under pure neutrality. In the nearly neutral model, species co-occur in the same community not because of, but in spite of, ecological differences. The more competitive species with higher fecundity tend to have higher abundance both in the metacommunity and in local communities. The nearly neutral perspective provides a theoretical framework that unites the sampling model of the neutral theory with theory of biodiversity affecting ecosystem function.     

Effects of ecotourism on forest loss in the Himalayan biodiversity hotspot based on counterfactual analyses

Ecotourism is developing rapidly in biodiversity hotspots worldwide, but there is limited and mixed empirical evidence that ecotourism achieves positive biodiversity outcomes. We assessed whether ecotourism influenced forest loss rates and trajectories from 2000 to 2017 in Himalayan temperate forests. We compared forest loss in 15 ecotourism hubs with nonecotourism areas in 4 Himalayan countries. We used matching statistics to control for local-level determinants of forest loss, for example, population density, market access, and topography. None of the ecotourism hubs was free of forest loss, and we found limited evidence that forest-loss trajectories in ecotourism hubs were different from those in nonecotourism areas. In Nepal and Bhutan, differences in forest loss rates between ecotourism hubs and matched nonecotourism areas did not differ significantly, and the magnitude of the estimated effect was small. In India, where overall forest loss rates were the lowest of any country in our analysis, forest loss rates were higher in ecotourism hubs than in matched nonecotourism areas. In contrast, in China, where overall forest loss rates were highest, forest loss rates were lower in ecotourism hubs than where there was no ecotourism. Our results suggest that the success of ecotourism as a forest conservation strategy, as it is currently practiced in the Himalaya, is context dependent. In a region with high deforestation pressures, ecotourism may be a relatively environmentally friendly form of economic development relative to other development strategies. However, ecotourism may stimulate forest loss in regions where deforestation rates are low.     

Finite population properties of individual predictors based on spatial patterns

In this study a conceptual framework for assessing the statistical properties of a non-stochastic spatial interpolator is developed through the use of design-based finite population inference tools. By considering the observed locations as the result of a probabilistic sampling design, we propose a standardized weighted predictor for spatial data starting from a deterministic interpolator that usually does not provide uncertainty measures. The information regarding the coordinates of the spatial locations is known at the population level and is directly used in constructing the weighting system. Our procedure captures the spatial pattern by means of the Euclidean distances between locations, which are fixed and do not require any further assessment after the sample has been drawn. The predictor for any individual value turns in a ratio of design-based random quantities. We illustrate the predictor design-based statistical properties, i.e. asymptotically p-unbiasedness and p-consistency, for simple random sampling without replacement. An application to a couple of environmental datasets is presented, for assessing predictor performances in correspondence of different population characteristics. A comparison with the equivalent non-spatial predictor is presented.     

A comparative study on intertidal faunal biodiversity of selected beaches of Mumbai coast

Comparative study has been done to examine the biodiversity and ecological status of the intertidal region of Tata Institute of Fundamental Research (TIFR), Bandstand and National Centre for Performing Arts (NCPA) rocky beaches in Mumbai, West coast of India. A total of 50 species of intertidal organisms were recorded from these shores. Shannon and Simpson's diversity index, Margalefs richness index and Pielou's evenness index indicated different level of ecological state of the shore in different months. Dendrograms and 2-D non metric MDS ordination from Bray-Curtis similarity matrix of occurrence of intertidal organisms from these sites showed highest similarity and combination pattern of occurrence between Nerita oryzarum and Planaxis sulcatus in TIFR and Bandstand shore. Nerita oryzarum and Tactarius malaccanus at NCPA shore. Abundance/biomass comparison (ABC) method of determining level of disturbance also pointed towards the polluted status of these shores. Study concludes that though these beaches are highly disturbed due to anthropogenic activities, they still support a rich intertidal biodiversity which need immediate attention for protection and conservation.     

基于空间马尔科夫链的关中地区生态安全时空演变分析

生态系统内部和生态系统之间都不是封闭的,各要素间均存在着相互作用。利用已获得的陕西关中地区生态安全格网化评价结果数据,运用空间马尔科夫链对该区域的生态安全时空演变进行了分析,得出以下四个结论：①区域背景在关中地区生态安全趋同时空演变过程中起着相当重要作用;②不同区域背景在区域生态安全等级转移中所起的作用也各不相同;③一个区域生态安全等级向上或向下转移的概率与该区域和周围邻居之间的差异程度不成比例;④空间马尔可夫转移概率矩阵为＂区域趋同的时空演变＂现象提供了空间上的解释。实践表明,空间马尔可夫链方法为定量分析地理环境对区域生态安全变化的空间效应提供了方法依据,值得进一步研究和讨论。     

Effect of streambed substrate on macroinvertebrate biodiversity

Macroinvertebrates are important components of stream ecosystems, and are often used as indicator species for the assessment of river ecology. Numerous studies have shown that substrate is the primary physical environmental variable affecting the taxa richness and density of macroinvertebrates. The aim of this work is to study the effects of the characteristics of streambed substrate, such as grain size, shape, and roughness, on the composition and biodiversity of macroinvertebrates. A field experiment was done on the Juma River, a second-order mountain stream in northern China. Substrata of cobbles, hewn stones, pebbles, coarse sand, and fine sand were used to replace the original gravel and sand bed in a stretch of 30 m in length. The sampling results indicated that the macroinvertebrate assemblage is significantly affected by the grain size, porosity and interstitial dimension of the substrate, while it is rarely affected by the shape and the surface roughness of the experimental substrata. Macroinvertebrate compositions in cobbles and hewn stones were stable and changed least over time. The taxa richness and density of individuals in the substrata of cobbles, hewn stones, and pebbles are much higher than in those of the coarse sand and fine sand.     

Growth of non-English-language literature on biodiversity conservation

English is widely recognized as the language of science, and English-language publications (ELPs) are rapidly increasing. It is often assumed that the number of non-ELPs is decreasing. This assumption contributes to the underuse of non-ELPs in conservation science, practice, and policy, especially at the international level. However, the number of conservation articles published in different languages is poorly documented. Using local and international search systems, we searched for scientific articles on biodiversity conservation published from 1980 to 2018 in English and 15 non-English languages. We compared the growth rate in publications across languages. In 12 of the 15 non-English languages, published conservation articles significantly increased every year over the past 39 years, at a rate similar to English-language articles. The other three languages showed contrasting results, depending on the search system. Since the 1990s, conservation science articles in most languages increased exponentially. The variation in the number of non-English-language articles identified among the search systems differed markedly (e.g., for simplified Chinese, 11,148 articles returned with local search system and 803 with Scopus). Google Scholar and local literature search systems returned the most articles for 11 and 4 non-English languages, respectively. However, the proportion of peer-reviewed conservation articles published in non-English languages was highest in Scopus, followed by Web of Science and local search systems, and lowest in Google Scholar. About 20% of the sampled non-English-language articles provided no title or abstract in English; thus, in theory, they were undiscoverable with English keywords. Possible reasons for this include language barriers and the need to disseminate research in countries where English is not widely spoken. Given the known biases in statistical methods and study characteristics between English- and non-English-language studies, non-English-language articles will continue to play an important role in improving the understanding of biodiversity and its conservation.     

Effectiveness of vegetation‐based biodiversity offset metrics as surrogates for ants

Biodiversity offset schemes are globally popular policy tools for balancing the competing demands of conservation and development. Trading currencies for losses and gains in biodiversity value at development and credit sites are usually based on several vegetation attributes combined to yield a simple score (multimetric), but the score is rarely validated prior to implementation. Inaccurate biodiversity trading currencies are likely to accelerate global biodiversity loss through unrepresentative trades of losses and gains. We tested a model vegetation multimetric (i.e., vegetation structural and compositional attributes) typical of offset trading currencies to determine whether it represented measurable components of compositional and functional biodiversity. Study sites were located in remnant patches of a critically endangered ecological community in western Sydney, Australia, an area representative of global conflicts between conservation and expanding urban development. We sampled ant fauna composition with pitfall traps and enumerated removal by ants of native plant seeds from artificial seed containers (seed depots). Ants are an excellent model taxon because they are strongly associated with habitat complexity, respond rapidly to environmental change, and are functionally important at many trophic levels. The vegetation multimetric did not predict differences in ant community composition or seed removal, despite underlying assumptions that biodiversity trading currencies used in offset schemes represent all components of a site's biodiversity value. This suggests that vegetation multimetrics are inadequate surrogates for total biodiversity value. These findings highlight the urgent need to refine existing offsetting multimetrics to ensure they meet underlying assumptions of surrogacy. Despite the best intentions, offset schemes will never achieve their goal of no net loss of biodiversity values if trades are based on metrics unrepresentative of total biodiversity.     

基于探索性空间分析的中国氮氧化物排放强度研究

采用全局和局部空间相关分析方法研究中国省际氮氧化物排放强度的空间自相关性和空间异质性.结果表明:2003—2011年全局自相关Moran'sⅠ值均为正数,表明省域之间氮氧化物排放强度呈现正相关的空间集聚分布,2003—2011年氮氧化物排放强度的空间聚集程度在不断加强;氮氧化物排放强度的空间异质性主要表现为氮氧化物排放强度的“冷点”区相对稳定,主要集中在东部、南部沿海和长江中游地区,“热点”区主要集中在东北、大西南、大西北和黄河中游地区;氮氧化物排放强度的空间差异与区域经济发展水平、产业结构和能源利用效率等因素密切相关,基于空间探索性数据分析方法研究我国氮氧化物排放强度的空间异质性,为国家制定差异化的区域氮氧化物减排目标和氮氧化物排放调控政策提供有益参考.     

土地利用变化对生物多样性的影响

土地利用变化对生物多样性影响是生物多样性受到威胁的重要因素.文章对土地利用变化对基因多样性、物种多样性、生态系统多样性影响方面的研究进行了总结分析,并提出了新的展望.土地利用变化对基因多样性的影响涉及了对物种生境的隔离、农牧业活动对物种改良和生境条件的改变方面,目前还主要集中在对少数物种繁殖过程方面影响的研究;土地利用变化对物种多样性影响包括对物种优势度和丰富度、种间关系、物种分布格局、物种入侵和灭绝方面的影响,目前对物种丰富性和多样性影响方面研究较多,对物种灭绝、物种入侵和种间关系影响方面的研究极少,且还限于大型动物和植物,对微生物和小型动植物研究却很少;土地利用变化对生态系统的影响涉及了对生态系统结构组成及分布方面的影响.另外,目前缺少土地利用变化对基因多样性、物种多样性和生态系统多样性综合影响方面的研究,难以量化和预测土地利用变化对生物多样性影响效应.未来需要综合考虑基因多样性、物种多样性和生态系统多样性方面,系统开展土地利用变化对生物多样性影响的趋势和机制方面的研究,定量预测土地利用变化对生物多样性的影响.     

A spatial clustering perspective on autocorrelation and regionalization

We revisit one of the classical problems in geography and cartography where multiple observations on a lattice (N) need to be grouped into many fewer regions (G), especially when this number of desired regions is unknown a priori. Since an optimization through all possible aggregations is not feasible, a hierarchical classification scheme is proposed with an objective function sensitive to spatial pattern. The objective function to be minimized during the assignment of observations to regions (classification) consists of two terms: the first characterizes accuracy and the second, model complexity. For the latter, we introduce a spatial measure that characterizes the number of homogeneous patches rather than the usual number of classes. A simulation study shows that such a classification procedure is less sensitive to random and spatially correlated error (noise) than non-spatial classification. We also show that for conditional autoregressive error (noise) fields the optimal partitioning is the one that has the highest within-units generalized Moran coefficient. The classifier is implemented in ArcView to demonstrate both a socio-economic and an environmental application to illustrate some potential applications.

The effect of biodiversity on the hantavirus epizootic

We analyze a mathematical model of the epizootic of Hantavirus in mice populations, including the effect of species that compete with the host. We show that the existence of the second species has an important consequence for the prevalence of the infectious agent in the host. When the two mice species survive in the ecosystem, the competitive pressure of the second species may lead to reduction or complete elimination of the prevalence of infection. The transition between the disappearance of the infection and its presence occurs at a critical value of the competitor's population, resembling a second-order phase transition in a statistical system. The results provide a rigorous framework for the study of the impact of biodiversity in the propagation of infectious diseases, and further lends itself to future experimental verification.