广西亚热带森林及空旷地土壤温度的比较研究

运用对比研究的方法,于1980—1991年,对广西亚热带不同地理区域主要森林类型及空旷地的土壤温度进行了定位观測研究。揭示了这些区域的森林土壤温度的生态效应,为森林土壤的生态效益评估及合理开发利用提供了科学依据。     

Body condition and the grouping behavior of brood-caring female common eiders (<Emphasis Type="Italic">Somateria mollissima</Emphasis>)

Both theoretical and empirical work has shown that group size increases with increasing ecological constraints on solitary breeding. Ecological constraints refer to extrinsic factors such as availability of breeding sites, food or mates. Common eider (Somateria mollissima) females pool their broods and share brood-rearing duties, or rear broods alone. Females are often in poor condition at hatching, as incubation is accomplished without feeding, and variation in body condition is largely environmentally induced and thus unpredictable. We found that the intensity of and duration of parental care that females provide is positively correlated with their body condition at hatching. This suggests that body condition is an ecological constraint on successful solitary breeding. We further observed that group productivity in common eider broods is a decelerating function of the number of tending females. As predicted, females in poorer condition (i.e., facing stronger ecological constraints) were found in larger groups. This result is straightforward if solitary tenders can enter any group at no cost. However, if entry is group-controlled, stable groups of non-relatives are predicted not to occur when per capita reproduction declines with group size. The N-person staying incentive model permits groups to form under these conditions, because reproduction is unevenly divided between dominants and subordinates in the group. We discuss the plausibility of these alternative models of group size for understanding the grouping behavior of brood-caring female common eiders.Communicated by M. Webster     

Limitations of Biodiversity Databases: Case Study on Seed-Plant Diversity in Tenerife, Canary Islands

Abstract:  Databases on the distribution of species can be used to describe the geographic patterns of biodiversity. Nevertheless, they have limitations. We studied three of these limitations: (1) inadequacy of raw data to describe richness patterns due to sampling bias, (2) lack of survey effort assessment (and lack of exhaustiveness in compiling data about survey effort), and (3) lack of coverage of the geographic and environmental variations that affect the distribution of organisms. We used a biodiversity database (BIOTA-Canarias) to analyze richness data from a well-known group (seed plants) in an intensively surveyed area (Tenerife Island). Observed richness and survey effort were highly correlated. Species accumulation curves could not be used to determine survey effort because data digitalization was not exhaustive, so we identified well-sampled sites based on observed richness to sampling effort ratios. We also developed a predictive model based on the data from well-sampled sites and analyzed the origin of the geographic errors in the obtained extrapolation by means of a geographically constrained cross-validation. The spatial patterns of seed-plant species richness obtained from BIOTA-Canarias data were incomplete and biased. Therefore, some improvements are needed to use this database (and many others) in biodiversity studies. We propose a protocol that includes controls on data quality, improvements on data digitalization and survey design to improve data quality, and some alternative data analysis strategies that will provide a reliable picture of biodiversity patterns.     

毛竹混交林主要种群多维生态位特征

应用生态位空间分割法，分别考虑资源利用率与否测定毛竹混交林多维资源空间中主要种群多维生态位宽度及多维生态位重叠，结果表明：考虑资源利用率与否对多维生态位宽度的测定有较大的影响，毛竹混交林中主要种群的多维生态位宽度与物种的生物学特性及竞争力密切相关，同一生境中物种的多维生态位重叠可通过生态位分化而减少竞争，研究毛竹混交林主要种群多维生态位特征对毛竹混交林营造具有指导作用．表8参24．     

Modelling the responses of the Lagoon of Venice ecosystem to variations in physical forcings

A Finite Element Ecological Model for the Lagoon of Venice (VELFEEM) has been used to test the responses of the Lagoon of Venice ecosystem to variations in physical conditions.The model is obtained by coupling a finite element hydrodynamic model, that computes the velocity fields of water, an energetic model to compute the water temperature fields, and an ecological model that simulates the dynamic of phytoplankton, zooplankton, nutrients (ammonia, nitrate and phosphate) organic detritus (organic nitrogen, organic phosphorous and CBOD) and dissolved oxygen.The transport model is a two-dimensional barotropic finite element model which allows for a better resolution of the lagoon morphology.The ecological model has been developed by starting from the ecological module EUTRO of WASP (Water Analysis Simulation System released by US EPA), and by adapting it to the peculiarity of the Lagoon of Venice.A reference condition has been identified by running a 1-year simulation under climatologic condition. Then, the sensitivity to physical forcing (tide and wind) and to the input of macronutrients has been investigated, by comparing model predictions of spatial and temporal evolution of major state variables and of an aggregate index of Water Quality Trophic Index (TRIX).     

Can environmental heterogeneity explain individual foraging variation in wild bottlenose dolphins (<Emphasis Type="Italic">Tursiops</Emphasis> sp.)?

Because behavioral variation within and among populations may result from ecological, social, genetic and phenotypic differences, identifying the mechanism(s) responsible is challenging. Observational studies typically examine social learning by excluding ecological and genetic factors, but this approach is insufficient for many complex behaviors associated with substantial environmental variation. Indian Ocean bottlenose dolphins (Tursiops sp.) in Shark Bay, Western Australia show individual differences in foraging tactics, including possible tool use with marine sponges and social learning may be responsible for this diversity. However, the contributions of ecological factors to the development of these foraging tactics were not previously investigated. Here, we determined the relationship between ecological variables and foraging tactics and assessed whether differences in habitat use could explain individual differences in foraging tactics. We monitored 14 survey zones to identify how foraging tactics were spatially distributed and matched behavioral data to the ecological variables within each zone. Three of four foraging tactics were significantly correlated with ecological characteristics such as seagrass biomass, water depth, presence of marine sponges and season. Further, individual differences in habitat use were associated with some tactics. However, several tactics overlapped spatially and previous findings suggest demographic and social factors also contribute to the individual variation in this population. This study illustrates the importance of environmental heterogeneity in shaping foraging diversity and shows that investigating social learning by ruling out alternative mechanisms may often be too simplistic, highlighting the need for methods incorporating the relative contributions of multiple factors.     

Bayesian areal wombling via adjacency modeling

Recently, public health professionals and other geostatistical researchers have shown increasing interest in boundary analysis, the detection or testing of zones or boundaries that reveal sharp changes in the values of spatially oriented variables. For areal data (i.e., data which consist only of sums or averages over geopolitical regions), Lu and Carlin (Geogr Anal 37: 265–285, 2005) suggested a fully model-based framework for areal wombling using Bayesian hierarchical models with posterior summaries computed using Markov chain Monte Carlo (MCMC) methods, and showed the approach to have advantages over existing non-stochastic alternatives. In this paper, we develop Bayesian areal boundary analysis methods that estimate the spatial neighborhood structure using the value of the process in each region and other variables that indicate how similar two regions are. Boundaries may then be determined by the posterior distribution of either this estimated neighborhood structure or the regional mean response differences themselves. Our methods do require several assumptions (including an appropriate prior distribution, a normal spatial random effect distribution, and a Bernoulli distribution for a set of spatial weights), but also deliver more in terms of full posterior inference for the boundary segments (e.g., direct probability statements regarding the probability that a particular border segment is part of the boundary). We illustrate three different remedies for the computing difficulties encountered in implementing our method. We use simulation to compare among existing purely algorithmic approaches, the Lu and Carlin (2005) method, and our new adjacency modeling methods. We also illustrate more practical modeling issues (e.g., covariate selection) in the context of a breast cancer late detection data set collected at the county level in the state of Minnesota.     

Risk-Based Viable Population Monitoring

Abstract:  We describe risk-based viable population monitoring, in which the monitoring indicator is a yearly prediction of the probability that, within a given timeframe, the population abundance will decline below a prespecified level. Common abundance-based monitoring strategies usually have low power to detect declines in threatened and endangered species and are largely reactive to declines. Comparisons of the population's estimated risk of decline over time will help determine status in a more defensible manner than current monitoring methods. Monitoring risk is a more proactive approach; critical changes in the population's status are more likely to be demonstrated before a devastating decline than with abundance-based monitoring methods. In this framework, recovery is defined not as a single evaluation of long-term viability but as maintaining low risk of decline for the next several generations. Effects of errors in risk prediction techniques are mitigated through shorter prediction intervals, setting threshold abundances near current abundance, and explicitly incorporating uncertainty in risk estimates. Viable population monitoring also intrinsically adjusts monitoring effort relative to the population's true status and exhibits considerable robustness to model misspecification. We present simulations showing that risk predictions made with a simple exponential growth model can be effective monitoring indicators for population dynamics ranging from random walk to density dependence with stable, decreasing, or increasing equilibrium. In analyses of time-series data for five species, risk-based monitoring warned of future declines and demonstrated secure status more effectively than statistical tests for trend.     

沈阳“十五”生态环境保护工作设想

分析了沈阳主要生态问题 ,阐述了问题症结所在 ;同时提出相应的生态保护对策、措施和任务。     

乡镇铝厂大气氟污染对区域冬小麦生长影响的研究

通过对郑州市某乡镇电解铝厂附近的参气，土壤及冬小麦等生态因素含氟量的分析与研究，表明：（１）铝厂所排放的化物是造成冬小麦减产的主要原因：（２）冬小麦各部位器官含量与距污染源的距离呈负相关；（３）对电解铝生产过程排放的气态氟化物应采取相应的治理和防护措施。