Field-breeding birds on organic and conventional arable farms in the Netherlands

In this study territory densities of field-breeding farmland birds were compared on pairwise-selected organic and conventional arable farms for two years. Differences in territory densities between the two farm types were explained examining the effects of three factors on territory densities: (1) non-crop habitats, (2) crop types and (3) within-crop factors. In both years, densities of most species did not differ between organic and conventional farms. Only skylark and lapwing were more abundant on organic farms, but only skylarks showed a consistent pattern over both years. Differences in crop types grown between the two systems were the only explaining factor for differences in densities of skylark. For lapwing, the difference was only partly due to differences in crop type, but differences in within-crop factors (probably as a result of crop management) were likely to have had an effect as well. There were no significant differences in abundance of non-crop habitats between the two farming systems, so this could not explain differences in territory densities.     

Dynamics of the Coordination of Economy-Society and Resource-Environment in Shandong Peninsula,China

Abstract

Shandong Peninsula, as a more developed region in Shandong Province even the east coast of China, is facing challenges from resources and environment pressures. This paper tried to track and assess the coordination status and the dynamic between resource-environment and economy-society systems in Shandong Peninsula during 2001—2008 in order to provide decision support for regional sustainability. An appraisal index system was built including five aspects of harmony degree (A), sustainability degree (B), opening degree (C), stability degree (D) and controllability degree (E). The results showed that: 1) The coordination level of resource-environment and economy-society in Shandong Peninsula has continuously grown, and it has undergone three stages: no coordinated degree (2001–2002), weak coordinated degree (2003–2006) and basically coordinated degree (2007– 2008). 2) Five indexes of criterion hierarchy also increased overall, but each index showed different trends. Harmony degree, sustainability degree and opening degree rose all the time, while stability degree and controllability degree alternately rose and fell. The improvement of controllability degree was the slowest. 3) The aggravating trend of environmental pollution was slowing down. The economic growth was driven by industrial growth and urbanization typically and investment was still the main force to pull the regional economic growth. At the same time, technology and education were becoming more and more important for economic growth. The level of foreign capital utility declined and the geographical advantage of Shandong Peninsula was exerted. Meanwhile some characteristics of knowledge economy were presenting. Water resources become the main constraint factor of fast development in Shandong Peninsula. It is necessary to further strengthen the coordination ability of government on regional sustainable development.     

System dynamics modeling for municipal water demand estimation in an urban region under uncertain economic impacts

Accurate prediction of municipal water demand is critically important to water utilities in fast-growing urban regions for drinking water system planning, design, and water utility asset management. Achieving the desired prediction accuracy is challenging, however, because the forecasting model must simultaneously consider a variety of factors associated with climate changes, economic development, population growth and migration, and even consumer behavioral patterns. Traditional forecasting models such as multivariate regression and time series analysis, as well as advanced modeling techniques (e.g., expert systems and artificial neural networks), are often applied for either short- or long-term water demand projections, yet few can adequately manage the dynamics of a water supply system because of the limitations in modeling structures. Potential challenges also arise from a lack of long and continuous historical records of water demand and its dependent variables. The objectives of this study were to (1) thoroughly review water demand forecasting models over the past five decades, and (2) propose a new system dynamics model to reflect the intrinsic relationship between water demand and macroeconomic environment using out-of-sample estimation for long-term municipal water demand forecasts in a fast-growing urban region. This system dynamics model is based on a coupled modeling structure that takes into account the interactions among economic and social dimensions, offering a realistic platform for practical use. Practical implementation of this water demand forecasting tool was assessed by using a case study under the most recent alternate fluctuations of economic boom and downturn environments.     

Ethnobotany and ecological perspectives on the management and use of plant species for a traditional fishing trap, southern coast of São Paulo, Brazil

The cerco-fixo is an artisanal fishing trap widely used by traditional communities in the estuarine region of the southern coast of the state of São Paulo, Brazil. The primary goal of the study was to investigate, through ethnobotanical and ecological approaches, the use of plant species by traditional fishermen to build the cerco-fixo at Cardoso Island State Park and Cananéia Island. Ethnobotanical data were collected through interviews, direct observation, plant collection and identification, and document analysis. An ecological evaluation was also done comparing five 20 × 20 m plots in a managed area to five 20 × 20m plots in an unmanaged area, both within arboreal sandy soil vegetation called restinga arbórea, found within the Brazilian Atlantic Forest domain. This study involved 34 fishermen living at Cardoso and Cananéia Islands. The fishermen know more than 90 Atlantic Forest plant species that can be used to build the cerco-fixo. Tree species from the family Myrtaceae were the most quoted in the interviews. With respect to the ecological evaluation, the cluster analyses showed greater heterogeneity in terms of floristic composition (i.e. greater floristic dissimilarity) within the plots of the managed area. The analyses of diversity showed a slightly higher species richness and slightly lower values for Shannon, Simpson, Hurlbert’s PIE and Evenness indices in the managed area (59 species; H′ = 3.28; 1/D = 10.77; E = 0.80; Hurlbert’s PIE = 0.91) compared to the unmanaged area (54 species; H′ = 3.39; 1/D = 20.21; E = 0.85; Hurlbert’s PIE = 0.95). The Hutcheson’s t test showed no significant difference between both areas’ Shannon diversity indices (t: −1.04; p: 0.30). These results are attributed to the greater dominance of the palm species Euterpe edulis Mart. in the managed area (28.2% of the trees sampled at this area; n = 118), which equals twice the percentage of individuals of the same species found for the unmanaged area (14.6% of the sampled trees; n = 48). We discuss the impact of the fishermen’s harvesting practices in the managed area with an emphasis on three main points: (1) the harvesting practices are likely not contributing to a decrease in diversity in the managed area; (2) the greater heterogeneity in terms of floristic composition found for the managed area may reflect a mosaic pattern created by the opening of small tree-gaps distributed across this area over the course of more than 50 years; (3) the disturbance promoted by the fishermen’s harvesting practices can be compared to natural disturbances of low impact that create mosaic patterns in tropical forests. This study emphasizes the prominence of the human dimension in ecological processes and the importance of considering the perspectives of local people when discussing the conservation of the natural environments in which these people live.     

黄河中上游能源化工区重点产业发展战略生态风险评价

结合黄河中上游能源化工区重点产业发展战略生态风险宏观性、综合性、复杂性的特点,论文以生态风险景观评价方法及3S技术等为研究手段,综合考虑重点产业发展战略人为风险源及自然风险源,以生态风险受体和终点选择、风险源分析、暴露危害分析、生态风险综合评价及生态风险分区为评价步骤,揭示了重点产业发展战略潜在生态风险空间分异特征。研究结果表明：黄河中上游重点产业战略实施区可划分为三类生态风险监控区,生态风险重点监控区自然风险源分布集中,重点产业人为风险源和自然风险源交织在一起,极易发生生态风险放大效应,生态风险次重点监控区自然生态风险源分布较单一,局部重点产业人为风险源强度增强,将增加区域生态风险水平,生态风险监控区自然生态风险源分布范围较小,潜在生态风险水平相对较低。论文探索了战略环评生态风险评价方法和评价思路,为国内重点产业发展战略生态风险评价提供了借鉴。     

计算流体动力学在模拟气升式环流反应器中的研究进展

计算流体动力学(CFD)是对气升式环流反应器进行数值模拟的重要手段.为此,本文综述了CFD模拟概况及气升环流反应器中流体数值模拟研究进展,总结了目前CFD模拟气升环流反应器存在的问题,并提出了进一步的研究方向.     

Modelling landscape effects on density-contact rate relationships of deer in eastern Alberta: Implications for chronic wasting disease

Managing wildlife diseases requires an understanding of disease transmission, which may be strongly affected by host population density and landscape features. Transmission models are typically fit from time-series disease prevalence data and modelled based on how the contact rate among hosts is affected by density, which is often assumed to be a linear (density-dependent transmission) or constant (frequency-dependent transmission) relationship. However, long-term time-series data is unavailable for emerging diseases, and this approach cannot account for independent effects of landscape. We developed a mechanistic model based on ecological data to empirically derive the contact rate-density relationship in white-tailed and mule deer in an enzootic region of chronic wasting disease (CWD) in Alberta, Canada and to determine whether it was affected by landscape. Using data collected from aerial surveys and GPS-telemetry, we developed empirical relationships predicting deer group size, home range size, and habitat selection to iteratively simulate deer distributions across a range of densities and landscapes. We calculated a relative measure of total per-capita contact rate, which is proportional to the number of other deer contacted per individual per unit time, for each distribution as the sum of pairwise contact rates between a target deer and all other individuals. Each pairwise contact rate was estimated from an empirical relationship developed from GPS-telemetry data predicting pairwise contact rates as a function of home range overlap and landscape structure. Total per-capita contact rates increased as a saturating function of density, supporting a transmission model intermediate between density- and frequency-dependent transmission. This pattern resulted from group sizes that reached an asymptote with increasing deer density, although this relationship was mediated by tree and shrub coverage in the landscape, such that in heavily wooded areas, the contact rate saturated at much lower densities. These results suggest that CWD management based on herd reductions, which require a density-dependent contact rate to be effective, may have variable effects on disease across a single management region. The novel mechanistic approach we employed for estimating effects of density and landscape on transmission is a powerful complement to typical data-fitting approaches for modelling disease transmission.     

Forecasting population trend from the scaling pattern of occupancy

Forecasting the temporal trend of a focal species, its range expansion or retraction, provides crucial information regarding population viability. To this end, we require the accumulation of temporal records which is evidently time consuming. Progress in spatial data capturing has enabled rapid and accurate assessment of species distribution across large scales. Therefore, it would be appealing to infer the temporal trends of populations from the spatial structure of their distributions. Based on a combination of models from the fields of range dynamics, occupancy scaling and spatial autocorrelation, here I present a model for forecasting the population trend solely from its spatial distribution. Numerical tests using cellular automata confirm a positive correlation, as inferred from the model, between the temporal change in species range sizes and the exponent of the power-law scaling pattern of occupancy. The model is thus recommended for rapid estimation of species range dynamics from a single snapshot of its current distribution. Further applications in biodiversity conservation could provide a swift risk assessment, especially, for endangered and invasive species.     

Predicting modes of spatial change from state-and-transition models

State-and-transition models (STMs) can represent many different types of landscape change, from simple gradient-driven transitions to complex, (pseudo-) random patterns. While previous applications of STMs have focused on individual states and transitions, this study addresses broader-scale modes of spatial change based on the entire network of states and transitions. STMs are treated as mathematical graphs, and several metrics from algebraic graph theory are applied—spectral radius, algebraic connectivity, and the S-metric. These indicate, respectively, the amplification of environmental change by state transitions, the relative rate of propagation of state changes through the landscape, and the degree of system structural constraints on the spatial propagation of state transitions. The analysis is illustrated by application to the Gualalupe/San Antonio River delta, Texas, with soil types as representations of system states. Concepts of change in deltaic environments are typically based on successional patterns in response to forcings such as sea level change or river inflows. However, results indicate more complex modes of change associated with amplification of changes in system states, relatively rapid spatial propagation of state transitions, and some structural constraints within the system. The implications are that complex, spatially variable state transitions are likely, constrained by local (within-delta) environmental gradients and initial conditions. As in most applications, the STM used in this study is a representation of observed state transitions. While the usual predictive application of STMs is identification of local state changes associated with, e.g., management strategies, the methods presented here show how STMs can be used at a broader scale to identify landscape scale modes of spatial change.