Use of object-oriented classification and fragmentation analysis (1985�C2008) to identify important areas for conservation in Cockpit Country, Jamaica

Forest fragmentation is one of the most important threats to global biodiversity, particularly in tropical developing countries. Identifying priority areas for conservation within these forests is essential to their effective management. However, this requires current, accurate environmental information that is often lacking in developing countries. The Cockpit Country, Jamaica, contains forests of international importance in terms of levels of endemism and overall diversity. These forests are under severe threat from the prospect of bauxite mining and other anthropogenic disturbances. In the absence of adequate, up-to-date ecological information, we used satellite remote sensing data and fragmentation analysis to identify interior forested areas that have experienced little or no change as priority conservation sites. We classified Landsat images from 1985, 1989, 1995, 2002, and 2008, using an object-oriented method, which allowed for the inclusion of roads. We conducted our fragmentation analysis using metrics to quantify changes in forest patch number, area, shape, and aggregation. Deforestation and fragmentation fluctuated within the 23-year period but were mostly confined to the periphery of the forest, close to roads and access trails. An area of core forest that remained intact over the period of study was identified within the largest forest patch, most of which was located within the boundaries of a forest reserve and included the last remaining patches of closed-broadleaf forest. These areas should be given highest priority for conservation, as they constitute important refuges for endemic or threatened biodiversity. Minimizing and controlling access will be important in maintaining this core.     

A Spatial Model to Estimate Habitat Fragmentation and Its Consequences on Long-Term Persistence of Animal Populations

The increasing use of the landscape by humans has led to important diminutions of natural surfaces. The remaining patches of wild habitat are small and isolated from each other among a matrix of inhospitable land-uses. This habitat fragmentation, by disabling population movements and stopping their spread to new habitats, is a major threat to the survival of numerous plant and animal species. We developed a general model, adaptable for specific species, capable of identifying suitable habitat patches within fragmented landscapes and investigating the capacity of populations to move between these patches. This approach combines GIS analysis of a landscape, with spatial dynamic modeling. Suitable habitat is identified using a threshold area to perimeter ratio. Potential movement pathways of species between habitat patches are modeled using a cellular automaton. Habitat connectivity is estimated by overlaying habitat patches with movement pathways. The maximum potential population is calculated within and between connected habitat patches and potential risk of inbreeding within meta-populations is considered. The model was tested on a sample map and applied to scenario maps of predicted land-use change in the Peoria Tri-county region (IL). It (1) showed area of natural area alone was insufficient to estimate the consequences on animal populations; (2) underscored the necessity to use approaches investigating the effect of land-use change spatially through the landscape and the importance of considering species-specific life history characteristics; and (3) highlighted the model's potential utility as an indicator of species likelihood to be affected negatively by land-use scenarios and therefore requiring detailed investigation.     

Designing Connected and Compact Nature Reserves

It is generally accepted that for many species, the ability to get around a reserve promotes their long-term persistence. Here, we measure the ease with which species can move by two spatial criteria: (i) the connectivity of the reserve, that is to say, the possibility to go through the whole reserve without leaving it, and (ii) the compactness of the reserve, that is to say, the remoteness of the sites in relation to each other, the distance between two sites being measured by the shortest distance to travel to get from one site to another without leaving the reserve. To protect the reserve of external disturbances, we also impose a connectivity constraint for the area outside the reserve. This article presents a method based on integer linear programming to define connected and compact reserves. Computational experiments carried out on artificial instances with 400 sites and 100 species are presented to illustrate the effectiveness of the approach.     

基于遥感和Markov模型的新疆生产建设兵团土地利用变化

通过对兵团土地利用空间格局变化分析,选择合适的土地利用政策保护生态环境。运用RS和GIS技术对兵团近10年土地利用/覆被变化及景观格局空间变化进行分析,并在此基础上运用Markov模型对未来30年土地利用变化进行预测。2000—2010年,新疆生产建设兵团景观多样性升高,连通性增强,形状愈来愈简单,景观格局整体变化不大;草地、灌丛、湿地、荒漠和冰川/永久积雪面积减少,耕地和城镇面积增加,森林保持稳定;人为干扰对土地利用结构的变化具有重要作用,土地利用强度受人为活动影响的同时受土地利用政策影响;在未来30年间耕地和城镇面积继续增加,除森林基本保持不变外其他土地利用类型均减小。兵团城镇用地与草地和耕地之间的矛盾逐渐显现,势必引起兵团生态格局的变化。因此,必须实行合适的土地利用政策保护环境。     

Quantifying landscape pattern and connectivity in a Mediterranean coastal settlement: the case of the Urla district,Turkey

This study was aimed at analyzing and interpreting changes in landscape pattern and connectivity in the Urla district, Turkey using core landscape metrics based on a 42-year data derived from 1963 CORONA and 2005 ASTER satellite images and ten 1/25,000 topographical maps (1963–2005). The district represents a distinctive example of re-emerged suburbanization in the Izmir metropolitan area. In order to explore landscape characteristics of the study area, nine landscape composition and configuration metrics were chosen as follows: class area, percentage of landscape, number of patches, patch density, largest patch index, landscape shape index, mean patch size, perimeter area fractal dimension, and connectance index. The landscape configurations in the Urla district changed significantly by 2005 in that the process of (sub-)urbanization in the study area evolved from a rural, monocentric urban typology to a more suburban, polycentric morphology. Agricultural, maquis-phrygana, and forest areas decreased, while the built-up, olive plantation and phrygana areas increased. There was nearly a fivefold increase in the built-up areas during the study period, and the connectivity of the natural landscape declined. To prevent further fragmentation, it is important to keep the existing natural land cover types and agricultural areas intact. More importantly, a sustainable development scenario is required that contains a green infrastructure, or an ecological network planning for conservation and rehabilitation of the vital natural resources in the study area.     

Landscape connectivity changes analysis for monitoring desertification of Minqin county, China

Landscape connectivity, as an important indicator of regional landscape functional pattern measured by cost–distances model, could both reveal evidence of, and act as an indicator, for desertification. Using Minqin county as a case study, this study was further to test cost–distance connectivity for indicating desertification, and to analyze temporal changes of connectivity in the county from 1977 to 1997. The results further indicate the connectivity interpreted as lower cost–distance and higher risk of desertification. The temporal change analysis of connectivity provides more detail supplement of desertification processes. Landscape connectivity changes in the county had three distinctive phases, the strongest decline of log cost–distance with overwhelming decrease area and decrease amount in the period 1977–1984, and its slight decline with the relative balance between the high decrease amount and high increase amount in the period 1984–1992, then its the slight decline with the relative balance between the low decrease amount and low increase amount in the period 1992–1997. The frequent temporal and spatial transition in source class, grassland, alkali–saline land and irrigated cultivated land caused negative effects on the oasis environment.     

Directional Connectivity of Wolf (Canis lupus) Populations in Northwest Spain and Anthropogenic Effects on Dispersal Patterns

In view of the extensive information available on wolf ecology and habitat suitability, and on the fragmentation of wolf populations by motorways and similar infrastructures, a key factor in their conservation, the aim of the present study was to model the directional connectivity of wolf populations in the region of Galicia in northwest Spain, and to quantify anthropogenic effects on wolf dispersal patterns. To this end, we map the probability of wolf movement by means of known relationships between wolf movement and anthropogenic, vegetation and topographic factors. The relative importance of each factor was quantified by sensitivity analyses. Three types of cost surface were constructed: (a) isotropic surfaces, (b) anisotropic cost surfaces taking into account terrain slope effects in the movement, and (c) surfaces obtained by combining the isotropic and anisotropic surfaces. The results obtained by approaches (a) and (c) indicate that one of the region’s motorways (the AP-9) probably acts as a significant barrier to wolf movement, possibly isolating two subpopulations, while the remaining motorways probably do not have major effects on dispersal. Estimation of lowest-cost routes for wolf displacement allowed identification of areas critical for connectivity, in which it would be of interest to perform detailed studies with more precise input data on motorway course and the location of drainage channels and underpasses, etc. (these being the factors identified by sensitivity analysis to be those with the most marked effects on the cost surfaces). The visualization of connectivity enabled by this approach will allow wolf management and conservation efforts to be focused on critical areas: such efforts might include measures aimed to encourage wolf dispersal through areas in which conflict with human activity is minimized, thus contributing positively to the management of a socially conflictive species. Finally, evaluation of the different cost surfaces suggests that it would be of interest to introduce two modifications to the anisotropic algorithm, to allow the user to weigh the importance of the different input factors, and to allow the inclusion of more than one anisotropic factor in the model.     

Indifference curves as a tool for environment impact assessment

Use of indifference curves, defined as functionality between development index and pollution load to evaluate environmental impact, is proposed. Existing Battelle environmental evaluation methodology is subjective in its approach. The use of indifference curves lends a more objective approach to environment assessment methodology. The extent of environmental damage we are prepared to accept, for a development, can be explained by Willingness to Pay and Willingness to Accept approach. The application of proposed approach has been demonstrated taking an example of Power plant set up in forest area. The curves clearly show that cost of EMP considering mitigation of ecological damage is higher than the EMP mitigating impacts of air and water pollution only. The example stresses the need for willingness to accept along with willingness to pay.     

Rapid Assessment of Plant Diversity Patterns: A Methodology for Landscapes

We present a rapid, cost-efficient methodology to link plantdiversity surveys from plots to landscapes using: (1) unbiasedsite selection based on remotely sensed information; (2) multi-scale field techniques to assess plant diversity; (3)mathematical models (species-area curves) to estimate thenumber of species in larger areas corrected for within-typeheterogeneity; and (4) mathematical techniques to estimatetotal species richness and patterns of plant diversity in alandscape. We demonstrate the methodology in a 754 ha studyarea in Rocky Mountain National Park, Colorado, U.S.A.,using four 0.025 ha and twenty-one 0.1 ha multi-scalevegetation plots. We recorded 330 plant species (1/3 thenumber of plants recorded in the 1074 km² Park) in the2.2 ha area within the plots: this represents a samplingintensity of 0.29% of the 754 ha study site. We estimated 552plant species, about half the plant species recorded in the Park,in just 0.7% of the Parks area. We show how this rapid,cost-efficient methodology: (1) produces a rich informationbase on the patterns of native plant diversity and thedistribution of non-native plant species and keystoneecosystems; and (2) can be easily adapted for other nationaland state parks, national forests, wildlife refuges, and nature reserves.     

Optimal redesign of groundwater quality monitoring networks: a case study

Assessment and redesign of water quality monitoring networks is an important task in water quality management. This paper presents a new methodology for optimal redesign of groundwater quality monitoring networks. The measure of transinformation in discrete entropy theory and the transinformation–distance (T–D) curves are used to quantify the efficiency of sampling locations and sampling frequencies in a monitoring network. The existing uncertainties in the T–D curves are taken in to account using the fuzzy set theory. The C-means clustering method is also used to classify the study area to some homogenous zones. The fuzzy T–D curve of the zones is then used in a multi-objective hybrid genetic algorithm-based optimization model. The proposed methodology is utilized for optimal redesign of monitoring network of the Tehran aquifer in the Tehran metropolitan area, Iran.     

A landscape-based reconnaissance survey of estrogenic activity in streams of the upper Potomac,upper James,and Shenandoah Rivers,USA

Endocrine-disrupting compounds (EDCs) are becoming of increasing concern in waterways of the USA and worldwide. What remains poorly understood, however, is how prevalent these emerging contaminants are in the environment and what methods are best able to determine landscape sources of EDCs. We describe the development of a spatially structured sampling design and a reconnaissance survey of estrogenic activity along gradients of land use within sub-watersheds. We present this example as a useful approach for state and federal agencies with an interest in identifying locations potentially impacted by EDCs that warrant more intensive, focused research. Our study confirms the importance of agricultural activities on levels of a measured estrogenic equivalent (E2Eq) and also highlights the importance of other potential sources of E2Eq in areas where intensive agriculture is not the dominant land use. Through application of readily available geographic information system (GIS) data, coupled with spatial statistical analysis, we demonstrate the correlation of specific land use types to levels of estrogenic activity across a large area in a consistent and unbiased manner.     

Robust Regression with Data-Dependent Regularization Parameters and Autoregressive Temporal Correlations

We introduce robust procedures for analyzing water quality data collected over time. One challenging task in analyzing such data is how to achieve robustness in presence of outliers while maintaining high estimation efficiency so that we can draw valid conclusions and provide useful advices in water management. The robust approach requires specification of a loss function such as the Huber, Tukey’s bisquare and the exponential loss function, and an associated tuning parameter determining the extent of robustness needed. High robustness is at the cost of efficiency loss in parameter loss. To this end, we propose a data-driven method which leads to more efficient parameter estimation. This data-dependent approach allows us to choose a regularization (tuning) parameter that depends on the proportion of “outliers” in the data so that estimation efficiency is maximized. We illustrate the proposed methods using a study on ammonium nitrogen concentrations from two sites in the Huaihe River in China, where the interest is in quantifying the trend in the most recent years while accounting for possible temporal correlations and “irregular” observations in earlier years.     

Ecological validity of river-floodplain system assessment by planktonic crustacean survey (Branchiata: Branchiopoda)

Studies of the Slovakian Danube have indicated profound changes in the structures of several invertebrate assemblages in the section of the river bypassed by the Gab?íkovo hydroelectric project in 1992 and in adjacent floodplain water bodies. The present study investigates the relationship between hydrological connectivity and species diversity in the old main channel and adjacent left-bank water bodies, using resident cladocerans as indicators of the ecological integrity of the river-floodplain system. The work aimed to quantify cladoceran habitat preferences using habitat values (HV) and indication weights (IW) calculated from data accumulated during long-term monitoring of planktonic communities of the Danube floodplain (1,840.5–1,804 rkm) and supplemented with data from the literature. Although not listed as an indicator group in the European Union Water Framework Directive, cladocerans are shown to be highly apposite in the ecological assessment of river-floodplain systems. Of 71 recorded cladoceran species, 19 taxa showed a preference for eupotamal habitats, 24 species preferred eupotamal B/parapotamal waters, and 28 cladocerans were found to prefer the plesiopotamal/paleopotamal habitat type. Identified habitat types follow a gradient of hydrological connectivity with the main river channel, ranging from the eupotamal to more or less isolated floodplain water bodies. A secondary aim was to use the calculated values to assess the ecological integrity of the river-floodplain system. The key element of this procedure is the calculation of the Floodplain Index (FI) (Chovanec et al. Large Rivers, 15(1–4), 169–185 2005) from the summation of the habitat values and indication weights of all species present at the sampling sites. Calculated index values indicate the extent of disruption to lateral connectivity in the floodplain area.     

Connectivity in priority area selection for conservation

The spatial relations of sites within networks of priority areas for conservation is critical to the long-term maintenance of key genetic, population and ecosystem processes. However, these relations have received relatively little attention in the development of mathematical methods for objectively identifying such networks. Here we present a novel heuristic for incorporating connectivity explicitly as part of the model constraints, provide an integer linear programming formulation for the same problem, describe an integer cutting procedure which defines a sequence of non-decreasing lower bounds on the optimal solution and report the results of some computational experiments using these algorithms.     

The Development of a Prediction Model for the Kinetic Constant of Chlorinated Aliphatic Hydrocarbons

Kinetic constants are important design parameters to determine the degradation of a substrate in biological treatment systems. The objective of this study was to develop a regression model using a quantitative structure–activity relationship technique for the prediction of the first-order rate constants (k) of chlorinated aliphatic hydrocarbons (CAHs). The prediction model showed very good correlations between the measured and calculated rate constants of CAHs. It was likely that the higher-order connectivity indices were important factors for the prediction of the kinetic constants, implying more complicated connectivity indices contributed to the prediction of a biological property. This technique would provide a useful tool to establish the kinetics of other CAHs without costly or time-consuming tests.     

Spectral reflectance properties of major objects in desert oasis: a case study of the Weigan–Kuqa river delta oasis in Xinjiang, China

Aiming at the remote sensing application has been increasingly relying on ground object spectral characteristics. In order to further research the spectral reflectance characteristics in arid area, this study was performed in the typical delta oasis of Weigan and Kuqa rivers located north of Tarim Basin. Data were collected from geo-targets at multiple sites in various field conditions. The spectra data were collected for different soil types including saline-alkaline soil, silt sandy soil, cotton field, and others; vegetations of Alhagi sparsifolia, Phragmites australis, Tamarix, Halostachys caspica, etc., and water bodies. Next, the data were processed to remove high-frequency noise, and the spectral curves were smoothed with the moving average method. The derivative spectrum was generated after eliminating environmental background noise so that to distinguish the original overlap spectra. After continuum removal of the undesirable absorbance, the spectrum curves were able to highlight features for both optical absorbance and reflectance. The spectrum information of each ground object is essential for fully utilizing the multispectrum data generated by remote sensing, which will need a representative spectral library. In this study using ENVI 4.5 software, a preliminary spectral library of surface features was constructed using the data surveyed in the study area. This library can support remote sensing activities such as feature investigation, vegetation classification, and environmental monitoring in the delta oasis region. Future plan will focus on sharing and standardizing the criteria of professional spectral library and to expand and promote the utilization of the spectral databases.     

上海市工业区大气污染预警监测信息平台研究与设计

根据上海市工业区大气污染排放特征,在构建大气特征污染监控网络的基础上,搭建了工业区大气污染预警监测信息平台,并研究了适用于大气特征污染自动站的通信传输规范,确保数据联网和应用。平台设置了大气质量监控、大气数据管理、污染源一厂一档、大气质量分析评价、污染源溯源分析、应急监测数据管理、智能移动终端查询等7个子系统,可为上海市工业区大气污染预警和管控提供实时监测数据。     

A Simulation Framework for Assessing Physical and Wildlife Impacts of Oil and Gas Development Scenarios in Southwestern Wyoming

Foreseeable natural gas development in southwestern Wyoming has the potential to increase sagebrush fragmentation and risks to resident wildlife species. The ability to balance future development with conservation goals, however, is enhanced by advances in directional-drilling technologies that use multiple wells per pad and produce less surface disturbance than conventional drilling methods. To evaluate the conservation potential of this technology, I developed an energy footprint model that simulates well, pad, and road patterns for oil and gas recovery options that vary in well types (vertical and directional) and number of wells per pad and use simulation results to quantify physical and wildlife-habitat impacts. I applied the model to assess tradeoffs among 10 conventional and directional-drilling scenarios in a natural gas field in southwestern Wyoming. Scenarios spanned a gradient in the number of vertical and directional wells, and in number of pads (2000 to 250), but all extracted the same amount of gas over a 15-year period. Reducing pad numbers with directional-drilling technology reduced surface disturbance area and impacts on spatially extensive habitats (48–96% of study area) such as sagebrush-obligate songbird habitat, elk winter range, and sagebrush core area. Impacts declined for spatially restricted mule deer migration corridors (24% of study area) and greater sage-grouse leks until energy infrastructure densities within corridors and near leks were similar to the initial landscape. Scenario simulations and tradeoff assessments such as illustrated in this study are intended to help decision-makers identify development designs that best achieve both energy and conservation goals.     

Modeling Large Fire Frequency and Burned Area in Canadian Terrestrial Ecosystems with Poisson Models

Large wildland fires are major disturbances that strongly influence the carbon cycling and vegetation dynamics of Canadian boreal ecosystems. Although large wildland fires have recently received much scrutiny in scientific study, it is still a challenge for researchers to predict large fire frequency and burned area. Here, we use monthly climate and elevation data to quantify the frequency of large fires using a Poisson model, and we calculate the probability of burned area exceeding a certain size using a compound Poisson process. We find that the Poisson model simulates large fire occurrence well during the fire season (May through August) using monthly climate, and the threshold probability calculated by the compound Poisson model agrees well with historical records. Threshold probabilities are significantly different among different Canadian ecozones, with the Boreal Shield ecozone always showing the highest probability. The fire prediction model described in this study and the derived information will facilitate future quantification of fire risks and help improve fire management in the region.