Fragmentation profiles for real and simulated landscapes

When a natural landscape is represented by a series of categorical raster maps of varying resolution, a multiresolution characterization of spatial pattern can be obtained in which entropy is computed at each resolution conditional on the next coarser resolution. The series of entropy values is plotted as a function of resolution, resulting in a multiresolution profile of fragmentation pattern in the landscape. If a categorical raster map is available at a single resolution only, a series of degraded maps at increasingly coarser resolutions is generated and the fragmentation profile is computed for this series. An algorithm has been developed for obtaining the profile directly from the single resolution map without having to generate and store the coarser resolution maps. A hierarchical stochastic model is described for simulating categorical raster maps and the fragmentation profile of the generating process is obtained in terms of the model parameters. These process profiles provide benchmarks for assessing empirical profiles obtained from raster maps of actual landscapes. Methods of the paper are applied to several watersheds of Pennsylvania using landcover maps derived from satellite imagery. These examples indicate that characteristic landscape types induce characteristic features in their fragmentation profiles.     

Methods to summarize change among land categories across time intervals

Time-series maps have become more detailed in terms of numbers of categories and time points. Our paper proposes methods for raster datasets where detailed analysis of all categorical transitions would be initially overwhelming. We create two measurements: Incidents and States. The former is the number of times a pixel’s category changes across time intervals; the latter is the number of categories that a pixel represents across time points. The combinations of Incidents and States summarize change trajectories. We also describe categorical transitions in terms of annual flow matrices, which quantify the additional information generated by intermediate time points within the temporal extent. Our approach summarizes change at the pixel and landscape levels in ways that communicate where and how categories transition over time. These methods are useful to detect hotspots of change and to consider whether the apparent changes are real or due to map error.     

A geostatistical approach for mapping thematic classification accuracy and evaluating the impact of inaccurate spatial data on ecological model predictions

Spatial information in the form of geographical information system coverages and remotely sensed imagery is increasingly used in ecological modeling. Examples include maps of land cover type from which ecologically relevant properties, such as biomass or leaf area index, are derived. Spatial information, however, is not error-free: acquisition and processing errors, as well as the complexity of the physical processes involved, make remotely sensed data imperfect measurements of ecological attributes. It is therefore important to first assess the accuracy of the spatial information being used and then evaluate the impact of such inaccurate information on ecological model predictions. In this paper, the role of geostatistics for mapping thematic classification accuracy through integration of abundant image-derived (soft) and sparse higher accuracy (hard) class labels is presented. Such assessment leads to local indices of map quality, which can be used for guiding additional ground surveys. Stochastic simulation is proposed for generating multiple alternative realizations (maps) of the spatial distribution of the higher accuracy class labels over the study area. All simulated realizations are consistent with the available pieces of information (hard and soft labels) up to their validated level of accuracy. The simulated alternative class label representations can be used for assessing joint spatial accuracy, i.e., classification accuracy regarding entire spatial features read from the thematic map. Such realizations can also serve as input parameters to spatially explicit ecological models; the resulting distribution of ecological responses provides a model of uncertainty regarding the ecological model prediction. A case study illustrates the generation of alternative land cover maps for a Landsat Thematic Mapper (TM) subscene, and the subsequent construction of local map quality indices. Simulated land cover maps are then input into a biogeochemical model for assessing uncertainty regarding net primary production (NPP).     

A concise review of ecological risk assessment for urban ecosystem application associated with rapid urbanization processes

ABSTRACT

Urban ecological risk (UER) caused by rapid urbanization means potential threat to urban ecosystem structure, pattern and services. The scales of ecological risk assessment (ERA) have been expanded from individual organisms to watersheds and regions. The types of stressor range from chemical to physical, biological and natural events. However, the application of ERA in urban ecosystems is relatively new. Here, we summarize the progress of urban ERA and propose an explicit framework to illumine future ERA based on UER identification, analysis, characterization, modeling, projection and early warning and management. The summary includes six urban ERA-relevant methods: weight-of-evidence (WoE), procedure for ecological tiered assessment of risks (PETAR), relative risk model (RRM), multimedia, multi-pathway, multi-receptor risk assessment (3MRA), landscape analysis and ecological models. Furthermore, we review critical cases of urban ERA in landscape ecology, soil, air, water and solid waste. Based on the Internet of Things (IoT) and cloud computing, an urban ERA management platform integrates various urban ERA methodologies that can be developed to provide better implementation strategies of UER for urban ecosystem managers and stakeholders. We develop a conceptual model of urban ERA based on the urban characteristics in China. The future applications of urban ERA include uncertainty analysis using Monte Carlo techniques on the basis of geospatial techniques and comprehensive urban ERA using nonlinear models or process models.     

Toward estimation of map accuracy without a probability test sample

The time and effort required of probability sampling for accuracy assessment of large-scale land cover maps often means that probability test samples are not collected. Yet, map usefulness is substantially reduced without reliable accuracy estimates. In this article, we introduce a method of estimating the accuracy of a classified map that does not utilize a test sample in the usual sense, but instead estimates the probability of correct classification for each map unit using only the classification rule and the map unit covariates. We argue that the method is an improvement over conventional estimators, though it does not eliminate the need for probability sampling. The method also provides a new and simple method of constructing accuracy maps. We illustrate some of problems associated with accuracy assessment of broad-scale land cover maps, and our method, with a set of nine Landsat Thematic Mapper satellite image-based land cover maps from Montana and Wyoming, USA.     

Are existing vegetation maps adequate to predict bird distributions?

Bird species are selective on the vegetation types in which they are found but predictive models of bird distribution based on variables derived from land-use/land-cover maps tend to have limited success. It has been suggested that accuracy of existing maps used to derive predictors is in part responsible for the limited success of bird distribution models. In two areas of 4900 km² of Western Andalusia, Spain, we compared the predictive ability of bird distribution models derived from two existing general-purpose land-use/land-cover maps, which differ in their resolution and accuracy: a coarse scale vegetation map of Europe, the CORINE land-cover map, and a detailed regional map, the 1995 land-use/land-cover map of Andalusia from the SINAMBA (Consejerı́a de Medio Ambiente, Junta de Andalucı́a). We compared the bird distribution models derived from these general-purpose vegetation maps with models derived from two more accurate structural vegetation maps built considering directly variables that influence bird habitat selection, one built from satellite images for this study and another obtained by improving the resolution and accuracy of the SINAMBA map with satellite data. We sampled the presence/absence of bird species at 857 points using 15-min point surveys. Predictive models for 54 bird species were built with generalised additive models (GAMs), using as potential predictors the same set of landscape and vegetation structure variables measured on each map. We compared for each bird species the predictive accuracy of the best model derived from each map. Vegetation structure measured at bird sample points was used as ground-truth for comparing the accuracy of vegetation maps. Although maps differed in their resolution and accuracy, the results show that all of them produced similarly accurate bird distribution models, with a mixed map produced with both thematic and satellite information being the best. The models derived from the more accurate vegetation structure maps obtained from satellite data were not more accurate than those derived directly from the SINAMBA or CORINE maps. Our results suggest that some general-purpose land-use/land-cover maps are accurate enough to derive bird distribution models. There is a certain limit to improve vegetation maps above which there is no effect in their power to predict bird distribution.     

Soil landscape constraint mapping for coastal land use planning using geographic information system

The aim of the study was to delineate soil landscape constraints to various land uses for urban and regional planning in the coastal areas of New South Wales (NSW), Australia. Soil landscape units mapped at 1:100,000 or coarser were sub-divided into component facets using advanced terrain modelling techniques in a geographic information system (GIS). The output facet grids were further overlain and linked with relevant GIS layers and soil databases to derive soil landscape constraint ratings for various land use purposes such as residential development, cropping and grazing. The constraint ratings for a specific land use were calculated based on objective and rule-based assessments of soil and landscape features such as engineering hazards, intrinsic fertility, drainage and other parameters. A series of soil landscape constraint maps which portray specific land use capability have been produced for the NSW coast. The methodology developed in this study has been demonstrated to be efficient in delineating soil landscape constraints and there is over 90% agreement between the model outputs and the assessment by soil surveyors with local knowledge. The output maps show levels of unprecedented detail of soil and landscape constraint for the coast of NSW and can be readily interpreted by land use planners and land managers for sustainable land use decision making practices.     

A multiscale hierarchical Markov transition matrix model for generating and analyzing thematic raster maps

A model is described for generating hierarchically scaled spatial pattern as represented in a thematic raster map. The model involves a series of Markov transition matrices, one for each level in the scaling hierarchy. In full generality, the model allows the transition matrices to be different at each level, potentially making available a large number of parameters for landscape characterization. The model is self-similar when the transition matrices are all equal. A method is presented for fitting the model to data that take the form of a single-resolution thematic raster map. Explicit analytic solutions are obtained for the fitted parameters. The fitting method is based on a relationship between the hierarchical transitions in the model and spatial transitions at varying distance scales in the data map, a categorical analogy of the geostatistical variogram.     

珠江三角洲典型区景观生态聚类分析

珠海是珠江三角洲地区一个海陆交互作用与人类干扰活动频繁的典型区域。文章以2000年TM数据为基础数据源，编制珠海地区景观类型图，并以镇(区)为基本空间单元将珠海划分为20个景观生态子区，在GIS与景观斑块分析软件Patch Analyst 2．0支持下计算各子区的景观特征指数。通过各子区的景观指数对比分析，探讨研究区范围内景观格局的空间差异，揭示人类活动、自然干扰等各种景观生态机制对区域景观生态的影响。根据各指数反映的景观特征信息，选择平均斑块大小(MPS)、斑块大小变异系数(PSCOV)、边缘密度(ED)、面积加权分维数(AWMPFD)、破碎度指数(F)、多样性指数(SDI)及人为干扰指数(DT)进行珠海景观生态聚类分析，根据聚类分析结果可多层次客观地对珠海地区进行景观生态类型区划分。     

The spatial links tool: Automated mapping of habitat linkages in variegated landscapes

The removal, alteration and fragmentation of habitat in many parts of the world has led to a loss of biodiversity. Within the prevailing societal limitations the process is not easily reversed. Attempts are being made to minimise the fragmentation of remaining habitat by strategically reversing or managing habitat loss. Although their relative usefulness is a topic of debate among ecologists, habitat corridors are seen as one way of maintaining spatially dependent ecological processes within landscapes where habitat has been seriously depleted. Corridors can only be effective if they significantly contribute to the species sustaining processes of gene flow, resource access or the colonisation of vacant patches. We present a spatial habitat modelling methodology for evaluating the contribution and potential contribution of connecting paths to landscape connectivity. We have developed the spatial links tool (SLT), which maps link value across a region. The SLT combines connectivity measures from metapopulation ecology with the least cost path algorithm from graph theory, and can be applied to continuously variable landscape data. Combined with expert judgement, link value maps can be used to delineate habitat corridors. The approach capitalises on some synergies between ecological relevance and computational efficiency to produce an easily applied heuristic tool that has been successfully applied in NSW Australia.     

A decision-support system in ICZM for protecting the ecosystems: integration with the habitat directive

This paper describes a decision-support system based on landscape ecology and focused on the study of ecosystems’ health. System capabilities are illustrated with three cases of integrated coastal zone management (ICZM), in the Adriatic Sea (Italy): the lagoon of Venice and the Rimini and Ancona coastal areas. Indicators and indices are developed with a focus on sub-regional and local problems in coastal management, with a multi-scale approach based on landscape and seascape ecology. Land-use changes of the coastal areas were detected by analyzing two sets of satellite images. Indices combining satellite imagery, socio-economic and environmental indicators, and landscape and seascape maps were created, showing ecological changes, habitat loss and gaps in conservation policy. The approach used provides means for the identification of conflicts and for the assessment of sustainability. Results show that the lagoon of Venice plays an important role in mitigating and compensating the impacts of human activities, and needs to be protected and restored. The Rimini area shows high ecological footprint and development-intensity and low biocapacity. The Ancona area needs the protection of its natural coastal space from potential sources of anthropogenic impacts to maintain its sustainability. A model of environment changes is critical for formulating effective environmental policies and management strategies. The developed decision-support system provides a suitability map per each area analyzed, which can be used in order to maximize different policy objectives and reduce coastal conflicts.     

Modeling and interpreting the accuracy assessment error matrix for a doubly classified map

This paper considers two maps having the same spatial extent and the same mapping categories but where each map is subject to classification error. An overlay of the maps yields a (dis)similarity matrix whose (i, j)-entry is the areal proportion placed into category i by the first map and into category j by the second map. A parametric model, called the latent truth model, is proposed which specifies the dissimilarity matrix in terms of the true (but unknown) proportions for the mapping categories as well as the unknown error rates for the two maps. The number of parameters in the model exceeds the degrees of freedom in the dissimilarity matrix. However, a method of regularization is applied to effectively reduce the dimension of the parameter space and to permit model fitting. From the fitted model, one obtains estimates for the true mapping proportions as well as estimated error matrices for each of the maps. Accuracy assessment characteristics for each map (such as user's accuracy, producer's accuracy, overall accuracy, and the kappa coefficient) can be computed from the estimated error matrices. Methods are illustrated with two landcover maps of Wicomico County, Maryland.     

Time discounting and the decision to protect areas that are near and threatened or remote and cheap to acquire

Should conservation organizations focus on protecting habitats that are at imminent risk of being converted but are expensive or more remote areas that are less immediately threatened but where a large amount of land can be set aside? Variants of this trade‐off commonly arise in spatial planning. I used models of land‐use change near a deforestation frontier to examine this trade‐off. The optimal choice of where to protect was determined by how decisions taken today accounted for ecological benefits and economic costs of conservation actions that would occur sometime in the future. I used an ecological and economic discount rate to weight these benefits and costs. A large economic discount rate favored protecting more remote areas, whereas a large, positive ecological discount rate favored protecting habitat near the current deforestation frontier. The decision over where to protect was also affected by the influence economic factors had on landowners' decisions, the rate of technological change, and ecological heterogeneity of the landscape. How benefits and costs through time are accounted for warrants careful consideration when specifying conservation objectives. It may provide a niche axis along which conservation organizations differentiate themselves when competing for donor funding or other support.     

Ecological effects associated with land-use change in China's southwest agricultural landscape

Research on land-use and land-cover change, with associated effects on the ecoenvironment, is a key to understanding global change. The concept of 'ecosystem services' is also a hot issue in ecology and ecological economics. In this study, ecosystem service values are used to assess the ecological values of corresponding land-use types, so as to evaluate the ecological effects of regional land-use change. China's southwest agricultural landscape has unique ecological functions; but it also belongs to an ecologically fragile zone. Consequently, land-use change and associated ecological effects must be monitored to assure sustainable development of this area. Based on TM images in 1988, 1994 and 1999, the landscape classification maps of Yongsheng County were assessed using supervised classification and interactive modification methods. The transition matrix of land-use types and three indices of spatial patterns, patch-level, class-level and landscape-level indices, were calculated using models and GIS to examine the spatial patterns and dynamics of land use in the study area. The results show the influences of human activities and natural environmental elements, and that unused land has decreased rapidly, together with a continuous increase in forest during the past 11 years. There are also frequent intermediate transitions between farmland and unused land. An index for landscape diversity shows a tendency to increase, indicating that the proportions of each landscape element tended to average. Also, the decrease in the fractal dimension of unused land reveals that the effects of human activity are increasing. Ecological value calculations show that land-use change in Yongsheng County from 1988–1999 has resulted in positive ecological effects, with distinct spatial differences.     

Impacts of residential development on vegetation cover for a remote coastal barrier in the Outer Banks of North Carolina, USA

Coastal barrier environments are heavily influenced by human activities yet there are few examples of landscape ecological work investigating human dimensions of settlement disturbance patterns and processes. We investigated the impacts of residential development on vegetation cover for a remote roadless coastal barrier in Carova, North Carolina that is subject to policies from the federal to local levels and addressed three research questions: How has the region’s the policy history influenced patterns of residential parcel development? What are the spatial and temporal patterns of parcel development? How has development impacted patterns of barrier vegetation cover? We traced the influences of the federal 1982 Coastal Barrier Resources Act (CBRA) designed to discourage development in risky coastal areas as well as state/local coastal policies and employed remote sensing change detection, NDVI analysis and spatial analysis and regression techniques. Results showed an acceleration of new housing structures since 1990, contrary to the intended effects of CBRA. An estimated vegetation cover loss of 437 m² was associated with each newly developed parcel. NDVI varied along spatial and temporal gradients with more recent development having lower NDVI than older development. Recently developed parcels were larger in area, closer to the beach, and contained houses with larger footprints compared to older developed parcels. Our approach represents a place-based analytical framework for coastal barrier landscapes. Beyond the Carova case study, adopting such an approach coupling natural and human systems for the entire eastern US barrier system requires defining a comprehensive set of coastal barrier spatial units to enable typological classification and subsequent systematic investigation to inform debates regarding coastal ecosystem services and sustainability.     

Integrating Landscape and Metapopulation Modeling Approaches: Viability of the Sharp-Tailed Grouse in a Dynamic Landscape

Abstract:  The lack of management experience at the landscape scale and the limited feasibility of experiments at this scale have increased the use of scenario modeling to analyze the effects of different management actions on focal species. However, current modeling approaches are poorly suited for the analysis of viability in dynamic landscapes. Demographic (e.g., metapopulation) models of species living in these landscapes do not incorporate the variability in spatial patterns of early successional habitats, and landscape models have not been linked to population viability models. We link a landscape model to a metapopulation model and demonstrate the use of this model by analyzing the effect of forest management options on the viability of the Sharp-tailed Grouse (  Tympanuchus phasianellus ) in the Pine Barrens region of northwestern Wisconsin (U.S.A.). This approach allows viability analysis based on landscape dynamics brought about by processes such as succession, disturbances, and silviculture. The landscape component of the model (LANDIS) predicts forest landscape dynamics in the form of a time series of raster maps. We combined these maps into a time series of patch structures, which formed the dynamic spatial structure of the metapopulation component (RAMAS). Our results showed that the viability of Sharp-tailed Grouse was sensitive to landscape dynamics and demographic variables such as fecundity and mortality. Ignoring the landscape dynamics gave overly optimistic results, and results based only on landscape dynamics (ignoring demography) lead to a different ranking of the management options than the ranking based on the more realistic model incorporating both landscape and demographic dynamics. Thus, models of species in dynamic landscapes must consider habitat and population dynamics simultaneously.     

Spatial uncertainty analysis of population models

This paper describes an approach for conducting spatial uncertainty analysis of spatial population models, and illustrates the ecological consequences of spatial uncertainty for landscapes with different properties. Spatial population models typically simulate birth, death, and migration on an input map that describes habitat. Typically, only a single “reference” map is available, but we can imagine that a collection of other, slightly different, maps could be drawn to represent a particular species’ habitat. As a first approximation, our approach assumes that spatial uncertainty (i.e., the variation among values assigned to a location by such a collection of maps) is constrained by characteristics of the reference map, regardless of how the map was produced. Our approach produces lower levels of uncertainty than alternative methods used in landscape ecology because we condition our alternative landscapes on local properties of the reference map. Simulated spatial uncertainty was higher near the borders of patches. Consequently, average uncertainty was highest for reference maps with equal proportions of suitable and unsuitable habitat, and no spatial autocorrelation. We used two population viability models to evaluate the ecological consequences of spatial uncertainty for landscapes with different properties. Spatial uncertainty produced larger variation among predictions of a spatially explicit model than those of a spatially implicit model. Spatially explicit model predictions of final female population size varied most among landscapes with enough clustered habitat to allow persistence. In contrast, predictions of population growth rate varied most among landscapes with only enough clustered habitat to support a small population, i.e., near a spatially mediated extinction threshold. We conclude that spatial uncertainty has the greatest effect on persistence when the amount and arrangement of suitable habitat are such that habitat capacity is near the minimum required for persistence.     

滨海新区规划对区域生态网络结构的影响分析

以滨海新区2008年卫星影像、《滨海新区城市总体规划（2005-2020）》和《滨海新区城市空间发展战略研究（2005-2050）》为基础,在GIS技术下运用景观格局分析、网络结构分析及斑块间的相互作用力分析法研究了滨海新区规划对区域生态网络结构的影响。结果表明：滨海新区2008年生态网络景观破碎化严重且连通性差;《总体规划》侧重于斑块间的廊道连接,但大尺度斑块比例小;《战略研究》侧重于大尺度斑块的构建,但连通性较差;根据景观生态学原理,提出了滨海新区的生态网络结构改进建议。     

Urban ecological security assessment and forecasting,based on a cellular automata model: A case study of Guangzhou,China

Forecasting changes in urban ecological security could be important for the maintenance or improvement of the urban ecological environment. However, there are few references in this field and no landmark research work has been reported, particularly quantitative research. A forecasting model for ecological security based on cellular automata (CA) was developed using preliminary spatial data from an ecological security assessment of Guangzhou conducted previously (1990–2005). The model was constrained using transformation rules based upon proposed planning for 2010–2020. A simulation accuracy of 72.09% was acquired. Using a one-bit assessment grid for 2005 as the starting state for the simulation, the model was used to forecast ecological security for 2020. This revealed that although the ecological security status would be improved relative to current trends, there would still be an overall decline in ecological security over the next 15 years. Even if new urban plans were implemented, landscape pattern analysis suggested a more scattered and homogenous distribution in the urban landscape of Guangzhou and significant variation in landscape characteristics among districts. This suggests that further measures must be adopted to reverse the current trends in Guangzhou's ecological security. The model highlights the need to make ecological protection an integral part of urban planning. This study demonstrates the potential of CA models for forecasting ecological security. Such models could make an important contribution to decision-making for regional governors and to the development of urban planning incorporating assessment and prediction of ecological security.     

Use of landscape and land use parameters for classification and characterization of watersheds in the mid-Atlantic across five physiographic provinces

The Atlantic Slope Consortium (ASC) is a project designed to develop and test a set of indicators in coastal systems that are ecologically appropriate, economically reasonable, and relevant to society. The suite of indicators will produce integrated assessments of the condition, health and sustainability of aquatic ecosystems based on ecological and socioeconomic information compiled at the scale of estuarine segments and small watersheds. The research mandate of the ASC project is the following:

Using a universe of watersheds, covering a range of social choices, we ask two questions:

• ? How “good” can the environment be, given those social choices?
• ? What is the intellectual model of condition within those choices, i.e., what are the causes of condition and what are the steps for improvement?

As a basis for compiling ecological indicators, a watershed classification system was required for the experimental design. The goal was to develop approximately five categories of watersheds for each physiographic province, utilizing landscape and land use parameters that would be predictive of aquatic resource condition. All 14-digit Hydrologic Unit Code (HUC) watersheds in the Mid-Atlantic region would then be classified according to the regime. Five parameters were utilized for the classification: three land cover categories, consisting of forested, agricultural, and urban, median slope or median elevation, and total variance of land covers in 1-km-radius circles positioned on all stream convergence points in a specified 14-digit?HUC watershed. Cluster analysis utilizing these five parameters resulted in approximately five well-defined watershed classes per physiographic province. The distribution of all watersheds in the Mid-Atlantic region across these categories provides a unique report on the probable condition of watersheds in the region.