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.     

Concentration of heavy metals in hair and skin of silver and red foxes (Vulpes vulpes)

The structure of hair and levels of main chemical elements (C, N, O, S, Cl, Ca, P, Al, Na) in the external layer of hair of silver and red foxes (Vulpes vulpes) in a non-industrialised, typically agricultural region of middle-west Poland was assessed using a scanning microscope. Additionally, analysis of the accumulation of certain heavy metals (Cr, Cu, Ni, Pb and Zn) in hair (washed) and skin (non-tanned) of those foxes was conducted. Heavy metal levels were determined using a spectrophotometric method (ICP-OES), and correlations between these levels in hair and skin were calculated. The microscopic external (morphological) and internal structures (histological) of the hair of farm and wild foxes were not differentiated; however, the hair of farm foxes (external layer) contained higher amounts of C, Na, Al and P. A significantly higher Pb content was noted in non-tanned skin of wild foxes in comparison to farm ones. In the case of farm foxes, a significantly higher Zn content in hair and Zn and Cu in skin was observed in comparison to wild ones. Positive significant correlations between Cr and Ni content (r = 0.622) and Zn and Cu (r = 0.721) in fox skin were noted. A similar relationship between Cr content in hair and Ni in skin (r = 0.643) and between Zn in hair and skin (r = 0.595) was also observed.     

A GIS tool to estimate West Nile virus risk based on a degree-day model

West Nile virus (Flaviviridae: Flavivirus) is a serious infectious disease that recently spread across the North America continent. A spatial analysis tool was developed on the ArcMap 9.x platform to estimate potential West Nile virus activity using a spatially explicit degree-day model. The model identifies when the virus Extrinsic Incubation Period (EIP) is completed within the vector longevity during mid-summer months. The EIP is treated as a threshold indicator of the potential for virus emergence and activity. Comparing the number of West Nile virus cases in Wyoming reported from 2003 to 2005 with model results, actual cases and predicted events of West Nile virus activity match relatively well. The model represents a useful method for estimating potential West Nile virus activity in a large spatial scale.     

An examination of the effect of landscape pattern, land surface temperature, and socioeconomic conditions on WNV dissemination in Chicago

This paper developed an approach by the synthesis of remote sensing, landscape metrics, and statistical methods to examine the effects of landscape pattern, land surface temperature, and socioeconomic conditions on the spread of West Nile virus (WNV) caused by mosquitoes and animal hosts in Chicago, USA. Land use/land cover and land surface temperature images were derived from Terra’s Advanced Spaceborne Thermal Emission and Reflection Radiometer imagery. An analytical procedure using landscape metrics was developed, applying configuration analysis of landscape patterns in the study area. The positive reports of mosquitoes and animal hosts for WNV in fall, 2001–2006, were collected from the Cook County Public Health Department. Forty-nine municipalities were found to have WNV-positive records in mosquitoes and animal hosts in fall 2004. Socioeconomic data were obtained from the 2000 US Census. Statistical analysis was applied to WNV data in fall 2004 to identify the relationship between potential predictors and WNV spread. As a result, landscape factors, such as landscape aggregation index and the urban areas and areas of grass and water, showed strong correlations with the WNV-positive records. Socioeconomic conditions, such as the population over 65 years old, also showed a strong correlation with WNV-positive records. Thermal conditions of water showed a less but still considerable correlation to WNV-positive records. This research offers an opportunity to explore the effects of landscape pattern, land surface temperature, and socioeconomic conditions on the spread of WNV caused by mosquitoes and animal hosts. Results can contribute to public health and environmental management in the study area.     

2007—2017年三亚城市景观空间格局动态特征及驱动因素分析

应用2007—2017年期间4个时间点的遥感影像数据,选取典型景观格局指数,对三亚市的景观空间格局动态特征进行分析,探求其驱动因素。研究表明：近十年来,三亚市内同种土地利用类型的空间聚集程度降低,空间分布逐渐趋向于分散,不同类型的土地之间相互融合度较高,形状趋于复杂化,景观类型分布趋势呈均衡化,景观的破碎化程度加强,景观复杂程度增高,土地利用的丰富程度逐渐加强。通过驱动因素分析,国家政策的导向、城市总体规划的实施、产业结构调整及自然环境的变化是影响三亚城市景观空间格局变化的主要驱动因素。     

Evaluating Spatio-temporal Complexities of Forest Management: An Integrated Agent-based Modeling and GIS Approach

The objective of this study is to integrate agent-based modeling and geographic information systems (GIS) for examining how interactions within forest management lead to patterns of land-cover change. Specifically, this study evaluates how management agents behave in the presence of variable timber prices, harvesting costs, and accessibility to timber and how their actions influence the spatial characteristics of the forest landscape over time. The GIS calculates the average harvested patch size, number of patches, and total harvested area as measures of emergent patterns resulting from agent actions. The results from the agent-based GIS model reveal that good economic conditions lead to few but large harvested patches, while deteriorating conditions will see more patches of smaller size if forest companies have access to high-quality timber. This study emphasizes the need for a complex systems approach to forest management as the model illustrates how system elements interact in a manner to produce emergent spatial patterns over time.     

Evaluation of potential habitat with an integrated analysis of a spatial conservation strategy for David's deer, Elaphurus davidians

How to assess the potential habitat integrating landscape dynamics and population research, and how to reintroduce animals to potential habitats in environments highly human disturbed are still questions to be answered in conservation biology. According to behavioral research on Elaphurus davidians, we have developed a suitability index and a risk index to evaluate the potential habitats for the deer. With these indices, we conducted two transect assessments to evaluate the gradient change of the target region. Then, taking rivers as border lines, we tabulated the forest areas, high grassland area and total area and then compared the forest and high grassland area in each subregion. Furthermore, we computed the land use transfer matrix for the whole Yancheng coast during 1987-2000. We also computed human modified index (HMI) in six subregions. Lastly with a geographical information system support we obtained the spatial distribution of the indices and evaluation of the whole potential habitats from a neighborhood analysis. The transect assessment showed that the suitability of the coastal area was higher than that of the inland area for the deer, while the southern area was higher than the northern. Landscape metrics and HMI analysis showed that different landscape patterns and different anthropogenic disturbance existed within the region, and the increasing human disturbance was the key factor causing the pattern dynamics. The evaluation of potential habitats showed that there was an estimated carrying capacity of no more than 10,000 for David's deer reintroduction into the natural area. Also the reintroduction strategy was discussed. This integrated approach linked the population research and the landscape metrics, and the dataset with different scale; thus, it is an approach likely to be useful for the protection of other large animal in a landscape highly disturbed by humans.     

Evaluating Habitat as a Surrogate for Population Viability Using a Spatially Explicit Population Model

Because data for conservation planning are always limited, surrogates are often substituted for intractable measurements such as species richness or population viability. We examined the ability of habitat quality to act as a surrogate for population performance for both Red-shouldered Hawks (Buteo lineatus) and Northern Goshawks (Accipiter gentilis). We compared simple measures of habitat quality to estimates of population growth rates obtained from a spatially explicit model of population dynamics. We found that habitat quality was a relatively poor predictor of simulated population growth rates for several reasons. First, a relatively small proportion of the potential habitat for each species served as population sources in our simulations--15% for Red-shouldered Hawks and 2% for Goshawks. Second, when habitat quality correctly predicted demographic sources on the landscape, it consistently underestimated the contribution of these areas to the population. In areas where habitat quality correctly anticipated the presence of demographic sinks, we found no useful quantitative relationship between the two measures. Our simulation model captured the influence of habitat quality on the hawk populations, but it also incorporated interactions between dispersing individuals and landscape patterns. Thus, the discrepancies we observed likely reflected the influence of forest fragmentation and the spatial arrangement of forest patches on the populations. We conclude that simple measures of habitat quality will often be poor surrogates for population persistence, but that spatially explicit population models can help inform the development of better indices.     

Spatial factors of white-tailed deer herbivory assessment in the central Appalachian Mountains

Because moderate to over-abundant white-tailed deer (Odocoileus virginianus) herbivory impacts biodiversity and can alter community function, ecological benchmarks of herbivory impact are needed to assess deer impacts. We evaluated spatial patterns of deer herbivory and their relation to herbivory assessment by evaluating woody vegetation along 20 transects at each of 30 sites spread across a wide range of deer herd densities and vegetative condition throughout the biodiverse Appalachian Mountains of Virginia, USA. Surprisingly, herbivory patterns and the availability of woody forage generally were unchanged among physiographic regions and land use diversity classes. However, some relationships between browsing pattern and vegetation varied with scale. The total quantity of vegetation browsed on a given site and at the transect scale were related positively to the availability of forage, as the proportion of stems browsed decreased as stem density increased. However, this was only true when all stems were considered equally. When stem densities by species were weighted for deer preference, the proportion of stems browsed had no relationship or increased with stem density. Compared to the value from all transects sampled, on average, the mean of ≥?3 transects within a site was within 0.1 of the browsing ratio and stem densities were within 0.5 stems m^?2. Our results suggest that one transect per square kilometer with a minimum of three transects may be sufficient for most browsing intensity survey requirements to assess herbivory impacts in the Appalachian region of Virginia. Still, inclusion of spatial factors to help partition variation of deer herbivory potentially may allow for improved precision and accuracy in the design of field herbivory impact assessment methods and improve their application across various landscape contexts.     

Modeling Runoff Response to Land Cover and Rainfall Spatial Variability in Semi-Arid Watersheds

Hydrologic response is an integrated indicator of watershed condition, and significant changes in land cover may affect the overall health and function of a watershed. This paper describes a procedure for evaluating the effects of land cover change and rainfall spatial variability on watershed response. Two hydrologic models were applied on a small semi-arid watershed; one model is event-based with a one-minute time step (KINEROS), and the second is a continuous model with a daily time step (SWAT). The inputs to the models were derived from Geographic Information System (GIS) theme layers of USGS digital elevation models, the State Soil Geographic Database (STATSGO) and the Landsat-based North American Landscape Characterization classification (NALC) in conjunction with available literature and look up tables. Rainfall data from a network of 10 raingauges and historical stream flow data were used to calibrate runoff depth using the continuous hydrologic model from 1966 to 1974. No calibration was carried out for the event-based model, in which six storms from the same period were used in the calculation of runoff depth and peak runoff. The assumption on which much of this study is based is that land cover change and rainfall spatial variability affect the rainfall-runoff relationships on the watershed. To validate this assumption, simulations were carried out wherein the entire watershed was transformed from the 1972 NALC land cover, which consisted of a mixture of desertscrub and grassland, to a single uniform land cover type such as riparian, forest, oak woodland, mesquite woodland, desertscrub, grassland, urban, agriculture, and barren. This study demonstrates the feasibility of using widely available data sets for parameterizing hydrologic simulation models. The simulation results show that both models were able to characterize the runoff response of the watershed due to changes of land cover.     

Rabbit Population Landscape-Scale Simulation to Investigate the Relevance of Using Rabbits in Regulatory Environmental Risk Assessment

This paper describes the development and testing of the ALMaSS rabbit model and its baseline, and subsequently its application to the question of lagomorph population vulnerability in environmental risk assessment (ERA). Development and testing following a pattern-oriented modelling protocol resulted in a model able to replicate local and landscape-level rabbit population patterns. We then tested how robust rabbit populations are to an (imaginary) extreme toxic stressor at a landscape level in a variety of landscapes, and to what extremes key uncertain model parameters must be pushed to cause extinctions. This was contrasted with the same (imaginary) toxic stressor applied to the already existing ALMaSS hare model. For EU risk assessment of plant protection products, these results clearly indicate that if the protection goal is population-level impacts, either in abundance and/or distribution, then the hare is a much more vulnerable species than the rabbit under all the conditions tested. Rabbits would only be more vulnerable than hares if the entire population were to be exposed simultaneously, when lower body mass would then be a critical factor. This did not occur even though the toxicant and exposure scenarios tested here were extreme and, in fragmented landscapes at scales used here, will not occur in reality from the use of plant protection products on crop fields. As well as specifically answering the question on rabbit versus hare vulnerability, this study generally illustrates the potential application of models for setting focal species for risk assessments.     

A Robust Optimization Model for an Invasive Species Management Problem

Invasive species pose a significant threat to global biodiversity. Managing invasive species often involves modeling the species’ spread pattern, estimating control costs and damage costs due to the invasion, designing control efforts, and accounting for uncertainties in model parameters. Dealing with uncertainty is arguably the most important part of the process, since biological, environmental, and economic factors can cause parameter values to vary greatly. Managers need decision tools that are robust to such limited or variable information. Here, we present a robust spatial optimization model to select treatment sites in a way that maximally reduces the size of an invasive population, given a constraint on financial resources. We develop an integer programming model that includes population dynamics and management costs over space and time. The model incorporates uncertainty in the available budget and the invasive spread rate as sets of discrete scenarios to determine a robust, cost-effective management plan in a novel way.     

Assessing Landscape Condition Relative to Water Resources in the Western United States: A Strategic Approach

The Environmental Monitoring and Assessment Program (EMAP) is proposing an ambitious agenda to assess the status of streams and estuaries in a 12-State area of the western United States by the end of 2003. Additionally, EMAP is proposing to access landscape conditions as they relate to stream and estuary conditions across the west. The goal of this landscape project is to develop a landscape model that can be used to identify the relative risks of streams and estuaries to potential declines due to watershed-scale, landscape conditions across the west. To do so, requires an understanding of quantitative relationships between landscape composition and pattern metrics and parameters of stream and estuary conditions. This paper describes a strategic approach for evaluating the degree to which landscape composition and pattern influence stream and estuary condition, and the development and implementation of a spatially-distributed, landscape analysis approach.     

Landscape ecological planning through a multi-scale characterization of pattern: studies in the Western Ghats,South India

This article analyzes landscape pattern in the WesternGhats mountain ranges in south-western India at two scales,comparing small-scale, detailed studies of landscapepattern, with broader, regional-scale assessments of theWestern Ghats. Due in large part to their inaccessibility,relatively little is known about the landscapes of thisbiodiverse region, which also supports some of the highestpopulation densities in the world. A broad-scale NDVI-basedIRS 1B satellite image classification is used to analyzenorth-south and east-west trends across the entire WesternGhats and western coast of India, an area over 170 000 km². Northern and eastern landscapes are morefragmented compared to the southern and western slopes.Western slopes also have greater landscape diversity withland cover types more interspersed compared to the easternslopes. These differences can be related to north-south andeast-west variations in rainfall and plant distribution. Data from thirteen landscapes 10–50 km² in area, arefurther utilized to analyze trends in landscape pattern, anddescribe the geographical distribution of major natural andmanaged ecotope types. At this scale, very high levels ofintra-ecotope type variability in landscape pattern areencountered for all land cover types. Results at these twoscales are integrated to suggest a hierarchical stratifiedapproach for monitoring land cover and biodiversity in the region.     

Application of Ecological Classification and Predictive Vegetation Modeling to Broad-Level Assessments of Ecosystem Health

The Little Missouri National Grasslands (LMNG) of western North Dakota support the largest permitted cattle grazing use within all lands administered by the USDA, Forest Service, as well as critical habitat for many wildlife species. This fact, coupled with the need to revise current planning direction for range allotments of the LMNG, necessitated that a broad-level characterization of ecosystem integrity and resource conditions be conducted across all lands within the study area (approximately 800,000 hectares) in a rapid and cost-effective manner. The approach taken in this study was based on ecological classifications, which effectively utilized existing field plot data collected for a variety of previous inventory objectives, and their continuous spatial projection across the LMNG by maps of both existing and potential vegetation. These two map themes represent current and reference conditions (existing vs. potential vegetation); their intersection allowed us to assign various ecological status ratings (i.e., ecosystem integrity and resource condition) based on the degree of departure between current and reference conditions. In this paper, we present a brief review of methodologies used in the development of ecological classifications, and also illustrate their application to assessments of rangeland health through selected maps of ecological status ratings for the LMNG.     

Evaluation of R-EMAP Techniques for the Measurement of Ecological Integrity of Streams in Washington State's Coast Range Ecoregion

We used methods from EPA's Environmental Monitoring and Assessment Program (EMAP) to assess the regional status of streams within the Coast Range ecoregion of Washington State. Study objectives were: to determine the ecological condition of wadable, 1st-order through 3rd-order streams; to provide information for the development of water quality biological criteria; and to determine the applicability of EMAP-derived methods in Washington. Stream condition was assessed using EMAP indicators for habitat (chemical and physical) and biology (invertebrate and vertebrate assemblages). EMAP's probability survey was used to select 75 1st through 3rd-order stream sites from the USGS 1:100,000 series hydrographic layer. Of these, 45 sites were sampled. Multivariate techniques were used to identify community types and related physical and chemical habitat. Overall, about 25% of the sites were rated least-impacted. Most impacts were associated with non-point source pollution, mainly forestry practices. The R-EMAP method was a successful tool for assessment of regional status and ecological integrity; however, in order to use it for biological criteria development in Washington State, the method would require some modification to complement the current state protocols.     

Landscape resistance to dispersal: simulating long-term effects of human disturbance on a small and isolated wolf population in southwestern Manitoba, Canada

Landscape fragmentation affects wildlife population viability, in part, through the effects it has on individual dispersal. In addition, some forms of human disturbance impinge on dispersal without physically fragmenting habitats. Here, we use the term "landscape resistance" to capture constraints to dispersal that cannot be linked directly to fragmentation. The extent to which landscape resistance can influence population persistence is not well understood. Agricultural development over the past 60?years has resulted in considerable habitat fragmentation in the Riding Mountain National Park (RMNP) region in southwestern Manitoba, Canada. We examined how park boundaries, roads outside park boundaries and negative human attitudes have altered dispersal success and population persistence. We examined whether stochastic disturbance, representing infectious disease epidemics, further reduced long-term population persistence for various scenarios. Finally, we assessed whether the simultaneous occurrence of the three features had additive effects. We simulated dispersal using HexSim, a spatially explicit individual-based population model, parameterised with data on wolves (Canis lupus) in the RMNP region. Simulations that separately accounted for negative human attitudes and roads outside the park boundaries exhibited lower mean population size than those that ignored these details. Increasing deflection from park boundaries did not appear to have significant impacts. Our results did not indicate the presence of additive effects, and scenarios incorporating all three features had similar results as that of roads. Stochastic disturbance further reduced mean population size. Our results do illustrate how less-visible human disturbances (i.e. those that do not clearly alter landscape characteristics) can significantly limit dispersal and population persistence.     

Monitoring the urban green spaces and landscape fragmentation using remote sensing: a case study in Osmaniye,Turkey

Urban green spaces play a significant role in management of physical activity, psychological well-being, and public health of urban residents. With the expansion of urban areas in Turkey during the past decades, urban green spaces have been fragmented and dispersed causing impairment and environmental degradation. The purpose of this study is to model urban green space distribution by focusing on the landscape fragmentation in city of Osmaniye using remote sensing and geographic information system technology. Normalized difference vegetation index (NDVI) and urban landscape ratio (ULR) were used to assess the proximity and spatial arrangement of urban green spaces within the neighbor landscapes to quantify the urban land use effect. The geospatial analysis results showed that increase in total built-up area and population has significantly decreased the urban green space cover because of high levels of landscape fragmentation in urban city center. Also, due to high levels of landscape fragmentation, approximately 45% of the Osmaniye city is estimated to become urbanized by 2030. This study demonstrated the benefits of directional vegetation index application with geospatial analyses in characterizing the environmental quality for planning and management of urban green spaces. This approach could be used for determining the future urban land development scenarios correlating with regional planning procedures.     

A comparison of fixed-site and non-fixed-site approaches for species protection

The efficacy of simultaneously advancing two distinct conceptual designs (referred to here as fixed-site and non-fixed-site) for species conservation and protection is addressed. In the literature, numerous models can be found that typically stem from a particular design, but rarely are comparisons made between approaches. This paper presents a more integrated optimization framework that models landowner behavior and species viabilities at a landscape scale. Regional demand for resource extraction is used as the economic driver, a variant of simulated annealing is used to solve the model under different species protection approaches, and a detailed species population simulator is utilized to measure biological responses. When directly comparing the outcomes of different species protection strategies from a case study in Oregon (USA), it was found that neither approach was universally superior in terms of financial value or degree of protection for two late seral forest dependent species.     

A method to the impact assessment of the returning grazing land to grassland project on regional eco-environmental vulnerability

The Chinese government has conducted the Returning Grazing Land to Grassland Project (RGLGP) across large portions of grasslands from western China since 2003. In order to explore and understand the impact in the grassland's eco-environment during the RGLGP, we utilized Projection Pursuit Model (PPM) and Geographic Information System (GIS) to develop a spatial assessment model to examine the ecological vulnerability of the grassland. Our results include five indications: (1) it is practical to apply the spatial PPM on ecological vulnerability assessment for the grassland. This methodology avoids creating an artificial hypothesis, thereby providing objective results that successfully execute a multi-index assessment process and analysis under non-linear systems in eco-environments; (2) the spatial PPM is not only capable of evaluating regional eco-environmental vulnerability in a quantitative way, but also can quantitatively demonstrate the degree of effect in each evaluation index for regional eco-environmental vulnerability; (3) the eco-environment of the Xianshui River Basin falls into the medium range level. The normalized difference vegetation index (NDVI) and land use cover and change (LUCC) crucially influence the Xianshui River Basin's eco-environmental vulnerability. Generally, in the Xianshui River Basin, regional eco-environmental conditions improved during 2000 and 2010. The RGLGP positively affected NDVI and LUCC structure, thereby promoting the enhancement of the regional eco-environment; (4) the Xianshui River Basin divides its ecological vulnerability across different levels; therefore our study investigates three ecological regions and proposes specific suggestions for each in order to assist in eco-environmental protection and rehabilitation; and lastly that (5) the spatial PPM established by this study has the potential to be applied on all types of grassland eco-environmental vulnerability assessments under the RGLGP and under the similar conditions in the Returning Agriculture Land to Forest Project (RALFP). However, when establishing an eco-environmental vulnerability assessment model, it is necessary to choose suitable evaluation indexes in accordance with regional eco-environmental characteristics.