Biodiversity and ecological value of conservation lands in agricultural landscapes of southern Ontario,Canada

In eastern North America, large forest patches have been the primary target of biodiversity conservation. This conservation strategy ignores land units that combine to form the complex emergent rural landscapes typical of this region. In addition, many studies have focussed on one wildlife group at a single spatial scale. In this paper, studies of avian and anuran populations at regional and landscape scales have been integrated to assess the ecological value of agricultural mosaics in southern Ontario on the basis of the maintenance of faunal biodiversity. Field surveys of avian and anuran populations were conducted between 2001 and 2004 at the watershed and sub-watershed levels. The ecological values of land units were based on a combination of several components including species richness, species of conservation concern (rarity), abundance, and landscape parameters (patch size and connectivity). It was determined that habitats such as thicket swamps, coniferous plantations and cultural savannas can play an important role in the overall biodiversity and ecological value of the agricultural landscape. Thicket swamps at the edge of agricultural fields or roads provided excellent breeding habitat for anurans. Coniferous plantations and cultural savannas attracted many birds of conservation concern. In many cases, the land units that provided high ecological value for birds did not score well for frogs. Higher scores for avian and anuran populations were recorded along the Niagara Escarpment and other protected areas as expected. However, some private land areas scored high, some spatially connected to the protected areas and therefore providing an opportunity for private land owners to enter into a management arrangement with the local agencies.     

Quantifying patch distribution at multiple spatial scales: Applications to wildlife-habitat models

Multiscale analyses are widely employed for wildlife-habitat studies. In most cases, however, each scale is considered discrete and little emphasis is placed on incorporating or measuring the responses of wildlife to resources across multiple scales. We modeled the responses of three Arctic wildlife species to vegetative resources distributed at two spatial scales: patches and collections of patches aggregated across a regional area. We defined a patch as a single or homogeneous collection of pixels representing 1 of 10 unique vegetation types. We employed a spatial pattern technique, three-term local quadrat variance, to quantify the distribution of patches at a larger regional scale. We used the distance at which the variance for each of 10 vegetation types peaked to define a moving window for calculating the density of patches. When measures of vegetation patch and density were applied to resource selection functions, the most parsimonious models for wolves and grizzly bears included covariates recorded at both scales. Seasonal resource selection by caribou was best described using a model consisting of only regional scale covariates. Our results suggest that for some species and environments simple patch-scale models may not capture the full range of spatial variation in resources to which wildlife may respond. For mobile animals that range across heterogeneous areas we recommend selection models that integrate resources occurring at a number of spatial scales. Patch density is a simple technique for representing such higher-order spatial patterns.     

Quantifying patch distribution at multiple spatial scales: Applications to wildlife-habitat models

Multiscale analyses are widely employed for wildlife-habitat studies. In most cases, however, each scale is considered discrete and little emphasis is placed on incorporating or measuring the responses of wildlife to resources across multiple scales. We modeled the responses of three Arctic wildlife species to vegetative resources distributed at two spatial scales: patches and collections of patches aggregated across a regional area. We defined a patch as a single or homogeneous collection of pixels representing 1 of 10 unique vegetation types. We employed a spatial pattern technique, three-term local quadrat variance, to quantify the distribution of patches at a larger regional scale. We used the distance at which the variance for each of 10 vegetation types peaked to define a moving window for calculating the density of patches. When measures of vegetation patch and density were applied to resource selection functions, the most parsimonious models for wolves and grizzly bears included covariates recorded at both scales. Seasonal resource selection by caribou was best described using a model consisting of only regional scale covariates. Our results suggest that for some species and environments simple patch-scale models may not capture the full range of spatial variation in resources to which wildlife may respond. For mobile animals that range across heterogeneous areas we recommend selection models that integrate resources occurring at a number of spatial scales. Patch density is a simple technique for representing such higher-order spatial patterns.     

Underestimating the effects of spatial heterogeneity due to individual movement and spatial scale: infectious disease as an example

Many ecological and epidemiological studies occur in systems with mobile individuals and heterogeneous landscapes. Using a simulation model, we show that the accuracy of inferring an underlying biological process from observational data depends on movement and spatial scale of the analysis. As an example, we focused on estimating the relationship between host density and pathogen transmission. Observational data can result in highly biased inference about the underlying process when individuals move among sampling areas. Even without sampling error, the effect of host density on disease transmission is underestimated by approximately 50 % when one in ten hosts move among sampling areas per lifetime. Aggregating data across larger regions causes minimal bias when host movement is low, and results in less biased inference when movement rates are high. However, increasing data aggregation reduces the observed spatial variation, which would lead to the misperception that a spatially targeted control effort may not be very effective. In addition, averaging over the local heterogeneity will result in underestimating the importance of spatial covariates. Minimizing the bias due to movement is not just about choosing the best spatial scale for analysis, but also about reducing the error associated with using the sampling location as a proxy for an individual’s spatial history. This error associated with the exposure covariate can be reduced by choosing sampling regions with less movement, including longitudinal information of individuals’ movements, or reducing the window of exposure by using repeated sampling or younger individuals.

     

Summer spatial patterning of chukars in relation to free water in western Utah

Free water is considered important to wildlife in arid regions. In the western United States, thousands of water developments have been built to benefit wildlife in arid landscapes. Agencies and researchers have yet to clearly demonstrate their effectiveness. We combined a spatial analysis of summer chukar (Alectoris chukar) covey locations with dietary composition analysis in western Utah. Our specific objectives were to determine if chukars showed a spatial pattern that suggested association with free water in four study areas and to document summer dietary moisture content in relation to average distance from water. The observed data for the Cedar Mountains study area fell within the middle of the random mean distance to water distribution suggesting no association with free water. The observed mean distance to water for the other three areas was much closer than expected compared to a random spatial process, suggesting the importance of free water to these populations. Dietary moisture content of chukar food items from the Cedar Mountains (59%) was significantly greater (P < 0.05) than that of birds from Box Elder (44%) and Keg-Dugway (44%). Water developments on the Cedar Mountains are likely ineffective for chukars. Spatial patterns on the other areas, however, suggest association with free water and our results demonstrate the need for site-specific considerations. Researchers should be aware of the potential to satisfy water demand with pre-formed and metabolic water for a variety of species in studies that address the effects of wildlife water developments. We encourage incorporation of spatial structure in model error components in future ecological research.     

Subjective perception of noise exposure in relation to urban green space availability

Noise pollution has been recognized as one of major threats to the health of urban residents. Increasing green space availability can create a natural buffer to the adverse effects of living in an urban environment. These positive effects of urban green space can be directly related to an objective reduction of noise levels and – indirectly – to the subjective perception of noise exposure. In our study carried out in Lodz, Poland, we explored the relationship between objective noise levels and the subjective perception of noise exposure by urban residents in relation to urban green space availability. We refer to objective noise exposure expressed as GIS modelled L_den derived from noise maps (compliant with the Environmental Noise Directive, 2002/49/EC), and subjective (self-reported) perception of noise exposure as declared in a questionnaire-based survey. We compared the percentage of green space in a buffer, the objectively measured noise level, and the perceived exposure to noise to find the most appropriate radius of the green space buffer. We decided to choose the green space coverage which is not correlated with an objective noise level to avoid potential multicollinearity in regression models. This contrasts with most studies, in which the radius of the buffer is set a priori. We thus compared the selected buffer of green space coverage – 300 m (representing green space availability) – with perceived noise exposure. We used the spatial error probit model to differentiate the impacts of objective and subjective noise indicators, at the same time including also the factor of green space availability. We found out that the direct effect of objectively measured noise levels, education, the presence of noisy neighbours, and building characteristics were the most important variables influencing the self-reported perception of noise by urban residents. The indirect effect of green space availability on noise perception was not strong, yet statistically significant. Although our study does not provide clear-cut evidence, it indicates that the indirect, psychological effects of urban green spaces can positively affect the life satisfaction of urban residents.     

Effects of landscape urbanization on magpie occupancy dynamics in France

Responses of species to landscape modifications are generally documented through their distribution at a given time along an intensity gradient of land transformation. By focusing on patterns, we are limited to infer ecological processes occurring within a system and its response to environmental disturbances which can further change over time. Using diachronic datasets at the scale of France, we analyzed the spatial responses of the black-billed magpie, which has recently colonized cities, to landscape urbanization. This study applied recently developed statistical approaches incorporating detection uncertainty of the magpie, based on the capture-recapture statistical framework. We tested whether, and how, extinction and colonization mechanisms influenced variations of magpie occupancy from 2001 to 2005. In addition, we assessed the importance of the recent urbanization of the French countryside in determining population dynamics. Overall, our analysis proved that the proportion of urban areas and recent urbanization in France led to an increase in the probability of magpie occupancy. Unexpectedly, the species is concomitantly disappearing from the countryside, leading to a rapid change in the distribution of the species. This study stressed the importance of incorporating detection uncertainty in inference process about spatial dynamics. Overall, we show how useful it is to account for the dynamic evolution of the landscape in ecological studies.     

Linking habitat suitability and road mortalities across geographic ranges

Protected areas are established to conserve biodiversity and facilitate resilience to threatening processes. Yet protected areas are not isolated environmental compounds. Many threats breach their borders, including transportation infrastructure. Despite an abundance of roads in many protected areas, the impact of roads on biota within these protected areas is usually unaccounted for in threat mitigation efforts. As landscapes become further developed and the importance of protected areas increases, knowledge of how roads impact on the persistence of species at large scales and whether protected areas provide relief from this process is vital. We took a two-staged approach to analysing landscape-scale habitat use and road-kill impacts of the common wombat (Vombatus ursinus), a large, widely distributed herbivore, within New South Wales (NSW), Australia. Firstly, we modelled their state-wide distribution from atlas records and evaluated the relationship between habitat suitability and wombat road fatalities at that scale. Secondly, we used local-scale fatality data to derive an annual estimate of wombats killed within an optimal habitat area. We then combined these two approaches to derive a measure of total wombats killed on roads within the protected area network. Our results showed that common wombats have a broad distribution (290,981?km²), one quarter (24.9?%) of their distribution lies within protected areas, and the percentage of optimal habitat contained within protected areas is 35.6?%, far greater than the COP10 guidelines of 17?%. Problematically, optimal habitat within protected areas was not a barrier to the effects of road-kill, as we estimated that the total annual count of wombat road-kill in optimal habitat within protected areas could be as high as 13.6?% of the total NSW population. These findings suggest that although protected areas are important spatial refuges for biodiversity, greater effort should be made to evaluate how reserves confer resilience from the impacts of roads across geographic ranges.     

An integrated approach of remote sensing,GIS and swarm intelligence for zoning protected ecological areas

Interest in protecting ecological areas is increasing because of land uses conflicts and environmental pressures. The optimal zoning of protected ecological areas belongs to a NP-hard problem because it is subject to both box and spatial constraints. A challenge in solving area optimization problems emerges with the increasing size of a study region. In this article, an integrated approach of remote sensing, GIS and modified ant colony optimization (ACO) is proposed for application in zoning protected ecological areas. Significant modifications have been made in the conventional ACO so that it can be further extended to solve zoning problems in large regions. An improved selection strategy is designed to accelerate the progress of sites selection for artificial ants. Another important modification in ACO is to incorporate the neighborhood diffusion strategy into pheromone updating. The optimal objective is to generate protected areas that maximize both ecological suitability and spatial compactness. The modified ACO model has been successfully applied to a case study involving an area of 25,483 cells in Dongguan, Guangdong, China. The experiments have demonstrated that the proposed model is an efficient and effective optimization technique for generating optimal protection. The modified ACO model only requires approximately 119 s for determining near-optimal solutions. Furthermore, the proposed method performs better than other methods, including simulated annealing, genetic algorithm, iterative relaxation, basic ACO, and density slicing.     

GAP management status and regional indicators of threats to biodiversity

Conservation assessment requires quantitative criteria for evaluating the relative degree of threat faced by species or ecological communities. Identifying appropriate criteria for communities is complicated because the species inhabiting them can have many different responses to land uses and other forms of environmental stress. The Gap Analysis Program (GAP) uses summary data on the proportion of the community that is protected as an estimate of its vulnerability. Management status from a gap analysis of California was compared with three ecological indicators (permitted land uses, human population growth, and the spatial extent of road effects) that more directly represent impacts on biodiversity. The classification of management status appears to provide a crude first approximation of these three indicators. Public and private lands that are not formally protected were susceptible to extensive land use conversion or resource extraction in both rural and urban settings. Some plant community types are more susceptible to future infringement by human population increases that were not well predicted by management status alone. Other community types have a high road density despite being moderately well protected. It is suggested that indicators such as future growth and current road effects could complement status in rating the potential vulnerability of plant communities and setting conservation priorities. The choice of indicators will depend on the threatening processes in a given region and the availability of spatial data to map or model them.     

The effect of target extent on the location of optimal protected areas networks in Canada

Various jurisdictions in Canada are currently undertaking, or have recently completed, planning exercises as part of implementation and expansion of representative reserve networks (networks of provincial parks, national parks, ecological reserves, etc.). These exercises have resulted in recommendations to governments about which areas of land should be set aside as protected areas, and different levels of government have been involved in the process of land acquisition. In some cases, planning exercises have included implementation of new protected areas to complement existing reserve networks. Many of these exercises have applied principles such as complementarity, using heuristic algorithms that are well-described in the literature. These planning exercises may be conducted within politically or ecologically bounded target regions of varying extents. Here, I develop candidate locations for representative reserve areas for disturbance-sensitive mammals across Canada. I use ecologically bounded regions (within the national boundaries of Canada) at three different levels of spatial hierarchy: mammal provinces, ecozones, and ecoregions. I show that the extent of the target region has an effect on the minimum number of protected areas required to achieve representation; a larger region requires fewer protected areas than the sum of the protected areas required to represent its component regions at a lower level of spatial hierarchy. The results illustrate that selection of sites for inclusion in a reserve network is highly scale-dependent, and different spatial extents in the target regions may introduce inefficiencies or redundancies in selecting representative protected areas.     

Influence of land-use/land-cover change on landscape connectivity for an endemic threatened amphibian (Argenteohyla siemersi pederseni,Anura: Hylidae)

Context

Modifications in natural landcover generally result in a loss of habitat availability for wildlife and it’s persistence will depend largely on their spatial configuration and functional connections. Argenteohyla siemersi is a threatened and endemic amphibian whose habitat is composed of forest patches near rivers and water bodies edges.

Objectives

This study aimed to analyse the accessible habitat for this species and identify key elements to maintain its ecological network in two different types of land uses: an anthropized area with extensive cattle raising and a protected area.

Methods

The structural and functional characteristics of both landscapes were analyzed. The connectivity at landscape level and the contribution of each habitat patch were evaluated through simulation models with different dispersion distances in the context of the graph theory.

Results

In both landscapes, nine types of landcover were identified with different compositions. Remarkable differences were found in habitat connectivity for this amphibian species between both landscapes. As the percentage of dispersion distance increases, reachable habitat increases as well, although with higher percentages in the protected area. Two corridors were identified in the protected landscape and one in the rangeland one; patches and key links constituted all of them.

Conclusions

The present work provides spatially explicit results with a quantitative basis. It could be useful as a tool for the development of management plans aimed at guaranteeing the functionality of the ecological network for this endangered species and, therefore, contribute to its long-term conservation.

     

The effects of habitat resolution on models of avian diversity and distributions: a comparison of two land-cover classifications

Quantifying patterns is a key element of landscape analysis. One aspect of this quantification of particular importance to landscape ecologists is the classification of continuous variables to produce categorical variables such as land-cover type or elevation stratum. Although landscape ecologists are fully aware of the importance of spatial resolution in ecological investigations, the potential importance of the resolution of classifications has received little attention. Here we demonstrate the effects of using two different land-cover classifications to predict avian species richness and the occurrences of six individual species across the conterminous United States. We compared models built with a data set based on 14 coarsely resolved land-cover variables to models built with a data set based on 160 finely resolved land-cover variables. In general, comparable models built with the two data sets fit the data to similar degrees, but often produced strikingly different predictions in various parts of the country. By comparing the predictions made by pairs of models, we determined in which regions of the US predictions were most sensitive to differences in land-cover classification. In general, these sensitive areas were different for four of the individual species and for predictions of species richness, indicating that alternate classifications will have different effects in the analyses of different ecological phenomena and that these effects will likely vary geographically. Our results lead us to emphasize the importance of the resolution to which continuous variables are classified in the design of ecological studies.This revised version was published online in May 2005 with corrections to the Cover Date.     

The effect of land use change and ecotourism on biodiversity: a case study of Manuel Antonio,Costa Rica,from 1985 to 2008

Development in biodiversity rich areas is of global concern. While development may lead to socioeconomic benefits, this often comes concomitant with biodiversity loss and deforestation. Biodiversity rich areas present the opportunity for both improvements in socioeconomic conditions and conservation; however numerous challenges exist. Costa Rica’s Manuel Antonio National Park presents an ideal case study to investigate the balance between alternative forms of development which have contrasting environmental impacts. The Manuel Antonio region is a highly dynamic landscape experiencing deforestation, from agriculture, cattle ranching and oil palm plantations; and also reforestation from abandonment of land holdings and nature oriented tourism. Landscape dynamics are closely intertwined with the livelihoods and perspectives on biodiversity conservation of local communities, determining ecological sustainability. We use an analysis combining multi-temporal remote sensing of land cover dynamics from 1985 to 2008 with questionnaire data from local families on their socioeconomic status, perspectives on conservation, and perceived changes in local wildlife populations. Our results show that, while regeneration occurred and forest fragmentation in the area decreased from 1985 to 2008, Manuel Antonio National Park is rapidly becoming isolated. Decreasing ecological connectivity is related to the rapid expansion of oil palm plantations adjacent to the park and throughout the lowland areas. Perceived decreases in wildlife abundance and compositional change are evident throughout the area, with local communities attributing this primarily to illegal hunting activities. Nature based tourism in the area presents an effective strategy for conservation, including reductions in hunting, through increased valuation of biodiversity and protected areas, and socioeconomic advantages. However, without urgent efforts to limit deforestation and preserve the remaining forested corridor connecting the park to core primary forest, the ability to maintain biodiversity in the park will be reduced.     

Multiscale sources of variation in ecological variables: modeling spatial dispersion,elaborating sampling designs

Detection of structured spatial variation and identification of spatial scales are important aspects of ecological studies. Spatial structures can correspond to physical features of the environment or to intrinsic characteristics of ecological processes and phenomena. Spatial variability has been approached through several techniques such as classical analysis of variance, or the calculation of fractal dimensions, correlograms or variograms. Under certain assumptions, these techniques are all closely related to one another and represent equivalent tools to characterize spatial structures.Our perception of ecological variables and processes depends on the scale at which variables are measured. We propose simple nested sampling designs enabling the detection of a wide range of spatial structures that show the relationships among nested spatial scales. When it is known that the phenomenon under study is structured as a nested series of spatial scales, this provides useful information to estimate suitable sampling intervals, which are essential to establish the relationships between spatial patterns and ecological phenomena. The use of nested sampling designs helps in choosing the most suitable solutions to reduce the amount of random variation resulting from a survey. These designs are obtained by increasing the sampling intensity to detect a wider spectrum of frequencies, or by revisiting the sampling technique to select more representative sampling units.     

The effect of eye-level street greenness exposure on walking satisfaction: The mediating role of noise and PM2.5

While there are plenty of studies on the effects of neighborhood and park greenness on personal overall satisfaction and walking behavior, the relationship between street greenness exposure and walking satisfaction has received limited attention. Also, the possible pathways by which street greenness exposure affects walking satisfaction need to be further examined. To fill these research gaps, we measured eye-level street greenness using street view images, machine learning techniques and global position systems. A structural equation model was used to examine the mediating effects of objective noise and PM_2.5 exposure and related subjective annoyance, on the relationship between street greenness exposure and people’s walking satisfaction. The results showed that street greenness exposure not only had a significant direct effect on walking satisfaction, but also has a significant indirect effect on walking satisfaction through subjective environmental annoyances (including noise and PM_2.5 annoyances) rather than through objective noise and PM_2.5 exposures. Besides physical activity and social interaction, the indirect effect of street greenness exposure on walking satisfaction through subjective environmental pollution annoyance accounted for about 17.39% of the total effect and cannot be ignored. These results suggest that the urban greenness layout policy should not only consider residential greenness but should improve people’s environmental perception and walking satisfaction by allocating more greenness on streets with high noise and PM_2.5 levels.     

Vegetation density of urban parks and perceived appropriateness for recreation

There is a growing body of evidence indicating that exposure to, and activities in, nature have beneficial effects on human health. Since a majority of people in many countries live in urban areas, availability and use of urban green areas is of increasing importance to public health. In the present study we measured urban residents’ (Trondheim, Norway) recreational preferences for urban park landscapes varying in vegetation density, and aimed at an identification of background variables and environmental value orientations that we hypothesised to influence such preferences. The results showed that moderately dense scenes received the highest preference ratings. Socio-demographic variables and value orientations predicted preferences for moderate to densely vegetated scenes: A curvi-linear effect of age of respondents was found, with subjects in their mid-40s expressing a higher preference for moderate to dense vegetation, compared to younger and older subjects. Preference for moderate to dense vegetation also increased as the educational levels of the respondents increased. The preference was lower among people living in apartment blocks, relative to those living in detached houses. Of attitudinal and value-related variables, interest in wildlife, and pro-ecological value orientation (measured with the NEP scale) predicted preference for urban parks with moderate and dense vegetation. The existence of preference for relatively dense vegetation in urban parks in segments of the population has consequences for the designing of urban parks in Norway.     

Green Veining: Landscape Determinants of Biodiversity in European Agricultural Landscapes

Many semi-natural landscape elements, the so-called green veining, are disappearing from the intensively used agricultural landscapes of Europe. In order to develop or restore biodiversity in these networks, it is necessary to quantify the relation between biodiversity and amount, spatial arrangement and management intensity of green veining elements. In this review, we investigate whether biodiversity increases with the amount of green veining in an agricultural landscape following the species–area relationship, and whether a certain level of biodiversity can be reached at lower densities of green veining if green veining elements are better connected (higher spatial connectivity) or if they are managed less intensively (lower management intensity). We reviewed studies on aboveground biodiversity in green veining structures in 39 scientific papers on field and experimental studies within Europe. More of these studies focussed on management intensity than on amount or spatial configuration of green veining. Also more studies focussed on the spatial scale of individual landscape elements than on the farm or landscape scale, which may be caused by the large number of studies focussing on plant or invertebrate species. Species living at larger spatial scales, e.g. mammals and birds were not often studied at the level of green veining elements as they also use agricultural fields as part of their habitat. We could not verify the species–area relation for green veining, nor the effect of amount, spatial configuration or management intensity on this relation, because only few studies quantified the found effects and no studies were found on the effect of management intensity or spatial configuration on the species–area curve in green veining. We addressed the most important challenges for future field and model research in order to fill the identified gaps in knowledge.     

Temporal change in fragmentation of continental US forests

Changes in forest ecosystem function and condition arise from changes in forest fragmentation. Previous studies estimated forest fragmentation for the continental United States (US). In this study, new temporal land-cover data from the National Land Cover Database (NLCD) were used to estimate changes in forest fragmentation at multiple scales for the continental US. Early and late dates for the land-cover change data were ca. 1992 and ca. 2001. Forest density was used as a multi-scale index of fragmentation by measuring the proportion of forest in neighborhoods ranging in size from 2.25 to 5314.41 ha. The multi-scale forest density maps were classified using thresholds of 40% (patch), 60% (dominant), and 90% (interior) to analyze temporal change of fragmentation. The loss of dominant and interior forest showed distinct scale effects, whereas loss of patch forest was much less scale-dependent. Dominant forest loss doubled from the smallest to the largest spatial scale, while interior forest loss increased by approximately 80% from the smallest to the second largest spatial scale, then decreased somewhat. At the largest spatial scale, losses of dominant and interior forest were 5 and 10%, respectively, of their ca. 1992 amounts. In contrast, patch forest loss increased by only 25% from the smallest to largest spatial scale. These results indicate that continental US forests were sensitive to forest loss because of their already fragmented state. Forest loss would have had to occur in an unlikely spatial pattern in order to avoid the proportionately greater impact on dominant and interior forest at larger spatial scales.     

Mapping global urban greenspace: An analysis based on open land-cover data

Urban greenspace plays a positive role in improving the urban living environment, and thus extensive studies have paid attention to the mapping of urban greenspace for various applications. Recently, open and high-resolution land-cover (LC) data have been viewed as essential sources for urban greenspace mapping. However, few studies have performed a global-scale analysis; moreover, as there are commonly different LC types in an LC dataset, few studies have investigated how the definition or selection of different LC types as greenspace impacts urban greenspace mapping. Therefore, this study aims to investigate the spatial pattern of urban greenspace at a global scale and the impact on selecting different LC types for urban greenspace mapping. We employed two global open datasets (FROM-GLC10 and GHS-UCDB) and identified 13,079 global urban areas. Various LC types that potentially relate to urban greenspace and three different selections of LC types were analyzed. Results show that: 1) The spatial pattern of global urban greenspace may vary with the use of different selections; 2) The impact of whether or not to select each LC type as urban greenspace relates to not only the LC type itself but also the geographic locations. The findings may benefit urban planners and designers to select proper LC type(s) for urban greenspace studies.