Influence of tree crown characteristics on the local PM10 distribution inside an urban street canyon in Antwerp (Belgium): A model and experimental approach

Apart from influencing the amount of leaf-deposited particles, tree crown morphology will influence the local distribution of atmospheric particles. Nevertheless, tree crowns are often represented very rudimentary in three-dimensional air quality models. Therefore, the influence of tree crown representation on the local ambient PM₁₀ concentration and resulting leaf-deposited PM₁₀ mass was evaluated, using the three-dimensional computational fluid dynamics (CFD) model ENVI-met^® and ground-based LiDAR imaging. The modelled leaf-deposited PM₁₀ mass was compared to gravimetric results within three different particle size fractions (0.2–3, 3–10 and >10 μm), obtained at 20 locations within the tree crown. Modelling of the LiDAR-derived tree crown resulted in altered atmospheric PM₁₀ concentrations in the vicinity of the tree crown. Although this model study was limited to a single tree and model configuration, our results demonstrate that improving tree crown characteristics (shape, dimensions and LAD) affects the resulting local PM₁₀ distribution in ENVI-met. An accurate tree crown representation seems, therefore, of great importance when aiming at modelling the local PM distribution.     

徐州市主城区绿地景观格局对PM2.5及PM10的影响

基于研究区7个国家监测站点的PM2.5、PM10数据,运用ArcGIS、Fragstats软件对徐州市主城区的遥感影像进行解译和绿地景观格局指数的计算,结合Excel、SPSS软件分析城市绿地景观格局在不同尺度上与PM2.5、PM10浓度之间的相关性,探寻绿地景观格局与PM2.5、PM10的关系,以期为进一步研究PM2.5、PM10的影响因素提供参考依据。结果表明:绿地、农业用地和水域与PM2.5呈负相关关系;建设用地、交通用地和未利用土地与PM2.5呈正相关关系;农业用地与PM10浓度具有季节性差异,冬季和春季农地会使PM10浓度降低,夏季和秋季会使PM10浓度增大。绿地斑块所占景观面积比、绿地最大斑块指数、面积加权平均斑块形状指数与PM2.5和PM10具有明显的负相关性,景观分离度指数与其呈正相关关系。     

Effects of plant leaf surface and different pollution levels on PM2.5 adsorption capacity

We selected 6 species of landscape plants growing under different pollution levels and performed quantitative determination of PM_2.5 adsorption. We compared the measured adsorption to the leaf morphology and the water-soluble ion content. The results indicated that the pollution level and plant leaf surface PM_2.5 adsorption capacity were positively correlated. There was variation in the leaf area PM_2.5 adsorption capacity for plants in different locations, allowing us to determine species-specific effects and effects of different pollution levels. The results of the study have important significance to design strategies to reduce urban air particulate matter pollution and improve air quality.     

The influence of plant morphological structure characteristics on PM2.5 retention of leaves under different wind speeds

Exploring the relationships between plant morphological structures and PM_2.5 (particulate matter < 2.5 µm in diameter) retention on leaf surfaces and determining the key factors will help to screen tree species with high-efficiency PM reduction and improve the air purification function of green spaces. PM_2.5 retention experiments were conducted in a wind tunnel using 1800 branches from 30 species with different morphological structures under wind speeds of 1, 3.5, and 8 m/s. Eight comprehensive variables (PC1–PC8) of plant morphological structure were extracted by principal component analysis, and their relationships with PM_2.5 retention and the main influencing factors were explored by stepwise regression models. Under all of the wind speeds, the totality characteristic (PC1) (composite variable of factors including volume and total surface area) and surface area/weight density (PC2) of plant branches and leaves were the two most significant influencing factors, and they had negative effects. In addition to the aforementioned two common key factors, the leaf size (PC5) and surface roughness (PC7) were the two key positive factors at wind speeds of 1 and 3.5 m/s, while the number of branches and leaves (PC3 and PC4, respectively) were the two key positive factors at a wind speed of 8 m/s. Generally speaking, with the increase of wind speed, the effect of leaf morphological characteristics on PM_2.5 retention decreased, while the crown structure characteristics became more significant. Compared with leaf morphological characteristics, the crown morphological structure variables had greater variability and a greater impact on PM_2.5 retention. Crown morphological structure should be given more importance in screening high-efficiency PM retention tree species.     

PM2.5 reduction capacities and their relation to morphological and physiological traits in 13 landscaping tree species

Fine particulate matter (PM_2.5) is emerging as a serious environmental problem worldwide with the increase in anthropogenic emission sources, such as fossil fuels, transportation, and industries. In urban areas, where industrial complexes and human activities are concentrated, PM_2.5 poses a threat to human health. Recently, because of their ability to reduce PM_2.5, the introduction of landscaping trees as an environment-friendly solution has become popular; however, there remains a lack of research on the selection of species and their management. In this study, we quantified and compared the PM_2.5 reduction capacities of 13 major landscaping tree species and analyzed their relationship with the morphological and physiological characteristics of each species. The results showed that the amount of PM_2.5 reduction per leaf area differed among species and was the highest in Ginkgo biloba (28 165 ± 5353 # cm⁻² min⁻¹) and the lowest in Pinus strobus (1602 ± 186 # cm⁻² min⁻¹). Moreover, PM_2.5 reduction by the broadleaf species (18 802 ± 1638 # cm⁻² min⁻¹) was approximately 8.6-fold higher than that of the needleleaf species (2194 ± 307 # cm⁻² min⁻¹). Correlation analysis revealed that differences in PM_2.5 reduction were explained by differences in specific leaf area between species (P = 0.004) and by the length of margin per leaf area among individual trees (P < 0.05). Additionally, reduction in PM_2.5 correlated with photosynthetic properties such as maximum assimilation and carboxylation rates (P < 0.001), indicating that PM_2.5 is reduced not only by physical adsorption but also by physiological processes. These findings emphasize that for effective reduction in PM_2.5 using landscaping trees, comprehensive consideration of the morphological and physiological characteristics of the species is essential during species selection, and that continuous management is also necessary to maintain the active physiological conditions of the trees.     

Using indicators of land-use development intensity to assess the condition of coastal wetlands in Hawai‘i

Although wetland condition assessment procedures have been developed, validated, and calibrated in the continental United States, they have not yet been fully developed or field-tested for wetlands in Hawai‘i. In order to address the need for comprehensive assessment methods for Hawaiian coastal wetlands, our research compared three indicators of landscape condition (landscape development intensity, road density, and forest cover) with wetland condition as measured by rapid assessment methods (RAM) and detailed field data collected on soil and water quality. We predicted that wetlands located in the least developed landscapes would have more nutrient rich soils, yet lower nutrient levels in the surface water, and would receive the highest rapid assessment scores. The hypotheses of our study were generally supported. However, while the correlations between landscape variables and δ¹⁵N isotopes and CRAM scores were relatively strong, the correlations between the landscape indicators and the other Level II and III field indicators were not very strong. These results suggest that further calibration and refinement of metrics is needed in order to more accurately assess the condition of Hawaiian coastal wetlands. A more detailed land use map, in addition to more comprehensive assessments of wetland water quality and biotic integrity would likely improve the relationships between indicators of landscape condition and wetland condition. Nonetheless, our research demonstrated that landscape analysis at larger scales (1,000 m buffers and watersheds) could provide managers with valuable information on how regional stressors may be affecting wetland water quality (measured as δ¹⁵N in plant tissue) as well as overall wetland condition (RAM scores).     

Structure of an urban green space indirectly affects the distribution of airborne particulate matter: A study based on structural equation modelling

Urban green spaces can effectively regulate microclimate and improve air quality. However, the relationship between the structure of an urban green space, meteorological conditions, and the concentration distribution of different sized particles inside and outside of green spaces is unclear. In this study, a field survey was conducted on the structures of 188 green spaces in Beijing. The temperature and relative humidity were also monitored, and the concentrations of different sized particles were measured both inside and outside of the selected green spaces to comprehensively analyse the relationships between these variables and the structure of a green space. The results of structural equation modelling showed that the structure of a green space indirectly affected the concentration distribution of particulate matter (PM) through the effects of cooling and humidification, while the direct effect was not obvious. In addition, the impact mechanisms of the structure of a green space on the concentration distribution of particles differed between PM₁, PM_1–5, and PM_5–25, primarily due to the influence of particle size and meteorological factors on the movement of PM. This study deepens the understanding of the influencing mechanisms of the structure of a green space on the concentration distribution of PM, thus providing an important reference for subsequent related field and numerical simulation research.     

A spatially-explicit method to assess the dry deposition of air pollution by urban forests in the city of Florence,Italy

Urban forests (UF) provide a range of important ecosystem services (ES) for human well-being. Relevant ES delivered by UF include urban temperature regulation, runoff mitigation, noise reduction, recreation, and air purification. In this study the potential of air pollution removal by UF in the city of Florence (Italy) was investigated. Two main air pollutants were considered – particulate matter (PM₁₀) and tropospheric ozone (O₃) – with the aim of providing a methodological framework for mapping air pollutant removal by UF and assessing the percent removal of air pollutant.The distribution of UF was mapped by high spatial resolution remote sensing data and classified into seven forest categories. The Leaf Area Index (LAI) was estimated spatially using a regression model between in-field LAI survey and Airborne Laser Scanning data and it was found to be in good linear agreement with estimates from ground-based measurements (R² = 0.88 and RMSE% = 11%). We applied pollution deposition equations by using pollution concentrations measured at urban monitoring stations and then estimated the pollutant removal potential of the UF: annual O₃ and PM₁₀ removal accounted for 77.9 t and 171.3 t, respectively. O₃ and PM₁₀ removal rates by evergreen broadleaves (16.1 and 27.3 g/m²), conifers (10.9 and 28.5 g/m²), and mixed evergreen species (15.8 and 31.7 g/m²) were higher than by deciduous broadleaf stands (4.1 and 10 g/m²). However, deciduous forests exhibited the largest total removal due to the high percentage of tree cover within the city. The present study confirms that UF play an important role in air purification in Mediterranean cities as they can remove monthly up to 5% of O₃ and 13% of PM₁₀.     

Does street canyon morphology shape particulate matter reduction capacity by street trees in real urban environments?

Urban street canyon morphology plays an important role in outdoor air quality and should be considered in tree planting schemes. However, the air pollutant reduction rate by street trees in different types of street canyon has rarely been analyzed for real urban environments. Therefore, this study conducted field investigation of 15 street canyons in residential areas to assess the reduction rate of particulate matter (PM) by trees in canyons with varying aspect ratio (AR) and orientation. The species of trees planted in these streets were Sophora japonica, Populus alba 'Berolinensis' L., Salix babylonica, Fraxinus chinensis, Pinus tabulaeformis, and Ulmus pumila. In the presence of trees, the mass concentration of fine PM (PM₁) decreased most in narrow canyons (AR = 1.37–3.02), while the concentration of coarse PM (PM₁₀) decreased most in wide canyons (AR = 0.45–0.69). The PM concentration increased most with tree planting in medium canyons (AR = 0.79–1.08). Additionally, street trees reduced fine PM concentration more in canyons with a 45° angle to the prevailing wind than in canyons aligned parallel to the prevailing wind. But they reduced coarse PM more in canyons aligned parallel to the prevailing wind than in canyons with a 45° angle to the prevailing wind. In comparison with tree-free cases, tree planting weakened the correlation between AR and coarse PM concentration, whereas no difference in correlation was found between AR and fine PM concentration. Overall, street canyon morphology should be considered seriously in developing tree planting guidelines for built-up environments.     

Spatial attenuation of ambient particulate matter air pollution within an urbanised native forest patch

Of interest to researchers and urban planners is the effect of urban forests on concentrations of ambient air pollution. Although estimates of the attenuation effect of urban vegetation on levels of air pollution have been put forward, there have been few monitored data on small-scale changes within forests, especially in urban forest patches. This study explores the spatial attenuation of particulate matter air pollution less than 10 μ in diameter (PM₁₀) within the confines of an evergreen broadleaved urban forest patch in Christchurch, New Zealand, a city with high levels of PM₁₀ winter air pollution. The monitoring network consisted of eight monitoring sites at various distances from the edge of the canopy and was operated on 13 winter nights when conditions were conducive for high pollution events. A negative gradient of particulate concentration was found, moving from higher mean PM10 concentrations outside the forest (mean=31.5 μg m^?3) to lower concentrations deep within the forest (mean=22.4 μg m^?3). A mixed-effects model applied to monitor meteorological, spatial and pollution data indicated temperature and an interaction between wind speed and temperature were also significant (P?0.05) predictors of particulate concentration. These results provide evidence of the potential role that urban forest patches may play in mitigating particulate matter air pollution and should be considered in plans for improving urban air quality.     

Particulate matter pollution capture by leaves of seventeen living wall species with special reference to rail-traffic at a metropolitan station

Atmospheric Particulate Matter (PM) constitutes a considerable fraction of urban air pollution, and urban greening is a potential method of mitigating this pollution. The value of living wall systems has received scant attention in this respect. This study examined the inter-species variation of particulate capture by leaves of seventeen plant species present in a living wall at New Street railway station, Birmingham, UK. The densities of different size fractions of particulate pollutants (PM₁, PM_2.5 and PM₁₀) on 20 leaves per species were quantified using an Environmental Scanning Electron Microscope (ESEM) and ImageJ image-analysis software. The overall ability of plant leaves to remove PM from air was quantified using PM density and LAI (Leaf Area Index); any inter-species variations were identified using one-way Anova followed by Tukey’s pairwise comparison. This study demonstrates a considerable potential for living wall plants to remove particulate pollutants from the atmosphere. PM capture levels on leaves of different plant species were significantly different for all particle size fractions (P < 0.001). Smaller-leaved Buxus sempervirens L., Hebe albicans Cockayne, Thymus vulgaris L. and Hebe x youngii Metcalf showed significantly higher capture levels for all PM size fractions. PM densities on adaxial surfaces of the leaves were significantly higher compared to abaxial surfaces in the majority of the species studied (t-test, P < 0.05). According to EDX (Energy Dispersive X-ray) analysis, a wide spectrum of elements were captured by the leaves of the living wall plants, which were mainly typical railway exhaust particles and soil dust. Smaller leaves, and hairy and waxy leaf surfaces, appear to be leaf traits facilitating removal of PM from the air, and hence a collection of species which share these characters would probably optimize the benefit of living wall systems as atmospheric PM filters.     

Particulate phase polycyclic aromatic hydrocarbons in the ambient atmosphere of a protected and ecologically sensitive area in a tropical megacity

This study reports, for the first time, the profiles and source analysis of 16 US EPA priority polycyclic aromatic hydrocarbons (PAHs) associated with PM₁₀ (particulate matter with aerodynamic diameter ≤10 μm) at a protected and ecologically sensitive area – the Yamuna Biodiversity Park – located in the megacity Delhi, India. Weekly PM₁₀ sampling was carried out at this location for 1 year (2009–2010) and the annual mean PM₁₀ level was found to be ～9 times the World Health Organization limit. Seasonal variation of PAHs (range 37.2–74.0 ng m^?3) was significant with winter values being 72% and 68% higher than summer and monsoon respectively. Principal component analysis coupled with multiple linear regression identified diesel, natural gas and lubricating oil combustion (49.5%), wood combustion (25.4%), gasoline (15.5%) and coal combustion (9.6%) sources for the observed PAHs. Heavy traffic on the national highway and arterial roads and domestic emissions from suburban households in the vicinity of the park appeared to have significantly affected its air quality. A substantial portion (～55%) of the aerosol PAH load was comprised of carcinogenic species, which yielded a considerably high lifetime inhalation cancer risk estimate (8.7E?04). If considered as a conservative lower-bound estimate, this risk translates into ～211 excess cancer cases for lifetime inhalation exposure to the observed PAH concentrations in Delhi.     

On the challenges of modeling the net radiative forcing of wetlands: reconsidering Mitsch et al. 2013

Wetlands play a role in regulating global climate by removing carbon dioxide (CO₂) from the atmosphere and sequestering it as soil carbon, and by emitting methane (CH₄) and nitrous oxide (N₂O) to the atmosphere. In a recent article in this journal (Mitsch et al. Landscape Ecol 28:583–597, 2013), CO₂ sequestration and CH₄ emissions were modeled for several freshwater wetlands that vary in vegetation type, climate, and hydrology. The authors of that study made significant errors that caused them to underestimate the importance of wetland CH₄ emissions on climate dynamics. Here, I reanalyze the Mitsch et al. dataset and show that all of their wetlands had an initial warming effect but eventually caused negative net radiative forcing within ~60–14,000 years, depending on the ratio of CO₂ sequestration to CH₄ emissions. The addition of a N₂O component to the model suggested that typical wetland N₂O emission rates would contribute only a minor burden to wetland radiative forcing, although specific application of this three-gas model is limited by the paucity of sites where CO₂ sequestration, CH₄ emission, and N₂O exchange rates have all been measured. Across the landscape, many natural wetlands may already cause negative net radiative forcing when integrated over their lifetime. However, caution should be applied when using carbon sequestration as a rationale for designing wetland construction and restoration projects since freshwater wetlands may have a net positive (warming) effect on climate for decades to centuries or longer.     

Hierarchical factors impacting the distribution of an invasive species: landscape context and propagule pressure

Distribution of invasive species is the outcome of several processes that interact at different hierarchical levels. A hierarchical approach is taken here to analyze the landscape level distribution pattern of Purple loosestrife (Lythrum salicaria), an aggressive wetland invader. Using land use/land cover (LULC) data and loosestrife presence records we were able to identify and characterize the key processes that resulted in the observed large-scale distribution. Herbaceous wetlands, edges of open water sites, and developed open spaces were identified as loosestrife’s preferred LULC types. Analysis of spatial neighborhoods of these key land cover types revealed that disturbance modified open water edges and herbaceous wetlands were more likely to be invaded by loosestrife. Moreover, developed open spaces appear to hold loosestrife only if there is water rich conditions in the immediate neighborhood. Neighborhood analyses also showed that wetlands and open water edges embedded within a neighborhood matrix of grassland and agricultural environments is less likely to contain loosestrife. Finally, there is strong evidence of propagule pressure. Open water edges and wetlands invaded by loosestrife had on an average more loosestrife as neighbors than uninvaded lake edges and wetlands. Taken together, it is apparent that loosestrife’s landscape level distribution is the outcome of three nested hierarchical factors: habitat preference, the spatial neighborhood and propagule pressure. The patterns characterized suggests that occurrence of an invasive species is not merely contingent on availability of suitable habitat but is also influenced by human actions within its proximity, and is further constrained by dispersal limitation.     

A polygon-based spatial (PBS) model for simulating landscape change

A spatial model of long term habitat succession at a degrading Louisiana wetland was constructed based upon simulating exchanges across irregularly shaped polygons. Polygons represented the natural morphology which is indicative of the natural landscape. The PBS model was partially successful in simulating spatial habitat changes over a 28-year period when more than 1000 ha of wetland loss occurred (r²=.56). General landscape trends did, however, emerge from the model development. Areas of high annual water level fluctuations, and high primary productivity were less likely to change from wetlands to open water and were most likely to recover if altered. We discuss the potential for predictive improvement and for integration with polygon-based geographic information systems, and conclude that a PBS model demonstrates the need for spatially explicit landscape management.     

国内外城市湿地公园游憩价值开发典型案例分析

梳理城市湿地公园游憩价值的构成要素及景观美学、休闲娱乐、康体健身、自然教育、民俗体验价值的内容.以伦敦湿地中心、香港城市湿地公园、杭州西溪湿地公园为案例,分析城市湿地公园在基础构成要素不同的背景下确立自身的规划设计和理念、开发模式、游憩产品策划.     

Research on the horizontal reduction effect of urban roadside green belt on atmospheric particulate matter in a semi-arid area

In this study, the horizontal abatement effects of green belts on atmospheric particulate matter at different horizontal distances and plant community structures were investigated in urban roadside green belts in semi-arid areas.We collected mass concentrations of six types of atmospheric particulate matter (PM) per unit time of PM_0.3, PM_0.5, PM_1.0, PM_2.5, PM_5.0, and PM₁₀ and various meteorological indices, to compare the horizontal reduction efficiency of different distances and plant community structures on different particle sizes, and to establish a support vector machine model. The results showed that 1) the horizontal abatement efficiency of green belts was different for six particle sizes, while the horizontal abatement rate strengthened as the particle size increased. The abatement rate was significantly correlated with microclimatic factors such as temperature and humidity, but less correlated with wind speed. 2) The horizontal abatement rate of roadside green belts on atmospheric particulate matter varies with the increase of horizontal distance in a "single-peak" or "double-peak" pattern, with the best abatement effect of green belts on each particle size at a horizontal distance of 45m. Among the four types of plant community structures, the strongest abatement ability was in the arbor-shrub-herb structure. 3) The correctly tuned prediction model, based on Support Vector Machines, resulted in better horizontal abatement ability of green belts on atmospheric PM. The prediction results showed that the average horizontal abatement rate has the best abatement effect at 45–55 m, peaked at 50 m, and formed stagnant dust at 65 m. In the design of urban road green spaces in semi-arid areas, to achieve the best dust retention effect, the green belt width should be ≥40 m and it is desirable to choose arbor-shrub-herb structures. This study provides a design basis and theoretical support for urban road green space planning in semi-arid areas.     

Modeling dissolved organic carbon in subalpine and alpine lakes with GIS and remote sensing

Current global trends in lake dissolved organic carbon (DOC) concentrations suggest a need for tools to more broadly measure and predict variation in DOC at regional landscape scales. This is particularly true for more remote subalpine and alpine regions where access is difficult and the minimal levels of anthropogenic watershed disturbance allow these systems to serve as valuable reference sites for long-term climate change. Here geographic information system (GIS) and remote sensing tools are used to develop simple predictive models that define relationships between watershed variables known to influence lake DOC concentrations and lake water color in the Absaroka-Beartooth Wilderness in Montana and Wyoming, USA. Variables examined include watershed area, topography, and vegetation cover. The resulting GIS model predicts DOC concentrations at the lake watershed scale with a high degree of accuracy (R ² = 0.92; P ≤ 0.001) by including two variables: vegetation coverage (representing sites of organic carbon fixation) and areas of low slope (0–5%) within the watershed (wetland sites of DOC production). Importantly, this latter variable includes not only surficially visible wetlands, but “cryptic” subsurface wetlands. Modeling with Advanced Land Imager satellite remote sensing data provided a weaker relationship with water color and DOC concentrations (R ² = 0.725; P ≤ 0.001). Model extrapolation is limited by small sample sizes but these models show promise in predicting lake DOC in subalpine and alpine regions.     

The accuracy of land cover-based wetland assessments is influenced by landscape extent

Widespread degradation of wetlands has motivated the development of tools to evaluate wetland condition. The application of field-based tools over large regions can be prohibitively expensive; however, land cover data may provide a surrogate for intensive assessments, enabling rapid and cost-effective evaluation of wetlands throughout whole regions. Our goal was to determine if land cover data could be used to estimate the biotic integrity of wetlands in Alberta??s Beaverhills watershed. Biotic integrity was measured using both plant- and bird-based indices of biotic integrity (IBIs) in 45 wetlands. Land cover data were extracted from seven nested landscape extents (100?C3,000?m radii) and used to model IBI scores. Strong, significant predictions of IBI scores were achieved using land cover data from every spatial extent, even after factoring out the influence of location to address the spatial autocorrelation of land cover classes. Plant-based IBI scores were best predicted using data from 100?m buffers and bird-based IBI scores were best predicted using data extracted from 500?m buffers. Road cover or density and measures of the proportion of disturbed land were consistent predictors of IBI score, suggesting their universal importance to plant and bird communities. Simplified models using the proportion of undisturbed land were less accurate than more detailed models (reductions in r ² of 0.31?C0.32). Regardless of the level of detail in land cover classification, our results emphasize the need to optimize landscape extent for the taxonomic group of interest: an issue that is typically poorly articulated in studies reporting on the development of GIS-based assessment methods. Our results also highlight the need to calibrate models in test areas before scaling up, to ensure predictive accuracy.     

Importance of Wetland Landscape Structure to Shorebirds Wintering in an Agricultural Valley

Only recently has the influence of landscape structure on habitat use been a research focus in wetland systems. During non-breeding periods when food can be locally limited, wetland spatial pattern across a landscape may be of great importance in determining wetland use. We studied the influence of landscape structure on abundances of wintering Dunlin (Calidris alpina) and Killdeer (Charadrius vociferus) observed on wetlands in the agricultural Willamette Valley of Oregon, USA, during two winters (1999–2000, 2000–2001) of differing rainfall. We examined (1) shorebird use within a sample of 100 km² regions differing in landscape structure (hectares of shorebird habitat [wet, unvegetated]) and (2) use of sites differing in landscape context (area of shorebird habitat within a species-defined radius). For use of sites, we also assessed the influence of two local characteristics: percent of soil exposed and area of wet habitat. We analyzed data using linear regression and information-theoretic modeling. During the dry winter (2000–2001), Dunlin were attracted to regions with more wetland habitat and their abundances at sites increased with greater area of shorebird habitat within both the site and the surrounding landscape. In contrast, Dunlin abundances at sites were related to availability of habitat at only a local scale during the wet winter (1999–2000). Regional habitat availability was of little importance in predicting Killdeer distributions, and Killdeer site use appeared unrelated to habitat distributions at both landscape and local scales. Results suggest prioritizing sites for conservation that are located in areas with high wetland coverage.