Use of landscape pattern metrics and multiscale data in aquatic species distribution models: a case study of a freshwater mussel

The distributions of freshwater mussels are controlled by landscape factors operating at multiple spatial scales. Changes in land use/land cover (LULC) have been implicated in severe population declines and range contractions of freshwater mussels across North America. Despite widespread recognition of multiscale influences few studies have addressed these issues when developing distribution models. Furthermore, most studies have disregarded the role of landscape pattern in regulating aquatic species distributions, focusing only on landscape composition. In this study, the distribution of Rabbitsfoot (Quadrula cylindrica) in the upper Green River system (Ohio River drainage) is modeled with environmental variables from multiple scales: subcatchment, riparian buffer, and reach buffer. Four types of landscape environment metrics are used, including: LULC pattern, LULC composition, soil composition, and geology composition. The study shows that LULC pattern metrics are very useful in modeling the distribution of Rabbitsfoot. Together with LULC compositional metrics, pattern metrics permit a more detailed analysis of functional linkages between aquatic species distributions and landscape structure. Moreover, the inclusion of multiple spatial scales is necessary to accurately model the hierarchical processes in stream systems. Geomorphic features play important roles in regulating species distributions at intermediate and large scales while LULC variables appear more influential at proximal scales.     

How does the landscape context of occurrence data influence models of invasion risk? A comparison of independent datasets in Massachusetts,USA

The spatial distribution of non-native, invasive plants on the landscape is strongly influenced by human action. People introduce non-native species to new landscapes and regions (propagule pressure) as well as increase ecosystem invasibility through disturbance of native ecosystems. However, the relative importance of different landscape drivers of invasion may vary with landscape context (i.e., the types and amounts of surrounding land cover and land use). If so, data collected in one context may not be appropriate for predicting invasion risk across a broader landscape. To test whether independent occurrence datasets suggest similar landscape drivers of invasion, we compared landscape models based on data compiled by the Invasive Plant Atlas of New England (IPANE), which are contributed opportunistically by trained citizen scientists, to models based on Forest Stewardship plans (FSPs), which are located in privately owned and relatively undisturbed forests. We evaluated 16 landscape variables related to propagule pressure and/or disturbance for significant predictors of invasive plant presence based on presence/absence and count regression models. Presence and richness of invasive plants within FSPs was most influenced by proportion of open land and proximity to residential areas, which are both sources of propagules in forest interiors. In contrast, IPANE invasive plant presence and richness for the same area was influenced by distance to roads and streams. These results suggest that landscape drivers of invasion vary considerably depending on landscape context, and the choice of occurrence dataset will strongly influence model results.     

Socioeconomics drive woody invasive plant richness in New England, USA through forest fragmentation

Woody invasive plants are an increasing component of the New England flora. Their success and geographic spread are mediated in part by landscape characteristics. We tested whether woody invasive plant richness was higher in landscapes with many forest edges relative to other forest types and explained land use/land cover and forest fragmentation patterns using socioeconomic and physical variables. Our models demonstrated that woody invasive plant richness was higher in landscapes with more edge forest relative to patch, perforated, and especially core forest types. Using spatially-explicit, hierarchical Bayesian, compositional data models we showed that infrastructure and physical factors, including road length and elevation range, and time-lagged socioeconomic factors, primarily population, help to explain development and forest fragmentation patterns. Our social–ecological approach identified landscape patterns driven by human development and linked them to increased woody plant invasions. Identifying these landscape patterns will aid ongoing efforts to use current distribution patterns to better predict where invasive species may occur in unsampled regions under current and future conditions.     

Modeling relative habitat suitability of southern Florida for invasive Burmese pythons (<Emphasis Type="Italic">Python molurus bivittatus</Emphasis>)

Context

Invasive Burmese pythons are altering the ecology of southern Florida and their distribution is expanding northward. Understanding their habitat use is an important step in understanding the pathways of the invasion.

Objectives

This study identifies key landscape variables in predicting relative habitat suitability for pythons at the present stage of invasion through presence-only ecological niche modeling using geographical sampling bias correction.

Methods

We used 2014 presence-only observations from the EDDMapS database and three landscape variables to model habitat suitability: fine-scale land cover, home range-level land cover, and distance to open freshwater or wetland. Ten geographical sampling bias correction scenarios based on road presence and sampling effort were evaluated to improve the efficacy of modeling.

Results

The best performing models treated road presence as a binary factor rather than a continuous decrease in sampling effort with distance from roads. Home range-level cover contributed the most to the final prediction, followed by proximity to water and fine-scale land cover. Estuarine habitat and freshwater wetlands were the most important variables to contribute to python habitat suitability at both the home range-level and fine-scale. Suitability was highest within 30 m of open freshwater and wetlands.

Conclusions

This study provides quantifiable, predictive relationships between habitat types and python presence at the current stage of invasion. This knowledge can elucidate future targeted studies of python habitat use and behavior and help inform management efforts. Furthermore, it illustrates how estimates of relative habitat suitability derived from MaxEnt can be improved by both multi-scale perspectives on habitat and consideration of a variety of bias correction scenarios for selecting background points.

     

A method for the use of landscape metrics in freshwater research and management

Freshwater research and management efforts could be greatly enhanced by a better understanding of the relationship between landscape-scale factors and water quality indicators. This is particularly true in urban areas, where land transformation impacts stream systems at a variety of scales. Despite advances in landscape quantification methods, several studies attempting to elucidate the relationship between land use/land cover (LULC) and water quality have resulted in mixed conclusions. However, these studies have largely relied on compositional landscape metrics. For urban and urbanizing watersheds in particular, the use of metrics that capture spatial pattern may further aid in distinguishing the effects of various urban growth patterns, as well as exploring the interplay between environmental and socioeconomic variables. However, to be truly useful for freshwater applications, pattern metrics must be optimized based on characteristic watershed properties and common water quality point sampling methods. Using a freely available LULC data set for the Santa Clara Basin, California, USA, we quantified landscape composition and configuration for subwatershed areas upstream of individual sampling sites, reducing the number of metrics based on: (1) sensitivity to changes in extent and (2) redundancy, as determined by a multivariate factor analysis. The first two factors, interpreted as (1) patch density and distribution and (2) patch shape and landscape subdivision, explained approximately 85% of the variation in the data set, and are highly reflective of the heterogeneous urban development pattern found in the study area. Although offering slightly less explanatory power, compositional metrics can provide important contextual information.     

Prey distribution,potential landscape supplementation,and urbanization affect occupancy dynamics of American mink in streams

Context

Land-use change can reduce and isolate suitable habitat generating spatial variation in resource availability. Improving species distribution models requires a multi-scale understanding of resource requirements and species’ sensitivities to novel landscapes.

Objectives

We investigated how the spatial distribution of supplementary habitats (permanent wetlands), urbanization, water depths, and distribution of a key prey species (muskrat; Ondatra zibethicus) influence occupancy dynamics of American mink (Neovison vison). Although mink are widespread across North America and a destructive invasive species in Europe, South America, and Asia, we have a limited understanding of factors affecting their spatial distribution.

Methods

We used 6 years of presence–absence data (2007–2012) to evaluate occupancy dynamics of mink at 58–90 stream sites along an urbanization gradient in Illinois, USA. We predicted negative relationships between stream occupancy and urban land cover and distance from permanent wetlands, and positive associations with muskrat presence, water depth, and riparian zone width.

Results

Contrary to our hypothesis, stream sites closer to permanent wetlands had lower occupancy and colonization rates for mink. Occupancy and colonization rates were higher at sites with deeper water, and colonization rates were related negatively to urbanization. Mink were more likely to leave stream habitat if muskrats were not present and permanent wetlands were nearby.

Conclusion

Factors interplaying across multiple scales influenced occupancy dynamics of mink in stream habitat in a highly modified landscape. Our results highlight the importance of considering both direct measures of prey availability and the spatial distribution of supplementary habitats to improve habitat-selection models for carnivores.

     

Rural housing is related to plant invasions in forests of southern Wisconsin,USA

Forests throughout the US are invaded by non-native invasive plants. Rural housing may contribute to non-native plant invasions by introducing plants via landscaping, and by creating habitat conditions favorable for invaders. The objective of this paper was to test the hypothesis that rural housing is a significant factor explaining the distribution of invasive non-native plants in temperate forests of the Midwestern US. In the Baraboo Hills, Wisconsin, we sampled 105 plots in forest interiors. We recorded richness and abundance of the most common invasive non-native plants and measured rural housing, human-caused landscape fragmentation (e.g. roads and forest edges), forest structure and topography. We used regression analysis to identify the variables more related to the distribution of non-native invasive plants (best subset and hierarchical partitioning analyses for richness and abundance and logistic regression for presence/absence of individual species). Housing variables had the strongest association with richness of non-native invasive plants along with distance to forest edge and elevation, while the number of houses in a 1 km buffer around each plot was the variable most strongly associated with abundance of non-native invasive plants. Rhamnus cathartica and Lonicera spp. were most strongly associated with rural housing and fragmentation. Berberis thumbergii and Rosa multiflora were associated with gentle slopes and low elevation, while Alliaria petiolata was associated with higher cover of native vegetation and stands with no recent logging history. Housing development inside or adjacent to forests of high conservation value and the use of non-native invasive plants for landscaping should be discouraged.     

Influences of habitat and land cover on fish distributions along a tributary to Lake Ontario,New York

Influences of habitat and land cover on fish distributions were determined along a lentic–lotic gradient along a tributary to Lake Ontario, New York. Nonmetric multidimensional scaling, cluster analysis, and specific characterization methods were used to classify the fish species into five groups based on their similar patterns of distribution, species-specific habitat relationship, and relative abundance observed along the gradient. A stepwise regression approach was used to select the best habitat and land cover variables to explain variations in the distribution pattern of each fish group. Distribution patterns of the five fish groups were significantly explained by either a set of the selected habitat or land cover predictor variables or a combination of both. Of the 10 habitat variables, water depth, current velocity, aquatic plants, algae, woody debris, sand, and rock-bedrock were selected to explain the variations in distribution patterns of one or more fish groups. Of the 16 land cover types, evergreen wetlands, evergreen plantations, successional shrubs, shrub swamps, roads, and urban areas were selected to explain the variations in distribution patterns of at least one fish group.     

Landscape fragmentation,land-use legacy and propagule pressure promote plant invasion on coastal dunes: a patch-based approach

Coastal dunes and sand areas are reported to be among the habitats most invaded by alien species in Europe. Landscape pattern could be a significant driver in invasion processes in parallel with land-use legacy. Fragmentation of natural habitats combined with the availability of propagules from the surrounding matrix may enhance the invisibility of ecological communities. Based on multitemporal land cover maps (1954–2008) and a floristic database, we analyzed how habitat fragmentation, propagule pressure and land-use legacy have affected alien plants’ presence and richness on natural dune patches along the Lazio Coast (Central Italy). Floristic data were derived from an existing geo-database of random vegetation plots (64 m²). A set of landscape patch-based metrics, considered to be adequate proxies of the main processes affecting alien invasion and richness, was calculated. First, we fit a generalized linear model (GLM) with binomial errors to assess which landscape metrics are influencing patch invasion. Second, we extracted invaded patches and, with GLMs, we investigated how landscape metrics affect average alien species richness. Alien invasion and alien richness seem to be affected by different processes: although alien invasion of each patch is strongly associated with its land-use legacy, the richness of aliens is more affected by landscape fragmentation and by the propagule pressure to which patch is exposed. By integrating spatial and temporal landscape metrics with floristic data, we were able to disentangle the relations of landscape fragmentation, propagule pressure and land-use legacy with the presence and richness of alien plants. The methodological approach here adopted could be easily extended to other alien species and ecosystems, offering scientifically sound support to prevent the high economic costs derived from both the control and the eradication of aliens.     

Modelling Habitat Suitability for Deciduous Forest Focal Species – A Sensitivity Analysis using Different Satellite Land Cover Data

We explored the usefulness of three satellite land cover data sets available to land managers in south-central Sweden for conservation planning using four deciduous forest focal resident bird species with different habitat requirements. Habitat suitability models using empirical species-specific habitat parameters and a Geographic Information System were applied to evaluate and compare the degree of consistency among three different land cover data sets. The study area encompassed 10,000 km² in a landscape mosaic of managed boreal forests and is within the distribution range of all four focal species. Although the three land cover data sets indicated similar total amounts of deciduous forest, the habitat suitability models showed that different land cover data yielded inconsistent results regarding the amount and distribution of suitable habitat within 5×5 km grid cells. Given this sensitivity to the choice of land cover data sets, the habitat suitability models showed positive relationships among the selected focal species for each land cover data set separately. As expected, decreasing amounts of suitable habitat were identified for species with higher specialisation. Thus, because habitat suitability models are an appropriate way to gain insight into the functionality and connectivity of habitat networks, land cover data must be carefully evaluated and if necessary combined with other landscape information for effective conservation planning.     

Historic landscape change and habitat loss: the case of black grouse in Lower Saxony,Germany

The declines of many specialist bird species in the agricultural landscapes of Central Europe have resulted in small and isolated populations. In the case of the black grouse, a ground-nesting bird species with large spatial requirements, empiric evidence about underlying landscape changes is scarce. In this study, we examined land cover and land cover changes in a farmland-forest mosaic in eastern Lower Saxony, Germany and how they affect occurrence and persistence of black grouse. Spatial information came from historic topographic maps from 1958 to 1975. The results show profound conversions of habitat to forest and farmland but also an increase in settlement area. Habitat conversions and suburbanization were negative correlates of black grouse persistence. Habitat models from before and after a decline period differed in some of the predictors and suggest black grouse habitat to be more diverse before the land cover changes. Our study confirms that land use factors at a landscape scale extent contribute to explain black grouse occurrence and thus can complement important small scale factors like the quality and size of individual habitat patches. Results also show that landscape factors affect black grouse distribution predominantly from an area much greater than an individual black grouse home range. Our models may be further evaluated on present-day landscapes and might be used to evaluate large-scale habitat availability for black grouse.     

Assessing the effects of applying landscape ecological spatial concepts on future habitat quantity and quality in an urbanizing landscape

This study develops a quantitative approach to evaluate the application of design concepts that link landscape ecology theory to landscape planning. Landscape ecology principles were used to develop spatial concepts for creating an armature of open space in areas subject to rapid urbanization. It focuses on the predicted urban expansion of Damascus, Oregon, as a case study. An alternative futures study was used to test three open space spatial concepts for patches, corridors and networks contrasted with compact and dispersed urban development patterns. Eight scenarios of land use and land cover, over 50 years, were defined based on different spatial design concepts to evaluate their effects on habitat quantity and quality and analyze the tradeoffs between urban development and conservation of three focal wildlife species: red-legged frog, western meadowlark, and Douglas squirrel. Open space spatial concepts highly influenced habitat quantity and quality differences among scenarios. Development patterns showed lower influence on those variables. Scenarios with no landscape ecological spatial concept provided the most land for urban development but reduced habitat quantity and quality. Greenway scenarios presented increases of habitats, but failed to provide sufficient habitats for western meadowlark. Park system scenarios also presented an increase on the amount of habitats, but high-quality habitats for western meadowlark and red-legged frog decreased. Network scenarios presented the best overall amount of habitats and increase of high-quality habitats for the three species, but constrained urban development options.     

Using animal movement behavior to categorize land cover and predict consequences for connectivity and patch residence times

Context

Landscape-scale population dynamics are driven in part by movement within and dispersal among habitat patches. Predicting these processes requires information about how movement behavior varies among land cover types.

Objectives

We investigated how butterfly movement in a heterogeneous landscape varies within and between habitat and matrix land cover types, and the implications of these differences for within-patch residence times and among-patch connectivity.

Methods

We empirically measured movement behavior in the Baltimore checkerspot butterfly (Euphydryas phaeton) in three land cover classes that broadly constitute habitat and two classes that constitute matrix. We also measured habitat preference at boundaries. We predicted patch residence times and interpatch dispersal using movement parameters estimated separately for each habitat and matrix land cover subclass (5 categories), or for combined habitat and combined matrix land cover classes (2 categories). We evaluated the effects of including edge behavior on all metrics.

Results

Overall, movement was slower within habitat land cover types, and faster in matrix cover types. Butterflies at forest edges were biased to remain in open areas, and connectivity and patch residence times were most affected by behavior at structural edges. Differences in movement between matrix subclasses had a greater effect on predictions about connectivity than differences between habitat subclasses. Differences in movement among habitat subclasses had a greater effect on residence times.

Conclusions

Our findings highlight the importance of careful classification of movement and land cover in heterogeneous landscapes, and reveal how subtle differences in behavioral responses to land cover can affect landscape-scale outcomes.

     

Relationships between land cover and the surface urban heat island: seasonal variability and effects of spatial and thematic resolution of land cover data on predicting land surface temperatures

We investigated the seasonal variability of the relationships between land surface temperature (LST) and land use/land cover (LULC) variables, and how the spatial and thematic resolutions of LULC variables affect these relationships. We derived LST data from Landsat-7 Enhanced Thematic Mapper (ETM+) images acquired from four different seasons. We used three LULC datasets: (1) 0.6 m resolution land cover data; (2) 30 m resolution land cover data (NLCD 2001); and (3) 30 m resolution Normalized Difference Vegetation Index data derived from the same ETM+ images (though from different bands) used for LST calculation. We developed ten models to evaluate effects of spatial and thematic resolution of LULC data on the observed relationships between LST and LULC variables for each season. We found that the directions of the effects of LULC variables on predicting LST were consistent across seasons, but the magnitude of effects, varied by season, providing the strongest predictive capacity during summer and the weakest during winter. Percent of imperviousness was the best predictor on LST with relatively consistent explanatory power across seasons, which alone explained approximately 50 % of the total variation in LST in winter, and up to 77.9 % for summer. Vegetation related variables, particularly tree canopy, were good predictor of LST during summer and fall. Vegetation, particularly tree canopy, can significantly reduce LST. The spatial resolution of LULC data appeared not to substantially affect relationships between LST and LULC variables. In contrast, increasing thematic resolution generally enhanced the explanatory power of LULC on LST, but not to a substantial degree.     

What multiscale environmental drivers can best be discriminated from a habitat index derived from a remotely sensed vegetation time series?

Understanding which environmental conditions are critical for species survival is a critical, ongoing question in ecology. These conditions can range from climate, at the broadest scale, through to elevation and other local landscape conditions, to fine scale landscape patterns of land cover and use. Remote sensing is an ideal technology to monitor and assess changes in these environmental conditions at a variety of spatial and temporal scales, with many studies focusing on the physiological state of vegetation derived from time series of satellite measurements. As vegetation occurs within specific climatic zones, over certain soil, terrain, and land cover types, it can be difficult to decipher the influence of the underlying role of climate, topography, soil, and land cover on the observed vegetation signal. In this article, we specifically addressed this problem by asking the question: what is the relative impact and importance of these different scales of environmental drivers on the temporal and spatial patterns observed on a habitat index derived from remotely sensed data? To find the solution, we utilized a SPOT VEGETATION-normalized difference vegetation index time series of Europe to create a remote-sensing-derived habitat index, which incorporates aspects of productivity, seasonality, and cover. We then compared the observed temporal and spatial variations in the index to a pan-Europe terrestrial classification system, which explicitly incorporates variations in climate, terrain, soil parent material, land cover, and use. Results indicated that the most accurate level of discrimination from the habitat index was at the broadest level of the hierarchy, climate, while the poorest degree of discrimination was associated with elevation. In terms of similarity on the index across time and space, we found that arable and forest cover classes were more similar across elevation and parent materials than across other land cover types within them. Analyzing the remote-sensing index, at multiple scales, provides significant insights into the drivers of satellite-derived greenness indices, as well as highlights the benefit and cautions associated with linking satellite-derived indirect indicators to species distribution modeling and biodiversity.     

Modelling historical landscape changes

Landscape Ecology - Historical maps of land use/land cover (LULC) enable detection of landscape changes, and help to assess drivers and potential future trajectories. However, historical maps are...     

Siberian flying squirrel responses to high- and low-contrast forest edges

We examined responses of Siberian flying squirrels ( Pteromys volans ) to edges between nesting habitat (mature spruce forests), movement habitat (other forests, pine bogs), and open areas within their home ranges in southern Finland in 1996-2000. Radio-tracked squirrels (n=146) were generally associated to edges when they were ac tive at night. Compared to distances expected from the habitat pattern of their home range, squirrels occurred closer to high-contrast edges (of open areas) and low-contrast edges (nesting or movement forest types). Asso ciation with edges of open areas was more pronounced when squirrels were in movement habitat than in nesting habitat, possibly because of stronger channeling of movements in the former habitat. When in nesting habitat, squirrels responded more strongly to field edges than to recent clearcut edges, probably as a result of the pres ence of more deciduous trees on field edges, unlike clearcut edges. Responses to open areas were independent of spatial scale. However, responses to movement habitat from nesting habitat, and vice versa, were more pronounced over hundreds than tens of meters. Nesting cavities and dreys were generally located at random with respect to edges. We conclude that squirrel responses to edges of landscape attributes are diverse and depend both on spatial scale and edge contrast.This revised version was published online in May 2005 with corrections to the Cover Date.     

Cultural landscapes of Germany are patch-corridor-matrix mosaics for an invasive megaforb

Predicting the vulnerability of landscapes to both the initial colonisation and the subsequent spread of invasive species remains a major challenge. The aim of this study was to assess the relative importance of sub-patch level factors and landscape factors for the invasion of the megaforb Heracleum mantegazzianum. In particular, we tested which factors affect the presence in suitable habitat patches and the cover-percentage within invaded patches. For this purpose, we used standard (logistic) regression modelling techniques. The regression analyses were based on inventories of suitable habitat patches in 20 study areas (each 1 km²) in cultural landscapes of Germany. The cover percentage in invaded patches was independent from landscape factors, except for patch shape, and even unsatisfactorily explained by sub-patch level factors included in the analysis (R ² = 0.19). In contrast, presence of H. mantegazzianum was affected by both local and landscape factors. Woody habitat structure decreased the occurrence probability, whereas vicinity to transport corridors (rivers, roads), high habitat connectivity, patch size and perimeter-area ratio of habitat patches had positive effects. The significance of corridors and habitat connectivity shows that dispersal of H. mantegazzianum through the landscape matrix is limited. We conclude that cultural landscapes of Germany function as patch-corridor-matrix mosaics for the spread of H. mantegazzianum. Our results highlight the importance of landscape structure and habitat configuration for invasive spread. Furthermore, this study shows that both local and landscape factors should be incorporated into spatially explicit models to predict spatiotemporal dynamics and equilibrium stages of plant invasions.     

Effects of changing landscape pattern and U. S. G. S. land cover data variability on ecoregion discrimination across a forest-agriculture gradient

We examined the use of coarse resolution land cover data (USGS LUDA) to accurately discriminate ecoregions and landscape-scale features important to biodiversity monitoring and management. We used land cover composition and landscape indices, correlation and principal components analysis, and comparison with finer-grained Landsat TM data, to assess how well LUDA data discriminate changing patterns across an agriculture-forest gradient in Minnesota, U.S.A. We found LUDA data to be most accurate at general class levels of agriculture and forest dominance (Anderson Level I), but in consistent and limited in ecotonal areas of the gradient and within forested portions of the study region at finer classes (Anderson Level II). We expected LUDA to over-represent major (matrix) cover types and under-represent minor types, but this was not consistent with all classes. 1) Land cover types respond individualistically across the gradient, changing landscape grain as well as their spatial distribution and abundance. 2) Agriculture is not over-represented where it is the dominant land cover type, but forest is over-represented where it is dominant. 3) Individual forest types are under-represented in an open land matrix. 4) Within forested areas, mixed deciduous-coniferous forest is over-represented by several orders of magnitude and the separate conifer and hardwood types under-represented. Across gradual, transitional agriculture-forest areas, LUDA cover class dominance changes abruptly in a stair-step fashion. In general, rare cover types that are discrete, such as forest in agriculture or wetlands or water in forest, are more accurately represented than cover classes having lower contrast with the matrix. Northward across the gradient, important changes in the proportions of conifer and deciduous forest mixtures occur at scales not discriminated by LUDA data. Results suggest that finer-grained data are needed to map within-state ecoregions and discriminate important landscape characteristics. LUDA data, or similar coarse resolution data sources, should be used with caution and the biases fully understood before being applied in regional landscape management. This revised version was published online in July 2006 with corrections to the Cover Date.     

Relationships between urbanization,tree morphology,and carbon density: An integration of remote sensing,allometric models,and field survey

Urban trees store and sequester large amounts of carbon and are a vital component of natural climate solutions. Despite the well-recognized carbon benefits of urban trees, there is limited effort to examine how spatial distribution of carbon density varies across distinctive social, demographic, and built dimensions of urban landscapes. Moreover, it is unclear whether specific aspects of landscape structure and design could help increase carbon densities in urban trees. Here, we produced a fine-resolution carbon density map of urban trees in New York City (NYC) by integrating high-resolution land cover map, LiDAR-derived tree metrics, i-Tree Eco, and field survey data. We then explored spatial variations of carbon density across the gradients of urban development intensity, social deprivation index, and neighborhood age, and we examined the relationships between carbon density, and fragmentation, aggregation, size, and shape of tree canopy cover. We find that carbon stored in urban trees in NYC is estimated as 1078 Gg, with an average density of 13.8 Mg/ha. This large amount of carbon is unevenly distributed, with carbon densities being highest in Bronx and in open parks and street trees. Furthermore, carbon densities are negatively associated with urban development intensity and the social gradient of deprivation. Regarding the impacts of tree morphology on carbon density, our results show that while the amount of tree cover is the most influential factor in determining carbon density, small-sized forest patches and moderate levels of forest edges are also conductive to increasing carbon densities of urban trees. To incorporate urban forestry into developing innovative, effective, and equitable climate mitigation strategies, planners and decision makers need to identify the optimal spatial configuration of urban forests and invest in tree planting programs in marginalized communities.