Local-scale Factors Research Articles

Small mammal assemblages in heterogeneous landscapes at the Southern tip of Italian peninsula evidence clear eco-biogeographic patterns

We investigated the frequencies of sympatric small mammal species in 12 habitat-types located in the extreme south of the Italian peninsula (Calabria) using trapping techniques. Ten species were detected with Apodemus sylvaticus, the most abundant species. The assemblages of small mammal species recorded in the 12 selected habitat types revealed clear ecological and biogeographical patterns in the extreme southern tip of the Italian peninsula. Ecologically, we observed a clear dissimilarity between a guild of species linked to thermo-xerophilous habitat types and a comparable guild of mesophilous species linked to forest and sciaphilous habitat types. The differences among communities inhabiting in different habitat types also emerged in rarefaction curves, DCA analysis and Whittaker plots. Thus, all these sets of analyses were consistent in their interpretation of the variation of small mammal community structure along the gradient (β-diversity) among habitat types. From a biogeographical point of view, this is an apparent expression of a clear North–South gradient pattern that was already observed at the species level with Calabria being characterized by a strong impoverishment in species’ richness and diversity (“peninsula effect”). However, this rationale has been based so far on indirect data of small mammals preyed upon and recorded in owl’s pellets: the fact that a similar pattern was obtained also using small mammals recorded by traps indicates that the results were robust and generalizable. Ecological factors at the local scale and biogeographical factors at the peninsular scale could explain the community patterns that we observed in the present study.

A comprehensive multi-fidelity surrogate framework based on Gaussian process for datasets with heterogeneous responses

In recent decades, the multi-fidelity (MF) surrogate framework has seen widespread application across various scenarios. This framework significantly enhances the efficiency of surrogate modeling by integrating data of varying fidelity levels. However, research on the MF surrogate has predominantly focused on regression settings, aiming at approximating continuous responses, with limited attention to classification problems involving discrete responses. Moreover, no existing studies have addressed a heterogeneous MF dataset, where the data types (continuous or discrete) vary between different fidelities. This paper introduces a comprehensive MF surrogate framework based on Gaussian process, designed to handle a wide range of MF dataset types. Our framework employs a hierarchical Kriging scheme and Bayesian inference, adaptable to any MF dataset type. Given the challenges posed by discrete data in analytical inference, we incorporate the Laplace approximation for the latent function associated with discrete data in our framework. Additionally, we introduce a local scaling factor specifically for low-correlation classification problems in MF settings. The superiority of our method over conventional ones is demonstrated through both synthetic and engineering examples. Notably, in an engineering example featuring a heterogeneous MF dataset, our proposed MF surrogate model achieves an error reduction exceeding 50%.

Chasing the heat: Unraveling urban hyperlocal air temperature mapping with mobile sensing and machine learning

Many cities face unprecedented high temperatures with increasing extreme events. Heatwaves pose significant health risks, including cardiovascular diseases, heatstroke, and dehydration. Mapping urban near-surface air temperature (Tair) is crucial for understanding thermal exposure and addressing climate change. Previous studies relied on satellite-derived land surface temperature (LST) and stationary monitoring, but high spaio-temporal Tair mapping is still a challenge. This study optimized a mobile sensing scheme using an electric bicycle platform with environmental and image sensors, and deep learning captured local-scale urban factors. A spatio-temporal data fusion model that consisted of three parts, temporal trend extraction, locality analysis, and neighborhood effect analysis, generated hyperlocal Tair maps. The Results from Beijing demonstrated the effectiveness of the framework, achieving the lowest MAE of 0.02 °C. Optimized data collection and the new model achieved accurate temperature predictions and thermal exposure assessment. Efficiency enhanced sensing strategy was also proposed. The study highlights local-scale factors and spatio-temporal dependencies in addressing heatwaves and climate change impacts in urban areas.

Local and regional variation in kelp loss and stability across coastal British Columbia

Kelp forests are among the most abundant coastal marine habitats but are vulnerable to climate change. The Northeast Pacific has experienced recent large-scale changes in kelp abundance and distribution, but little is known about changes north of the British Columbia (BC)-Washington border. Here, we assessed whether and how floating canopy kelp (Macrocystis pyrifera, Nereocystis luetkeana) distributions have changed in recent decades along the extensive coast of BC. We assembled and analysed available kelp distributional data, comparing snapshots of kelp linear extent from 1.5-3 decades ago (1994-2007) to recently collected data (2017-2021) across 11 different subregions spanning the province. We then leveraged timeseries, where available (n = 7 data sets), to contextualise patterns of change. In aggregate, the data suggest that kelp forests have declined considerably in some parts of the province, but with variable patterns of change across BC. In the warmest areas (southern BC), kelp persistence was negatively correlated with mean summer sea surface temperatures, which at times exceeded known thermal tolerances. In contrast, in northern subregions, top-down control by sea urchins and otters appeared to modulate kelp dynamics, with declines occurring in 2 subregions despite cool ocean temperatures. Timeseries data suggest that many declines occurred around the 2014-2016 marine heatwave, an event associated with sustained warming and altered trophic dynamics. Our results suggest that the extent of BC’s kelp forests has declined in some places in recent decades, but that regional and local-scale factors influence their responses to environmental change.

King Rail (Rallus elegans) presence in the Midwestern United States is predicted by local-scale factors and avian community.

The King Rail (Rallus elegans) is a wetland dependent species of conservation concern. Our objective was to gain a better understanding of the breeding habitat associations of King Rails in the Midwestern United States and the relationship of this species to other obligate marsh birds using occupancy and MaxEnt models. To collect data pertaining to occupancy, we placed trail cameras at 50 random points in coastal wetlands in the western Lake Erie basin where calls of King Rails were continuously broadcast at night. Data pertaining to other marsh bird species were collected via call-broadcast surveys and camera surveys at each sample point. For MaxEnt modeling, we obtained presence data for King Rails and other obligate marsh birds from eBird and habitat data from GIS databases. Trail cameras and call-broadcast surveys captured 10 detections of King Rails at nine sites, an 18% naive occupancy rate. King Rail occupancy was positively related to amount of interspersion, average water depth, and percent cover of emergent vegetation at local scales within a 5-m radius. Our MaxEnt models indicated that, at a broader scale, the presence of other rail species such as the Sora (Porzana carolina) may be more important for predicting King Rail presence than other marsh birds or coarse wetland categories such as "emergent vegetation." Our results could help wetland managers to predict where King Rails occur and to adapt management plans to incorporate King Rail conservation.

Programmable multi-layered auxetic mechanisms

The present work investigates programmable auxetic surfaces and how they can be enabled to achieve a general surface shape upon external control. To actively generate target geometries from an initial geometry, a process of non-uniform expansion or contraction as well as an alteration of local curvatures are necessary. This implies the alignment of a multiplicity of control factors. The present work suggests that auxetic mechanisms hold a high potential to achieve and simplify such alignments. As a key principle for achieving defined target forms and the required shape transitions, the study identifies the modification of the local scaling factor and the Gaussian curvature of plane surfaces. Within this work, such active surfaces are created utilizing multi-layered auxetic tessellations. To control the scaling factor and the curvature of the resulting structure, we propose different multi-layered auxetic structures comprising rotational actuators. These concepts are demonstrated for the example of kagome tessellations but can easily be transferred to other auxetic tessellations.

A Climate Change Study: Downscaling of Climatic Parameters and Their Assessment Over East Rathong Glacier of Eastern Himalayan Region

In this study monthly Temperature Lapse Rates and basic downscaling technique of subtracting means are used to construct temperature (T) series over East Rathong glacier by using multiple data sets from Automatic Weather Stations (AWS) at Himalayan Mountaineering Institute (HMI), Gangtok Indian Meteorological Department (IMD), Yuksum and ERA5reanalysis data. Precipitation (P) over glacier is estimated using Gangtok IMD data and downscaled ERA5 data. The P data is downscaled using local scaling factor method. Change in volume of 0.180 km3 (from 1962 to 2020) estimated using satellite data are used to construct Mass Balance (MB) series for the glacier. It is observed that the glacier is losing its mass with increasing T, Aerosol Optical Depth (AOD) (from 0.1 in 1980 to 0.2 in 2020), and increasing Pmainly during June-July-August months when temperatures are already high. This study is important as it used multiple data sets along with field data extracted from the literature to study climatic impacts on East Rathong glacier. Data generated from this study may be used in mass balance projection of the glaciers in the absence of field data.

Interactions between large-scale and local factors influence seed predation rates and seed loss.

Herbivores often have highly variable impacts on plant fecundity. The relative contribution of different environmental factors operating at varying spatial scales in affecting this variability is often unclear. We examined how density-dependent seed predation at local scales and regional differences in primary productivity are associated with variation in the magnitude of pre-dispersal seed predation on Monarda fistulosa (Lamiaceae). Within M. fistulosa populations growing in a low-productivity region (LPR), Montana, USA, and a high-productivity region (HPR), Wisconsin, USA, we quantified the magnitude of pre-dispersal seed predation among individual plants differing in seed head densities. Out of a total of 303 M. fistulosa plants that were surveyed, we found half as many herbivores in seed heads in the LPR (n = 133 herbivores) compared to the HPR (n = 316). In the LPR, 30% of the seed heads were damaged in plants with low seed head density, while 61% of seed heads were damaged in plants with high seed head density. Seed head damage was consistently high in the HPR (about 49% across the range of seed head density) compared to the LPR (45% across a range of seed head density). However, the proportion of seeds per seed head that were destroyed by herbivores was nearly two times higher (~38% loss) in the LPR compared to HPR (22% loss). Considering the combined effects of probability of damage and seed loss per seed head, the proportion seed loss per plant was consistently higher in the HPR regardless of seed head density. Nevertheless, because of greater seed head production, the total number of viable seeds produced per plant was higher in HPR and high-density plants, despite being exposed to greater herbivore pressure. These findings show how large-scale factors can interact with local-scale factors to influence how strongly herbivores suppress plant fecundity.

Climatology of the global summer monsoon rainy seasons: Revisited from a high-resolution satellite climate data record

Reliable information on the monsoon rainfall at finer spatiotemporal scales has always been crucial for applications in hydrometeorology, water resource management, disaster prevention, and assessment of numerical model outputs. Here, the spatial-temporal characteristics of the summer monsoon rainy seasons worldwide are revisited using a global, high-resolution, bias-corrected satellite rainfall climate data record. The Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks–Climate Data Record (PERSIANN-CDR) provides 0.25° rainfall estimates for the latitude band 60°S–60°N from 1983 to the near present. The global monsoon regimes are defined based on the annual rainfall range and the summer rainfall ratio. The onset, peak, and withdrawal of the rainy season are then determined using a concise yet pertinent rainfall parameter with universal objective criteria.Overall, six major summer monsoon regimes of the globe, the Asian Monsoon, Indonesian–Australian monsoon, North African monsoon, South African monsoon, North American and South American monsoon, are all reasonably represented by PERSIANN-CDR. The progression patterns of climatological onset, peak, and withdrawal phases of these monsoons are consistent with those reported by previous global and regional monsoon studies. Furthermore, compared with other coarser resolution satellite rainfall estimates such as the Climate Prediction Center Merged Analysis of Precipitation (CMAP), the present result is clearly in better agreement with that obtained from ground-based observations since it allows the determination of more detailed information associated with local-scale factors such as the sharp land-sea contrast, local surface heating, and topography effects. However, some “spots”, particularly over complex topography lacking ground truth validations, are revealed to have rainy season characteristics that differ substantially from those over the surrounding areas and have not been fully described by published literature. These distinct features need to be confirmed by further regional monsoon studies.

Local-scale factors and dynamics in climate adaptability among subsistence farmers

Climate change is the primary environmental threat to subsistence farmers’ productivity in Peru. Adaptation is promoted as the best mechanism to cope with climate change in subsistence agricultural livelihoods. However, climatic adaptability depends on the resources the farmer has access to or can use, which are not always adequate to respond effectively to the speed and aggressiveness of climate change. This study explored the local factors and dynamics (assets) influencing the climate adaptability processes of subsistence farmers in Huayhuay, Peru. Twenty subsistence farmers participated in semi-structured interviews within a basic qualitative design. The results brought to light 18 local factors and dynamics that influence the coping mechanisms of climate adaptability. These findings support other investigations that demonstrate the difficulty of climate change adaptation agricultural communities face. The difficulty of climate change adaptation has rooted the interrelationships of assets of different natures within the same adaptive process. Future research and interventions should encourage the active participation of farmers in local climate action and evaluate the efficiency and effectiveness of farmers' adaptability mechanisms, considering the role of each local-scale factor and dynamic.

Mixed models elucidate local- and regional-scale drivers of paleoenvironmental change in eastern Africa during the emergence of Paranthropus and Homo

Climate and environmental change are considered important drivers of hominin speciation and diversification, including the emergence of Paranthropus and Homo. Therefore, making connections between potential drivers of hominin evolution on multiple spatial scales is a critical issue in hominin paleoecology. This is especially true in light of evidence that paleoenvironmental proxies operating at different spatial scales lead to divergent interpretations about whether environmental change in eastern Africa was primarily driven by regional-scale or local-scale factors. This study takes a novel approach to addressing issues of scale in hominin paleoecology by using linear mixed models to test the relative impact of local factors versus regional factors in driving variation in aridity and vegetation at important hominin paleontological sites across eastern Africa between 3.7 Ma and 2.3 Ma. Results indicate there are no significant trends in aridity as evidenced by stable oxygen isotopes of paleosol carbonates. However, the results for stable carbon isotopes of paleosol carbonates suggest regional-scale factors drove a uniform increase in grassy vegetation at nearly all sites. Additionally, we find that while regional-scale factors drive vegetation change, local-scale factors were important in determining the unique mix of trees/shrubs and grass that was present at each site and upon which vegetation change acted. Thus, while sites across eastern Africa experienced the same degree of vegetation change, at any given time the vegetation at each site would have differed from other sites. This result offers a possible resolution between regional-scale proxies which show an overall increase in C4 photosynthesizing grasses and local-scale proxies which indicate that paleoenvironments at different sites were varied. It also connects regional-scale drivers to local-scale environmental change which would have had an important impact on hominin evolution and adaptation. This study introduces linear mixed models as a methodology which to date has not been widely applied to questions of hominin paleoecology and has the potential to address critical issues of scale.

Assessment of wind resource considering local turbulence based on data acquisition with SODAR

This work presents a new methodology to evaluate the influence of wind speed data corrections in the fit of the Weibull distribution. Corrections are made for data measured by Sonic Detection and Ranging (SODAR) and MERRA-2 base data. SODAR data are corrected through Turbulence Intensity (TI). The MERRA-2 data correction uses National Institute of Meteorology (INMET) weather station data to find a local scale factor. The results showed that the corrected data present a better fit in the Weibull distribution and evidence that corrections are necessary when wind speed averages are used to evaluate the wind resource. Wind speed data were also applied to simulate the energy production by a commercial turbine to demonstrate the contrast in the total energy generated. The new methodology shows that IT must be considered in the evaluation of wind resources.

Forested wetlands in a protected area and the adjacent working landscape provide complementary biodiversity value based on breeding birds: A case study from Nova Scotia, Canada

Protected areas (PAs) are a key component of most conservation strategies because they are thought to enhance biodiversity value relative to similar habitats in working landscapes. To examine whether PAs in Nova Scotia are functioning to enhance the biodiversity value of the landscapes in which they are embedded, we surveyed breeding bird communities in forested wetlands inside and outside of a large PA during 2018 and 2019. We found significantly higher species richness and diversity at sites in the working landscape relative to those inside the PA. Bird communities from different wetland types inside the PA were distinct from each other and those outside the PA, whereas bird communities at outside sites were homogenized and comprised of more early-successional species. There were numerous species of conservation concern at both inside and outside sites, indicating that both types of sites are playing important conservation roles. Abundances of these key species were driven by a combination of local (e.g., water table depth, herb, and shrub cover) and landscape scale factors (e.g., edge density and human disturbance). The higher abundance of long-distance migrants and insectivores at inside sites suggests PAs are providing critical additional support to key guilds that are in steep decline.

A multiscale landscape approach for prioritizing river and stream protection and restoration actions.

River and stream conservation programs have historically focused on a single spatial scale, for example, a watershed or stream site. Recently, the use of landscape information (e.g., land use and land cover) at multiple spatial scales and over large spatial extents has highlighted the importance of incorporating a landscape perspective into stream protection and restoration activities. Previously, we developed a novel framework that links information about watershed-, catchment-, and reach-scale integrity with stream biological condition using scatterplots and a landscape integrity map. Here we examined an application of this approach for streams in urban and other settings in King County, Washington State, United States, where we related stream macroinvertebrate condition to two indices of landscape integrity, the US Environmental Protection Agency's (USEPA) nationally available Index of Watershed Integrity (IWI) and Index of Catchment Integrity (ICI). We generated a scatterplot of IWI versus ICI for sample sites, where points represented site macroinvertebrate condition from poor to good. The same data were also visualized as a landscape integrity map that displayed catchments of King County according to the level of watershed and catchment integrity (high or low IWI/ICI). Almost three-quarters of poor-condition sites were associated with high-integrity watersheds and catchments (i.e., underperforming sites), which suggested that either one or both national indicators were insufficient for this area, and that sites underperformed because of local-scale factors. In response, we used a catchment-scale indicator related to forest condition (PctForestCat) after examining several GIS-based dispersal indicators from the National Hydrography Dataset and other candidates from the USEPA's StreamCat dataset. We then compared the results of the scatterplots and maps based on the current and original analyses and found that many of the sites previously classified as underperforming now performed as expected, that is, they were poor-condition sites in poor-condition catchments. This analysis demonstrates how results based on a national dataset can be improved by developing an alternative that represents regionally important stressors. The methods used to develop an effective landscape indicator based on StreamCat datasets, and the utility of the multiscale approach, could provide important tools for prioritizing, optimizing, and communicating stream conservation actions.

Local-scale habitat configuration makes a niche for wildlife encroaching into an urban landscape: grubbing sites of wild boar Sus scrofa in a city matrix

Urban environments may offer certain species diverse and abundant food resources of natural and anthropogenic origin. However, the local-scale configuration of habitats and urban infrastructure may influence foraging decisions regardless of the availability of food. In recent years, the expansion of wild boar Sus scrofa into areas significantly transformed by humans has been observed in many parts of its range. Grubbing (rooting) is a major foraging mode of the species, during which disturbance of the upper soil layers enables these animals to find and consume food items. However, the factors that determine the selection of grubbing sites in the urban landscape, where the balance between food availability and the avoidance of humans may influence foraging decisions, are not known. Our aim was to identify local-scale factors that influence grubbing site selection and the size of grubbed patches in an urban landscape. The characteristics of 108 wild boar grubbing sites in the city of Kraków (Poland) were compared to randomly selected control sites. The probable presence of a grubbing site was positively correlated with the proportion of meadows and fallow land in the vicinity and with increases in both canopy cover and distance to pavements. The size of a grubbed patch was positively correlated with the percentage of meadows in the vicinity, increasing distance to buildings and decreasing distance to pavements. We found a non-random pattern of grubbing sites in the urban landscape and indicated that the local-scale configuration of vegetation and urban infrastructure contribute to foraging site selection by wild boar. Our study highlights that the encroachment of wildlife into the urban landscape is a complex process, driven by both resource availability and the avoidance of human-related disturbances.

The Upper Range Limit of Alien Plants Is Not in Equilibrium with Climate in the Andes of Central Chile

Alien plant species are colonizing high-elevation areas along roadsides. In this study, we evaluated whether the distributions of alien plants in the central Chilean mountains have reached climatic equilibrium (i.e., upper distribution limits consistent with their climatic requirements). First, we evaluated whether the upper elevational limits of alien plants changed between 2008 and 2018 based on the Mountain Invasion Research Network (MIREN) database. Second, we compared the observed upper elevational limits with the upper limits predicted by each species’ global climatic niche. On average across species, the upper elevation limit did not change between 2008 and 2018. However, most species maintained the same limit or shifted downward, while only 23% of the species shifted upwards. This lack of change does not mean that the species’ distributions are in equilibrium with the climate, because the observed upper limit was lower than the limit predicted by the global niche model for 87% of species. Our results suggest that alien species in this study region may not only be climate-limited, but could also be limited by other local-scale factors, such as seed dispersal, intermittent disturbance rates, soil type and biotic interactions.

Unravelling Trait-Environment Relationships at Local and Regional Scales in Temperate Forests.

Understanding the trait–environment relationships has been a core ecological research topic in the face of global climate change. However, the strength of trait–environment relationships at the local and regional scales in temperate forests remains poorly known. In this study, we investigated the local and regional scale forest plots of the natural broad-leaved temperate forest in northeastern China, to assess what extent community-level trait composition depends on environmental drivers across spatial scales. We measured five key functional traits (leaf area, specific leaf area, leaf carbon content, leaf nitrogen content, and wood density) of woody plant, and quantified functional compositions of communities by calculating the “specific” community-weighted mean (CWM) traits. The sum of squares decomposition method was used to quantify the relative contribution of intraspecific trait variation to total trait variation among communities. Multiple linear regression model was then used to explore the community-level trait–environment relationships. We found that (i) intraspecific trait variation contributed considerably to total trait variation and decreased with the spatial scale from local to regional; (ii) functional composition was mainly affected by soil and topography factors at the local scale and climate factor at the regional scale, while explaining that variance of environment factors were decreased with increasing spatial scale; and (iii) the main environment driver of functional composition was varied depending on the traits and spatial scale. This work is one of the few multi-scale analyses to investigate the environmental drivers of community functional compositions. The extent of intraspecific trait variation and the strength of trait–environment relationship showed consistent trends with increasing spatial scale. Our findings demonstrate the influence of environmental filtering on both local- and regional-scale temperate forest communities, and contribute to a comprehensive understanding of trait–environment relationships across spatial scales.

Multiple Factors at Regional, Landscape, and Local Scales Determine Spider Assemblage Composition in Pomegranate Orchards

Orchards may support high spider diversity relative to annual crops due to their structural complexity and relative stability. Multiple environmental conditions at the landscape, regional, and local scales may influence the assemblage composition of spiders in orchards. We asked which environmental variables best explains spider assemblage composition and the similarity of the assemblages of pomegranate orchards located along a latitudinal gradient in Israel? Spiders were sampled from twelve pomegranate orchards along a climatic gradient from north to south. Orchards located at higher latitudes had richer assemblages than orchards located at lower latitudes. The assemblage composition was influenced at the large scale by latitude and annual crop cover in the surrounding landscape but not by local factors. By contrast, functional groups based on foraging strategies were affected by local scale factors, such as vegetation within the orchards. This study demonstrates the importance of considering environmental variables at different scales to understand the factors affecting the assemblage composition of naturally occurring predators in the orchard.

Local-scale factors matter for tree cover modelling in Mediterranean drylands

Forests contribute directly to ecosystem structure and functioning, maintaining biodiversity, acting as a climate regulator and reducing desertification. To better manage forests, it is essential to have high-resolution forest models and appropriate spatial-explicit variables able to explain tree cover at different scales, including the management scale. Most tree cover models rely only on broad-scale variables (>500 m), such as macroclimate, while only few studies include also local-scale variables (<500 m). This study aimed to identify the importance of local-scale factors relative to broad-scale factors and identify the environmental variables at different scales that explain tree cover in oak woodlands in Mediterranean drylands. Sixty sites previously identified as being covered with Holm oak or Cork oak were stratified by precipitation. Normalized Difference Vegetation Index, used here as a surrogate of tree cover, was modelled using simultaneously broad-scale factors (macroclimate) and local-scale factors (microclimatic and edaphic conditions). The percentage of variance explained by local- and broad-scale factors and the effect size of each environmental variable on tree cover was determined for the study site. It was found that local-scale factors and their interaction with broad-scale factors explained more variance than broad-scale factors alone. The most important local-scale factors explaining tree cover were elevation, potential solar radiation, used as a surrogate of microclimatic conditions, and wetness evaluated terrain used as an indicator of water flow accumulation. The main broad-scale factors were related to temperature and precipitation. The effect of some local-scale variables in tree cover seems to increase in areas where water as a limiting factor is more important. This study demonstrates the critical importance of including local-scale factors in multi-scale modelling of tree cover to obtain better predictions. These models will support well-suited forest management decisions, such as reforestation and afforestation plans to reverse evergreen oaks decline in Mediterranean drylands.

Effects of urbanization on Odonata assemblages in tropical island streams in San Juan, Puerto Rico

Urbanization has considerable impacts on stream ecosystems. Streams in urban settings are affected by multiple stressors such as flow modifications and loss of riparian vegetation. The richness and abundance of aquatic insects, such as odonates, directly reflect these alterations and can be used to assess urban impacts on streams. The effects of urbanization on odonate richness and abundance on tropical islands is as yet poorly understood. The objective of this study is to identify the effects of urbanization on stream habitat quality and associated odonate assemblages in Puerto Rico. We sampled 16 streams along a rural to urban gradient in the San Juan Metropolitan Area, where each stream was characterized using the Stream Visual Assessment Protocol (SVAP) for Puerto Rico and by analyzing their surrounding land cover. A 100-m segment of each stream was surveyed to assess adult odonate richness and abundance during the rainy and dry seasons. Adults were identified visually, and their abundance was recorded. Favorable local scale factors, like improved habitat quality, as measured with the SVAP, resulted in higher abundances of odonates. However, regional factors such as percent urban cover did not appear to significantly affect richness and abundances of odonates. Overall, our study indicates that odonate assemblages are affected by the loss of habitat integrity, and conservation of tropical odonates may benefit from focusing on local scale factors.