Land Cover Composition Research Articles

Assessing the extent of land-use change around important bat-inhabited caves

BackgroundModification and destruction of natural habitats are bringing previously unencountered animal populations into contact with humans, with bats considered important zoonotic transmission vectors. Caves and cave-dwelling bats are under-represented in conservation plans. In South Africa, at least two cavernicolous species are of interest as potential zoonotic hosts: the Natal long-fingered bat Miniopterus natalensis and the Egyptian fruit bat Rousettus aegyptiacus. Little information is available about the anthropogenic pressures these species face around important roost sites. Both bats are numerous and widespread throughout the country; land-use changes and urban expansions are a rising concern for both conservation and increased bat-human contact.ResultsOur study addressed this shortfall by determining the extent of land-cover change around 47 roosts between 2014 and 2018 using existing land cover datasets. We determined the land-cover composition around important roost sites (including maternity, hibernacula and co-roosts), distances to urban settlements and assessed the current protection levels of roost localities. We detected an overall 4% decrease in natural woody vegetation (trees) within 5 km buffer zones of all roost sites, with a 10% decrease detected at co-roost sites alone. Agricultural land cover increased the most near roost sites, followed by plantations and urban land-cover. Overall, roosts were located 4.15 ± 0.91 km from urban settlements in 2018, the distances decreasing as urban areas expand. According to the South African National Biodiversity Institute Ecosystem Threat Status assessment, 72% of roosts fall outside of well-protected ecosystems.ConclusionsThe current lack of regulatory protection of cavernicolous bats and their roosts, increasing anthropogenic expansions and proximity to human settlements raises concerns about increased human-bat contact. Furthermore, uncontrolled roost visitation and vandalism are increasing, contributing to bat health risks and population declines, though the extent of roosts affected is yet to be quantified. In an era where pandemics are predicted to become more frequent and severe due to land-use change, our research is an urgent call for the formal protection of bat-inhabited caves to safeguard both bats and humans.

Impact of land cover on air pollution at different spatial scales in the vicinity of metropolitan areas

China’s urbanization process is accompanied by land use and cover change (LUCC), influencing variations of air pollutants at multiple spatial scales. Monitoring the spatiotemporal variations of air pollutants and their relationship with land cover (LC) is vital for understanding the mechanisms of land-air interaction and guiding environmental management. In this study, both statistical and geo-statistical analysis is used to investigate the relationship between spatiotemporal variations of air pollutants and LC composition in the vicinity of China’s three major urban agglomerations (UAs), including Jing-Jin-Ji (JJJ), Yangtze River Delta Region (YRD), and Guangdong-Hong Kong-Macau Greater Bay Area (GBA). Results show that the spatial variations of six criteria air pollutants intra-region are large, even greater than inter-region and inter-season differences. Partial correlation analysis shows that although the impervious surface is the main driving force in elevating air pollution on a local scale, cropland is more important in elevating air pollutant levels at a regional scale. Besides that, the relationship between air pollutant levels and LC demonstrates varied seasonal and regional characteristics for different air pollutants. Our analysis provides a comprehensive understanding of the relationship between air pollutant levels and LC composition, emphasizing the impact of LC at different spatial scales.

Disentangling associations between vegetation greenness and dengue in a Latin American city: Findings and challenges

Being a Re-Emerging Infectious Disease, dengue causes 390 million cases globally and is prevalent in many urban areas in South America. Understanding the fine-scale relationships between dengue incidence and environmental and socioeconomic factors can guide improved disease prevention strategies. This ecological study examines the association between dengue incidence and satellite-based vegetation greenness in 3826 census tracts nested in 474 neighborhoods in Belo Horizonte, Brazil, during the 2010 dengue epidemic. To reduce potential bias in the estimated dengue-greenness association, we adjusted for socioeconomic vulnerability, population density, building height and density, land cover composition, elevation, weather patterns, and neighborhood random effects. We found that vegetation greenness was negatively associated with dengue incidence in a univariate model, and this association attenuated after controlling for additional covariates. The dengue-greenness association was modified by socioeconomic vulnerability: while a positive association was observed in the least vulnerable census tracts, the association was negative in the most vulnerable areas. Using greenness as a proxy for vegetation quality, our results show the potential of vegetation management in reducing dengue incidence, particularly in socioeconomically vulnerable areas. We also discuss the role of water infrastructure, sanitation services, and tree cover in lowering dengue risk.

Brazilian Semi-Arid Mangroves-Associated Microbiome as Pools of Richness and Complexity in a Changing World.

Mangrove microbiomes play an essential role in the fate of mangroves in our changing planet, but the factors regulating the biogeographical distribution of mangrove microbial communities remain essentially vague. This paper contributes to our understanding of mangrove microbiomes distributed along three biogeographical provinces and ecoregions, covering the exuberant mangroves of Amazonia ecoregion (North Brazil Shelf) as well as mangroves located in the southern limit of distribution (Southeastern ecoregion, Warm Temperate Southwestern Atlantic) and mangroves localized on the drier semi-arid coast (Northeastern ecoregion, Tropical Southwestern Atlantic), two important ecotones where poleward and landward shifts, respectively, are expected to occur related to climate change. This study compared the microbiomes associated with the conspicuous red mangrove (Rhizophora mangle) root soils encompassing soil properties, latitudinal factors, and amplicon sequence variants of 105 samples. We demonstrated that, although the northern and southern sites are over 4,000 km apart, and despite R. mangle genetic divergences between north and south populations, their microbiomes resemble each other more than the northern and northeastern neighbors. In addition, the northeastern semi-arid microbiomes were more diverse and displayed a higher level of complexity than the northern and southern ones. This finding may reflect the endurance of the northeast microbial communities tailored to deal with the stressful conditions of semi-aridity and may play a role in the resistance and growing landward expansion observed in such mangroves. Minimum temperature, precipitation, organic carbon, and potential evapotranspiration were the main microbiota variation drivers and should be considered in mangrove conservation and recovery strategies in the Anthropocene. In the face of changes in climate, land cover, biodiversity, and chemical composition, the richness and complexity harbored by semi-arid mangrove microbiomes may hold the key to mangrove adaptability in our changing planet.

Forests buffer against variations in precipitation.

Atmospheric moisture recycling effectively increases the amount of usable water over land as the water can undergo multiple precipitation–evapotranspiration cycles. Differences in land cover and climate regulate the evapotranspiration flux. Forests can have deep roots that access groundwater facilitating transpiration throughout the dry season independent of precipitation. This stable transpiration buffers the forest against precipitation variability. However, it is not known whether the buffering effect, already modeled for tropical forests, is common to all forests globally. Here we apply a state‐of‐the‐art Lagrangian moisture tracking model (UTrack) to study whether forest land cover in the upwind precipitationshed can lead to a reduction in monthly precipitation variability downwind. We found a significant buffering effect of forests in the precipitation variability of 10 out of 14 biomes globally. On average, if 50% of precipitation originates from forest, then we find a reduction in the coefficient of variation of monthly precipitation of 60%. We also observed that a high fraction of precipitation from non‐forest land sources tends to have the opposite effect, that is, no buffering effect. The average variation of monthly precipitation was 69% higher in areas where 50% of precipitation originates from non‐forest land sources in the precipitationshed. Our results emphasize the importance of land cover composition in the precipitationshed to buffer precipitation variability downwind, in particular forest cover. Understanding the influence of land cover in a precipitationshed on atmospheric moisture transport is key for evaluating an area's water‐climate regulatory ecosystem services and may become increasingly important due to continued changes in land cover and climate change.

Impact of Land Cover Composition and Structure on Air Temperature Based on the Local Climate Zone Scheme in Hangzhou, China

At present, conflicts between urban development and the climate environment are becoming increasingly apparent under rapid urbanization in China. Revealing the dynamic mechanism and controlling factors of the urban outdoor thermal environment is the necessary theoretical preparation for regulating and improving the urban climate environment. Taking Hangzhou as an example and based on the local climate zones classification system, we investigated the effects of land cover composition and structure on temperature variability at the local scale. The measurement campaign was conducted within four local climate zones (LCZ 2, 4, 5, and LCZ 9) during 7 days in the summer of 2018. The results showed that the temperature difference within the respective LCZ was always below 1.1 °C and the mean temperature difference between LCZs caused by different surface physical properties was as high as 1.6 °C at night. Among four LCZs, LCZ 2 was always the hottest, and LCZ 9 was the coolest at night. In particular, the percentage of pervious surface was the most important land cover feature in explaining the air temperature difference. For both daytime and nighttime, increasing the percentage of pervious surface as well as decreasing the percentage of impervious surface and the percentage of building surface could lower the local temperature, with the strongest influence radius range from 120 m to 150 m. Besides, the temperature increased with the SVF increased at day and opposite at night.

Using landscape metrics to characterize towns along an urban-rural gradient

ContextUrban-rural gradients are useful tools when examining the influence of human disturbances on ecological, social and coupled systems, yet the most commonly used gradient definitions are based on single broad measures such as housing density or percent forest cover that fail to capture landscape patterns important for conservation.ObjectivesWe present an approach to defining urban–rural gradients that integrates multiple landscape pattern metrics related to ecosystem processes important for natural resources and wildlife sustainability.MethodsWe develop a set of land cover composition and configuration metrics and then use them as inputs to a cluster analysis process that, in addition to grouping towns with similar attributes, identifies exemplar towns for each group. We compare the outcome of the cluster-based urban-rural gradient typology to outcomes for four commonly-used rule-based typologies and discuss implications for resource management and conservation.ResultsThe resulting cluster-based typology defines five town types (urban, suburban, exurban, rural, and agricultural) and notably identifies a bifurcation along the gradient distinguishing among rural forested and agricultural towns. Landscape patterns (e.g., core and islet forests) influence where individual towns fall along the gradient. Designations of town type differ substantially among the five different typologies, particularly along the middle of the gradient.ConclusionsUnderstanding where a town occurs along the urban-rural gradient could aid local decision-makers in prioritizing and balancing between development and conservation scenarios. Variations in outcomes among the different urban-rural gradient typologies raise concerns that broad-measure classifications do not adequately account for important landscape patterns. We suggest future urban-rural gradient studies utilize more robust classification approaches.

Broad-Winged Hawks Overwintering in the Neotropics: Landscape Composition and Threats in Wintering Areas of a Long-Distance Migrant

The Broad-winged Hawk (Buteo platypterus) is an obligate long-distance migrant that breeds in deciduous and mixed forests of North America and migrates to Neotropical regions to overwinter. Despite advances in understanding the breeding ecology and migration of this species, the overwintering period and associated threats remain understudied. We used telemetry data to quantify land cover composition and threats during the overwintering period of seven females affixed with Argos solar-powered transmitters between 2014 and 2018. Broad-winged Hawks in our study nested in Pennsylvania, USA, and overwintered in Colombia, Brazil, and Peru. Overwintering areas varied in size (x̄ = 243.6 ± 101.2 km2) and were composed of evergreen sub-montane forests, lowland non-flooded forests, and lowland flooded evergreen forest. In general, the loss of forest cover in all areas used by Broad-winged Hawks in our study did not exceed 10% of the total overwintering area used, suggesting Broad-winged Hawks may select wintering areas with little forest disturbance. Illegal mining was a common disturbance in areas used by Broad-winged Hawks overwintering in southern Peru, and forest fires were the prevalent disturbance in the overwintering area of Mato Grosso in western Brazil. These results provide the first analysis of land cover composition and threats of Broad-winged Hawks during the overwintering period. Although more data are needed to determine specific habitat selection for this species, our study suggests large forested areas in the Neotropics are key to ensure the conservation of the Broad-winged Hawk during the overwintering period, an understudied stage of its annual cycle.

The dietary, productivity, and economic value of swiftlet (Aerodramus fuciphagus) farming in East Kalimantan, Indonesia

Abstract. Mursidah, Lahjie AM, Masjaya, Rayadin Y, Ruslim Y, Judinnur MB, Andy. 2021. The dietary, productivity, and economic value of swiftlet (Aerodramus fuciphagus) farming in East Kalimantan, Indonesia. Biodiversitas 22: 2528-2537. Edible-nest swiftlets have many health benefits. The availability of edible-nest swiftlets from caves is decreasing, while the demand for edible-nest swiftlets is getting higher. Swiftlet farming is carried out to meet this demand. The location of swiftlet farming should be close to the feeding sources. Swiftlet is flying insectivorous animals. A financial feasibility assessment is carried out to determine the feasibility of the business. This study aims to determine the composition of land cover, determine the insect order of feed sources, and analyze the production and financial feasibility of swiftlet farming. The study was carried out from June to December 2019. The composition of land cover was determined using the supervised classification method, the order of insects was known using the insect determination key, while production and financial feasibility were analyzed using the Net B/C, NPV, IRR, and PP methods. The observed location and swiftlet farming were determined purposefully. The results of this study show that the land cover was dominated by shrubs (56.58%) and secondary forest (27.3%); both types of land cover are suitable for swiftlet farming locations. The dominant insects found in shrubs and wetland shrubs are Diptera (78.25%), in rice fields are Diptera (86.7%) and in oil palm plantations are Diptera (29.4%) and Hymenoptera (27.78%). Edible-nest swiftlets harvest begins in the third year, with a production period of between 17-34 years. From the financial feasibility, it can be concluded that swiftlet farming is feasible.

Does soil bioengineering benefits aquatic biodiversity? An empirical study of the relative influence of local and regional drivers on benthic macroinvertebrate assemblages

Riverine ecosystems form a dendritic network in which landscape and catchment-scale properties influence freshwater community structure. Placed in a restoration framework, this suggests that regional drivers can overrule the benefit of measures aiming at improving local habitat quality. Disentangling the relative influence of local and regional drivers on freshwater communities is thus crucial for ecosystem management and restoration. Along riverbanks, soil bioengineering is often used to both control erosion and improve ecological conditions. Soil bioengineering techniques aim at copying naturally functioning riverbank models and can thus be viewed as riparian ecosystem restoration. Nevertheless, these techniques are mostly designed at the local scale and are implemented in a broad range of rivers. This implies large variations in regional drivers, which may greatly influence the response of freshwater communities to restoration efforts. We studied 37 riverbanks, from civil engineering to soil bioengineering, plus natural willow stands, in the foothills of the Alps and Jura Mountains, and assessed the relative influence of local (terrestrial and aquatic habitat conditions) and regional (water quality, hydrological context and land cover composition) drivers on benthic macroinvertebrate assemblages. Using multivariate GLM and structural equation modelling, we investigated variations in the taxonomic and functional composition and in the diversity of native, exotic, shredder and scraper taxa to both set of drivers. Our results showed that soil bioengineering improved local habitat conditions, with an increase in the vegetation density and in the aquatic habitat quality. These changes directly influenced functional composition but indirectly diversity patterns. Instead, we found that native and shredder species richness increased between civil engineered and soil bioengineered structures, suggesting a positive effect of vegetated riverbanks on other local abiotic factors (i.e. shade, water temperature, organic matter supply). Our results also showed that macroinvertebrates were more influenced by regional than by local drivers. Thus, the hydrological context best explained the composition of taxa feeding habits and variation in taxa diversity, with larger abundance and richness of scrapers and shredders in small headwater streams. Land cover ranked second in explaining variation in functional composition. Also, the diversity of natives, scrapers and shredders increased as the proportion of predominantly urban landscapes decreased. Finally, the abundance of scraper and native species increased with water quality, while the richness of exotic species decreased. Overall, these results highlight the hierarchical structure of local and regional drivers on freshwater communities. Along river networks, catchment-scale properties and landscape attributes are major drivers of macroinvertebrate assemblages. Soil bioengineering improves habitat quality and as such appears to be a good compromise solution to control erosion and support freshwater communities, even though this nature-based solution cannot solve anthropogenic pressures at larger scales. To improve the efficiency of restoration efforts, integrated approaches accounting for both local and regional drivers remains a priority.

Land cover composition, climate, and topography drive land surface phenology in a recently burned landscape: An application of machine learning in phenological modeling

Land surface phenology (LSP) characterizes the seasonal dynamics of vegetation communities that compose individual satellite pixels and its interannual and spatial variations have been widely associated with climate. However, increasing evidence shows an effect of land cover composition within a pixel on LSP, but it remains unclear the extent of impacts relative to other drivers. To fill this gap, this study quantitatively assessed the contributions of land cover composition, climate, and topography on the spatial and interannual variation in LSP throughout the 2002 Ponil Complex Fire in New Mexico, USA, using a machine learning approach of Boosted Regression Trees (BRT). As the fire mainly converted ponderosa pine and Douglas-fir (evergreen tree) to soil ground and Gambel Oak (deciduous shrub), we computed both the proportion of tree cover to all vegetation cover (PTV) and vegetation fractional cover (VFC) as the metrics of land cover composition from high-resolution images in 2018 and from MODIS growing season greenness from 2001-2018. Start (SOS) and end (EOS) of growing season were derived from 500-m MODIS data from 2001-2018 and 30-m Harmonized Landsat Sentinel-2 data in 2018. BRT models showed that PTV was the most important predictor of spatial variations in SOS and EOS in 2018, despite the different contributions (20.3% - 42.9%) at 30-m and 500-m spatial scales. Although the growing degree days (28.6%) and the first freeze date (19.6%) were the most important predictors of interannual variations in SOS and EOS from 2001-2018, respectively, VFC also presented an important contribution for SOS (8.4%) and EOS (12.2%). This study demonstrates the utility of machine learning in modeling phenology and highlights the essential role of land cover composition in understanding the spatial and interannual variations of LSP that have been widely associated with topography and climate.

Quantification of the Environmental Impacts of Highway Construction Using Remote Sensing Approach

Highways provide key social and economic functions but generate a wide range of environmental consequences that are poorly quantified and understood. Here, we developed a before–during–after control-impact remote sensing (BDACI-RS) approach to quantify the spatial and temporal changes of environmental impacts during and after the construction of the Wujing Highway in China using three buffer zones (0–100 m, 100–500 m, and 500–1000 m). Results showed that land cover composition experienced large changes in the 0–100 m and 100–500 m buffers while that in the 500–1000 m buffer was relatively stable. Vegetation and moisture conditions, indicated by the normalized difference vegetation index (NDVI) and the normalized difference moisture index (NDMI), respectively, demonstrated obvious degradation–recovery trends in the 0–100 m and 100–500 m buffers, while land surface temperature (LST) experienced a progressive increase. The maximal relative changes as annual means of NDVI, NDMI, and LST were about −40%, −60%, and 12%, respectively, in the 0–100m buffer. Although the mean values of NDVI, NDMI, and LST in the 500–1000 m buffer remained relatively stable during the study period, their spatial variabilities increased significantly after highway construction. An integrated environment quality index (EQI) showed that the environmental impact of the highway manifested the most in its close proximity and faded away with distance. Our results showed that the effect distance of the highway was at least 1000 m, demonstrated from the spatial changes of the indicators (both mean and spatial variability). The approach proposed in this study can be readily applied to other regions to quantify the spatial and temporal changes of disturbances of highway systems and subsequent recovery.

Short Communication: Plant diversity utilization and land cover composition in the Subak Jatiluwih, Bali, Indonesia

Abstract. Sutomo, Iryadi R, Darma ID, Wibawa IPAH, Rahayu A, Hanum SF, Rizal S, Novamizanti L, Raharjo J. 2021. Short Communication: Plant diversity utilization, and land cover composition in the Subak Jatiluwih, Bali, Indonesia. Biodiversitas 22: 1424-1432. Subak is water management or irrigation system for paddy fields in Bali Island and it has been assigned as a UNESCO’s World Heritage Site. At a landscape level, it comprises several components which are forests, terraced paddy landscape, rice fields, villages and temples. Subak in Jatiluwih Village, Tabanan Regency depicts an area characterized by its natural appearance in the form of a vast rice valley with a dike in stratum following its natural contours (frequent terraces). This paper aimed to explore plant diversity in various vegetations around Subak Jatiluwih as well as their usage in the daily living of the local community. We also explore the potential application of drone for classifying the landscape patterns of the Subak.Vegetation sampling to record plant diversity was done using purposive sampling, and drone or Unmanned Aerial Vehicle (UAV) was used to map the Subak Jatiluwih landscape. The potential usage of each species was obtained through interview with key respondents, and the level of usage of each species was analyzed using the BIV (Benefit Index Value). Tegalan area shows the highest number plant diversity in Subak Jatiluwih area. Furthermore, there are four species of plants that have the highest BIV namely: Cocos nucifera L., Psidium guajava L., Areca catechu L. and Musa × paradisiaca L.. Various plant uses by the locals include for animal feed, building, ceremony, craft, and food and medicinal purposes. The landscape in Subak Jatiluwih is dominated the vast valley of rice fields that has strata following its natural contours. These conditions provide opportunities to applied the conservation strategy based on cultural and custom values.

Representativeness of Eddy-Covariance flux footprints for areas surrounding AmeriFlux sites

Large datasets of greenhouse gas and energy surface-atmosphere fluxes measured with the eddy-covariance technique (e.g., FLUXNET2015, AmeriFlux BASE) are widely used to benchmark models and remote-sensing products. This study addresses one of the major challenges facing model-data integration: To what spatial extent do flux measurements taken at individual eddy-covariance sites reflect model- or satellite-based grid cells? We evaluate flux footprints—the temporally dynamic source areas that contribute to measured fluxes—and the representativeness of these footprints for target areas (e.g., within 250–3000 m radii around flux towers) that are often used in flux-data synthesis and modeling studies. We examine the land-cover composition and vegetation characteristics, represented here by the Enhanced Vegetation Index (EVI), in the flux footprints and target areas across 214 AmeriFlux sites, and evaluate potential biases as a consequence of the footprint-to-target-area mismatch. Monthly 80% footprint climatologies vary across sites and through time ranging four orders of magnitude from 103 to 107 m2 due to the measurement heights, underlying vegetation- and ground-surface characteristics, wind directions, and turbulent state of the atmosphere. Few eddy-covariance sites are located in a truly homogeneous landscape. Thus, the common model-data integration approaches that use a fixed-extent target area across sites introduce biases on the order of 4%–20% for EVI and 6%–20% for the dominant land cover percentage. These biases are site-specific functions of measurement heights, target area extents, and land-surface characteristics. We advocate that flux datasets need to be used with footprint awareness, especially in research and applications that benchmark against models and data products with explicit spatial information. We propose a simple representativeness index based on our evaluations that can be used as a guide to identify site-periods suitable for specific applications and to provide general guidance for data use.

Spatial Interconnections of Land Surface Temperatures with Land Cover/Use: A Case Study of Tokyo

As one of the most populated metropolitan areas in the world, the Tokyo Metropolitan Area (TMA) has experienced severe climatic modifications and pressure due to densified human activities and urban expansion. The surface urban heat island (SUHI) phenomenon particularly constitutes a significant threat to human comfort and geo-environmental health in TMA. This study aimed to profile the spatial interconnections between land surface temperature (LST) and land cover/use in TMA from 2001 to 2015 using multi-source spatial data. To this end, the thermal gradients between the urban and non-urban fabric areas in TMA were examined by joint analysis of land cover/use and LST. The spatiotemporal aggregation patterns, variations, and movement trajectories of SUHI intensity in TMA were identified and delineated. The spatial relationship between SUHI and the potential driving forces in TMA was clarified using geographically weighted regression (GWR) analysis. The results show that the thermal environment of TMA exhibited a polynucleated spatial structure with multiple thermal island cores. Overall, the magnitude and extent of SUHI in TMA increased and expanded from 2001 to 2015. During that time, SUHIs clustered in the compact residential quarters and redevelopment/renovation areas rather than downtown. The GWR models showed better performance than ordinary least squares (OLS) models, with Adj R2 > 0.9, indicating that the magnitude of SUHI significantly depended on its neighboring geographical setting, including land cover composition and configuration, population size, and terrain. We suggest that UHI mitigation in Tokyo should be focused on alleviating the magnitude of persistent thermal cores and controlling unstable SUHI occurrence based on partitioned or location-specific landscape design. This study’s findings have immense implications for SUHI mitigation in metropolitan areas situated in bay regions.

Use of molecular scatology to assess the diet of feral cats living in urban colonies

Abstract The overpopulation of domestic cats (Felis catus) presents a serious concern for wildlife conservationists, animal welfare advocates, public health officials, and community members alike. In cities, free-ranging, unowned cats often form high-density groups (commonly called ‘colonies’) around human provisioned food sources. While previous diet studies have primarily utilized morphology-based methods, molecular techniques offer a higher resolution alternative. In this study, we used next-generation sequencing techniques to examine the diet composition of feral cats living in five Trap-Neuter-Return colonies located in urban parks on Staten Island, a borough of New York City. We hypothesized that (1) cats living in urban colonies would still consume natural prey despite being regularly fed and (2) that the composition of taxa represented in the diet of each colony would vary, possibly due to differences in prey availability across sites. In total, 16 vertebrate prey taxa were identified in the diet, 13 at the genus level and 3 at the family level. Despite being regularly fed, 58.2% of cat scats contained DNA from natural prey. The diet composition of the cat colonies differed depending on the land cover composition surrounding the colony with the frequency of native prey positively correlated with the proportion of green space and that of non-native prey with developed land cover types. The use of molecular techniques combined with environmental DNA methods offers a promising, non-invasive approach to assessing the diet and consequently, impact of a highly abundant and non-native predator on the persistence of wildlife communities in cities.

Prospects of eco-hydrological model for sponge city construction

ABSTRACT Introduction Understanding complex urban eco-hydrological processes through models is an important approach in sponge city construction. However, the research on this has not kept pace with the urgent need for sustainable development of urban water resources, which makes the current construction efficiencies unsatisfactory. Outcomes This review highlights the importance of establishing a multi-scale urban distributed eco-hydrological model by analyzing the connotations of sponge city construction. Hydrological models that can be configured for sponge city construction were selected. Traditional models have limitations in coupling ecological and hydrological processes, multi-scale and landscape-based simulations, refined simulations, and computational efficiency. By contrast, cellular automaton has a discrete data structure in space, time, and states, is capable of bottom-up computing, and provides a new conceptual framework for simulating complex urban eco-hydrological processes. Discussion and Conclusion Future model development may focus on the conduction of multi-scale simulation systems, the simulation of coupled urban eco-hydrological processes, the quantification of eco-hydrological responses to land cover composition, spatial configuration and low impact development practices, and improving simulation accuracy.

Dispersal and Land Cover Contribute to Pseudorabies Virus Exposure in Invasive Wild Pigs

We investigated the landscape epidemiology of a globally distributed mammal, the wild pig (Sus scrofa), in Florida (U.S.), where it is considered an invasive species and reservoir to pathogens that impact the health of people, domestic animals, and wildlife. Specifically, we tested the hypothesis that two commonly cited factors in disease transmission, connectivity among populations and abundant resources, would increase the likelihood of exposure to both pseudorabies virus (PrV) and Brucella spp. (bacterial agent of brucellosis) in wild pigs across the Kissimmee Valley of Florida. Using DNA from 348 wild pigs and sera from 320 individuals at 24 sites, we employed population genetic techniques to infer individual dispersal, and an Akaike information criterion framework to compare candidate logistic regression models that incorporated both dispersal and land cover composition. Our findings suggested that recent dispersal conferred higher odds of exposure to PrV, but not Brucella spp., among wild pigs throughout the Kissimmee Valley region. Odds of exposure also increased in association with agriculture and open canopy pine, prairie, and scrub habitats, likely because of highly localized resources within those land cover types. Because the effect of open canopy on PrV exposure reversed when agricultural cover was available, we suggest that small-scale resource distribution may be more important than overall resource abundance. Our results underscore the importance of studying and managing disease dynamics through multiple processes and spatial scales, particularly for non-native pathogens that threaten wildlife conservation, economy, and public health.

Microclimate in an urban park and its influencing factors: a case study of Tiantan Park in Beijing, China

Construction of urban green spaces may effectively mitigate urban heat island effect. Better design of green spaces may improve their thermal performance, and therefore provide better ecosystem services in cities. Aiming at providing empirical evidence and further insights for urban park design, field measurement of air temperature (Ta) and relative humidity (Rh) was conducted in Tiantan Park in Beijing, China. Results show that within Tiantan park, 1.29–2.71 °C air temperature difference and 1.27–5.16% relative humidity difference were observed at different time. Among all parameters, radiation condition (β = 0.872; β = 0.723) and land cover composition (β = 0.601) are dominant influencing factor on daytime and nighttime Ta respectively. Among different vegetation types, deciduous trees have significant cooling and humidifying effects at noon in summer (ρ = −0.65); evergreen trees have little effects in summer, but a humidifying effect in winter (ρ = −0.58); grassland may give rise to daytime Ta in both summer and winter (ρ = 0.48; ρ = 0.52). Effects of the shape of different vegetation types remain unclear, while more compact imperious surfaces may lead to lower daytime Ta (ρ = 0.55; ρ = 0.67). Understanding such microclimate conditions in an urban park may assist designers to create a more thermally friendly environment in future.

Fine-scale roadkill risk models: understanding the intersection of wildlife and roads

Robust, spatially explicit approaches accounting for ecological drivers are needed to identify environmental correlates of roadkill and set conservation priorities. We predicted wildlife road mortality across a nationwide road network using species distribution models with environmental covariates. We applied MaxEnt to a citizen science database of > 60,000 roadkill records to predict roadkill probability. Twenty-eight environmental covariates at 50 m spatial resolution were included, such as road type and land cover composition. We focused on ecological guilds and endangered species: common venomous snakes (CVS), semiaquatic and aquatic snakes (SAS), turtles, and the Maki’s keelback snake (Hebius miyajimae, HM). All predictive models performed well with AUCs > 0.7. Projected roadkill risks for CVS, SAS, turtles, and HM were highest in montane regions, coastal lowlands, the southwestern coast, and parts of central Taiwan, respectively. Roadkill projection models performed well across ecological levels and scales. Road-type strongly influenced roadkill risk. As predictions and variable importance differed across guild and species models, individual models need to be produced for each group of interest. Additionally, the project emphasizes the importance of systematic collection of roadkill data, which contributes to both informing conservation action and engaging the public in wildlife education. We discovered novel findings on predicted high- and low-risk areas for groups with conservation need and produced interactive roadkill risk maps as a conservation tool for managers and practitioners. Importantly, this methodology is not limited to Taiwan; it can be applied anywhere with sufficient roadkill and environmental data and is scalable to address the ecological question of interest.