Tree Canopy Cover Research Articles

Trees on buildings: Opportunities, challenges, and recommendations

Implementation of trees on buildings has substantially increased as an alternative solution to increase tree canopy coverage in dense cities, due to inadequate plantable space at ground level, and to achieve a range of environmental, social, and economic benefits. However, the requirements of this type of implementation have received little attention in the literature. This paper aims to identify and prioritise the opportunities and challenges of implementing trees on buildings by engaging with experts from various disciplines who are experienced in implementing trees on buildings using qualitative and quantitative approaches. This study demonstrates that although there may be challenges to implementing trees on buildings, opportunities significantly outweigh these challenges. Shading and moderating the microclimate was the greatest opportunity, whereas the quality of design, construction, management, and maintenance was considered the biggest challenge in implementing trees on buildings. This study also highlights gaps in the existing literature, including between different disciplines engaged with the tree implementation process and provides recommendations to reduce these gaps, enhance the implementation process, and increase the application of trees on buildings. In addition, the study discusses the implications of the results of this study for research, practice and policy, and compares the study findings with relevant green roof studies.

Are vegetation influences on Arctic–boreal snow melt rates detectable across the Northern Hemisphere?

The timing and rate of northern high latitude spring snowmelt plays a critical role in surface albedo, hydrology, and soil carbon cycling. Ongoing changes in the abundance and distribution of trees and shrubs in tundra and boreal ecosystems can alter snowmelt via canopy impacts on surface energy partitioning. It is unclear whether vegetation-related processes observed at the ecosystem scale influence snowmelt patterns at regional or continental scales. We examined the influence of vegetation cover on snowmelt across the boreal and Arctic region across a ten-year reference period (2000–2009) using a blended snow water equivalent (SWE) data product and gridded estimates of surface temperature, tree cover, and land cover characterized by the dominant plant functional type. Snow melt rates were highest in locations with a late onset of melt, higher temperatures during the melt period, and higher maximum SWE before the onset of melt. After controlling for temperature, melt onset, and the maximum SWE, we found snow melt rates were highest in evergreen needleleaf forest, mixed boreal forest, and herbaceous tundra compared to deciduous needleleaf forest and deciduous shrub tundra. Tree canopy cover had little effect on snowmelt rate within each land cover type. While accounting for the influence of vegetative land cover type is necessary for predictive understanding of snowmelt rate variability across the Arctic–Boreal region. The relationships differed from observations at the ecosystem and catchment scales in other studies. Thus highlighting the importance of spatial scale in identifying snow-vegetation relationships.

Comparing greenspace metrics and buffer methods in Metro Vancouver, Canada: Implications for environmental health research

BACKGROUND & AIM: Access and exposure to greenspace has been shown to promote mental and physical health; however, not all studies have found these benefits, with some studies reporting no association and others reporting associations with adverse health outcomes. It has been suggested that the use of diverse greenspace metrics, the varied quality of these metrics, and the specific methods used to quantify exposure or access, may contribute to these inconsistent findings. This project sought to compare the results of using different metrics in Metro Vancouver, Canada. METHODS: Greenspace metrics were calculated from the centroid of each 6-digit postal code. Average buffer normalized differences vegetation index (NDVI), green landcover, tree canopy cover, and park count were calculated using circular and network buffers, at both 400m and 1000m. Pearson’s correlation coefficients were calculated to compare the results for each metric and method. RESULTS: The number of parks was only weakly positively correlated with each of the other three greenspace metrics for 1000m circular buffers (NDVI r = 0.12; green land cover r = 0.07; tree canopy r = 0.14, p < .01). For 1000m network buffers (NDVI r = -0.34; green landcover r = -0.12; tree canopy r = 0.05, p < .01) two of the correlations became negative. Circular and network buffer were most highly correlated for the tree canopy (1000m r = 0.92; 400m r = 0.86, p < .01), whereas park count had the weakest correlation (1000m r = 0.66; 400m r = 0.66, p < .01). CONCLUSIONS: The associations between greenspace metrics vary. Selection of buffering method may be particularly influential when using park count data. These findings support the importance of intentional selection of greenspace metric and measurement method in environmental epidemiological research. KEYWORDS: greenspace metrics, NDVI, tree canopy cover, parks, network buffers, and circular buffers

Quantification of green and walkable neighbourhoods across the distribution of social and material deprivation in Metro Vancouver, Canada

BACKGROUND & AIM: Along with other environmental exposures, both neighbourhood walkability, and greenspace exposure and access have been linked to many diverse health benefits. Previous work has examined the spatial relationship of built and natural environments according to levels of neighbourhood deprivation; however, less is known about how these relationships may vary when different greenspace metrics are used. This work examines how normalized differences vegetation index (NDVI), tree canopy cover, green land cover, and park count metrics relate to walkability, and how these neighbourhood characteristics associate with both social and material deprivation. METHODS: Greenspace exposure was measured using NDVI, tree canopy cover, and green land cover, while park access was quantified by the number of designated public parks within 1000m and 400m network buffers for each six-digit postal-code centroid in Metro Vancouver, Canada. Local area deprivation was measured using the 2016 Material and Social Deprivation Index (MSDI). Pearson’s correlation coefficients were calculated to compare these neighbourhood characteristics. RESULTS: Walkability was positively associated with social deprivation (1000m r = 0.48; 400m r = 0.48, p < .01), while walkability has a weak inverse relationship with material deprivation (1000m r = -0.21, p < .01). Tree canopy was negatively related to both social (1000m r = -0.23, 400m r = -0.23, p < .01) and material deprivation (1000m r = -0.24, 400m r = -0.23, p < .01). In contrast, the relationship between park count and both deprivation measures was weak. CONCLUSION: In this study, areas with greater social and material deprivation tend to have less greenspace, but not necessarily less park access. The identification of neighbourhoods with higher material deprivation, low walkability, and low greenspace, may be prioritized by urban planners and decision makers as possible locations for additional greenspace allocation. KEYWORDS: greenspace, walkability, social deprivation, material deprivation

Association between Residential Green Space and Healthcare Utilization

BACKGROUND AND AIMS Prior studies have shown greenness to be associated with beneficial health outcomes. We sought to determine if residential greenness correlated with healthcare utilization within an integrated health delivery system. METHODS We linked 5,189,303 members of Kaiser Permanente Northern California (KPNC) to Normalized Differentiated Vegetation Index (NDVI) values from Landsat satellite data (30m x 30m resolution) in 250, 500, and 1000 m radial buffers around each member's home. Healthcare utilization data for inpatient, outpatient, and emergency room visits were obtained by accessing data from the KPNC electronic health record. Using generalized estimating equations that adjusted for demographic, socioeconomic and other environmental factors, we regressed green space (in deciles) on healthcare utilization across the 2013 and 2017 study period. Adjustments were made for area sociodemographic and socioeconomic factors, and population and housing density. RESULTS We observed a significant trend across the decile range between higher levels of residential greenness and lower utilization of inpatient services (p<0.01) and emergency room visits (p<0.01). For outpatient visits, we observed a U-shaped curve where residing in middle of the NDVI range for this population was associated with greater outpatient visits than either the highest or lowest green space areas. Sensitivity analyses, including using various buffer sizes and tree canopy cover, an alternative measure of green space, yielded consistent findings. CONCLUSION Residing in an area with greater greenspace relative to low levels of greenspace was associated with greater in-patient and emergency room utilization. Residential greening can have a significant healthcare impact as measured by healthcare utilization. Keywords: green space, green cover, healthcare utilization, healthcare services

Early Life Exposure to Greenspace and Autism Spectrum Disorder and the Mediating Effects of Air Pollution in Ontario, Canada

BACKGROUND AND AIM Early life exposure to greenspace is associated with health benefits on childhood development, but the pathways of this relationship are not completely understood. This study aimed to evaluate early life exposure to different greenspace metrics on the development on autism spectrum disorder (ASD) and whether these associations are mediated by reductions in ambient air pollution. METHODS This case-control study included 1,801 ASD cases and 9002 controls less than 5 years of age identified from 2012 to 2017 using health administrative databases in the province of Ontario, Canada. Greenspace metrics were estimated using the Normalized Difference Vegetation Index (NDVI), Green View Index (GVI) and percent tree canopy coverage using values within 250 m of participants’ residential postal codes at birth. Conditional logistic regression was used to investigate associations between greenspace exposure and ASD while adjusting for maternal age, parity, maternal comorbidities, substance use (i.e. smoking and alcohol), socioeconomic status and urbanicity. We estimated the mediation effects of nitrogen dioxide (NO2), fine particulate matter (PM2.5), and ozone (O3) using causal mediation analyses. RESULTS In the adjusted model, we found that one interquartile range (IQR) increase in percentage tree canopy was associated with a 6% reduction in the odds of ASD (Odds ratio = 0.94; 95% CI: 0.90, 0.98). No associations were found for NDVI and GVI in relation to ASD. We found that 81.8% (77.6 – 85.9), 20.1% (16.6 – 23.6) and 13.6% (11.1 – 16.0) of the association between tree canopy exposure and ASD was mediated through reductions in NO2, PM2.5, and O3, respectively. CONCLUSIONS Early life exposure to greenspace might reduce the risk of ASD through reductions in ambient air pollution, in particular traffic pollution from NO2. Our findings may provide support to communities on the potential health benefits of greenspaces.

Combining aerial photos and LiDAR data to detect canopy cover change in urban forests.

The advancement and accessibility of high-resolution remotely sensed data has made it feasible to detect tree canopy cover (TCC) changes over small spatial scales. However, the short history of these high-resolution collection techniques presents challenges when assessing canopy changes over longer time scales (> 50 years). This research shows how using high-resolution LiDAR data in conjunction with historical aerial photos can overcome this limitation. We used the University of British Columbia's Point Grey campus in Vancouver, Canada, as a case study, using both historical aerial photographs from 1949 and 2015 LiDAR data. TCC was summed in 0.05 ha analysis polygons for both the LiDAR and aerial photo data, allowing for TCC comparison across the two different data types. Methods were validated using 2015 aerial photos, the means (Δ 0.24) and a TOST test indicated that the methods were statistically equivalent (±5.38% TCC). This research concludes the methods outlined is suitable for small scale TCC change detection over long time frames when inconsistent data types are available between the two time periods.

Estimating the GPP of olive trees with variable canopy cover by the use of Sentinel-2 MSI images

The estimation of gross primary production (GPP) is a key step towards the simulation of crop yield which can be performed by feeding the light use efficiency approach with remotely sensed estimates of absorbed photosynthetic active radiation (fAPAR). The application of this approach, however, is problematic for bi-layer ecosystems, such as olive groves, which have tree canopy cover (CC) variable in space and time due, for example, to pruning or leaf growing. The current paper investigates on this issue concerning a small olive grove in Florence (Central Italy), which, during the 2021 growing season, was monitored by standard meteorological and soil water content measurements; additionally, observations of fAPAR were taken in four plots differently affected by spring pruning. These ground observations allowed to calculate daily GPP references for the four plots, which were used to assess corresponding estimates obtained from interpolated weather data and Sentinel-2 MSI NDVI imagery. In particular, the fAPAR and GPP estimates were obtained both considering the NDVI values of the entire plots and separating the contribution of olive tree canopies from that of grasses. The results of the experiment indicated that the GPP of the most intensively pruned plots could be estimated correctly only by taking into consideration the temporally variable fAPAR contribution of olive tree canopies.

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.

The impact of shade tree species identity on coffee pests and diseases

The multifunctional role of shade trees for conservation of biodiversity and ecosystem services in natural forests and agroforests is well documented, yet we lack insights into the impact of shade tree species identity on pest and disease dynamics on agroforestry crops such as coffee and cacao, and its implications for management. We conducted two surveys on the impact of shade tree species identity and canopy cover on pests, diseases and a fungal hyperparasite on Arabica coffee in southwestern Ethiopia, which is one of the areas of origin of Arabica coffee. One survey was in a commercial plantation, and the other along a management gradient from only little managed coffee growing in the natural forest to intensively managed commercial plantations. To link these findings to current shade tree selection criteria, we complemented these surveys by interviews with farmers and managers. Shade tree species identity left a weak imprint on insect pest levels, and insect pests levels differed strongly in the strength and direction of their response to canopy cover. In contrast to the insect pests, the incidence of coffee leaf rust and its hyperparasite, as well as coffee berry disease, differed among shade tree species, with particularly high levels of coffee leaf rust and the hyperparasite underneath the canopy of the shade trees Acacia abyssinica and Croton macrostachyus, and coffee berry disease underneath the canopy of Acacia abyssinica and Polyscias fulva. Smallholder farmers used many criteria for selecting shade trees, such as leaf traits and competition for soil moisture, but low priority is given to the effect of shade tree species identity on pests and diseases. Our findings help to understand spatial variation in pest and disease dynamics in natural forests and agroforests, and may inform the selection of shade tree species by coffee producers and thereby contribute to ecologically-informed pest and disease management. Importantly, our finding highlight the potential for using tree identity for the sustainable management of pests and diseases, with relevance for global agroforestry systems.

Study on the land surface cover dynamics of built-up areas and its implication for sustainable urban planning in Hawassa city, Ethiopia

Rapid and uncontrolled urbanization is one of the drivers responsible for land cover Change dynamics in Ethiopia. In most of the cities and towns of Ethiopia, the proportion of different types of urban land surface cover and trends of change in each are unknown and thus hindering environmentally sustainable urban planning. This study describes different land surface cover types and their dynamics of change, and subsequent influence on the Land Surface Temperature of Hawassa city between 2011 and 2021. The i-Tree canopy and Landsat 5 (TM) and Landsat 8 (OLI) images were used for 2011 and 2021 to analyze the land surface cover and surface temperature change, respectively. The results show that bare soil is the dominant land surface cover type (23.4%), followed by tree canopy cover (21.4%), while impervious roads occupied the smallest land surface area cover (3.4%) along with water bodies (1%). In 10 years most of the land surface cover types increased positively, including tree covers by + 9.8%. The only exceptions were bare soil and herbaceous cover, which decreased drastically by − 34.6% and − 2.8%, respectively. As a result of tree cover increment, the average and maximum Land Surface Temperature showed a declining trend between the two periods. This study shows that increasing tree cover in line with the expansion of urbanization is inversely correlated with the land surface temperature which implies that integrating green coverage along with the built-up area can reduce heatwave in the fast growing urban areas. Therefore, the Hawassa city administration should set tree cover targets to achieve the desired balance between green and grey infrastructure and enhance the climate resilience level of the study area.

Evaluating Statewide NAIP Photogrammetric Point Clouds for Operational Improvement of National Forest Inventory Estimates in Mixed Hardwood Forests of the Southeastern U.S.

The U.S. Forest Service, Forest Inventory and Analysis (FIA) program is tasked with making and reporting estimates of various forest attributes using a design-based network of permanent sampling plots. To make its estimates more precise, FIA uses a technique known as post-stratification to group plots into more homogenous classes, which helps lower variance when deriving population means. Currently FIA uses a nationally available map of tree canopy cover for post-stratification, which tends to work well for forest area estimates but less so for structural attributes like volume. Here we explore the use of new statewide digital aerial photogrammetric (DAP) point clouds developed from stereo imagery collected by the National Agricultural Imagery Program (NAIP) to improve these estimates in the southeastern mixed hardwood forests of Tennessee and Virginia, United States (U.S.). Our objectives are to 1. evaluate the relative quality of NAIP DAP point clouds using airborne LiDAR and FIA tree height measurements, and 2. assess the ability of NAIP digital height models (DHMs) to improve operational forest inventory estimates above the gains already achieved from FIA’s current post-stratification approach. Our results show the NAIP point clouds were moderately to strongly correlated with FIA field measured maximum tree heights (average Pearson’s r = 0.74) with a slight negative bias (−1.56 m) and an RMSE error of ~4.0 m. The NAIP point cloud heights were also more accurate for softwoods (R2s = 0.60–0.79) than hardwoods (R2s = 0.33–0.50) with an error structure that was consistent across multiple years of FIA measurements. Several factors served to degrade the relationship between the NAIP point clouds and FIA data, including a lack of 3D points in areas of advanced hardwood senescence, spurious height values in deep shadows and imprecision of FIA plot locations (which were estimated to be off the true locations by +/− 8 m). Using NAIP strata maps for post-stratification yielded forest volume estimates that were 31% more precise on average than estimates stratified with tree canopy cover data. Combining NAIP DHMs with forest type information from national map products helped improve stratification performance, especially for softwoods. The monetary value of using NAIP height maps to post-stratify FIA survey unit total volume estimates was USD 1.8 million vs. the costs of installing more field plots to achieve similar precision gains. Overall, our results show the benefit and growing feasibility of using NAIP point clouds to improve FIA’s operational forest inventory estimates.

Rethinking forest monitoring for more meaningful global forest landscape change assessments.

Forest ecosystems play an indispensable role in addressing various pressing sustainability and social-ecological challenges such as climate change, biodiversity loss, and ecosystem services deterioration, hence the monitoring of the world's forests is crucial. As part of the global forest assessment workflow, a forest is generally classified and mapped based on land use and/or using a tree canopy cover threshold. In this paper, we examine the limitations of this approach and argue that the use of a land use-based forest definition and tree canopy cover thresholds can overlook forest degradation and enhancement, disguise the actual status of forest landscapes, and misinform management planning. These limitations can delay the development and implementation of forest restoration and conservation measures. To help overcome these issues, we propose some enhancements to the global forest assessment workflow, including the sharing of spatial data and inclusion of tree canopy cover estimates in assessment reports. Such enhancements are needed to achieve more meaningful forest monitoring and reporting in the context of global environmental initiatives, such as those related to climate change mitigation and adaptation, forest restoration, biodiversity conservation, and ecosystem services monitoring.

Project IICE

Project IICE was a multi-disciplinary learning experience designed for students at Southern New Hampshire University. Students worked together in teams to communicate scientific data that was initially collected by an Introductory Botany class. Students in this course measured trees and recorded variables, including tree height, diameter, species, and canopy cover. They shared the data with students in freshman Statistics courses, who analyzed mathematically for trends. Finally, students in Graphic Design used the data to create visual representations and icons. Students collaborated in groups that were randomly assigned across all of the courses to include members of each discipline. During the process, each student was required to help others in the group understand the meaning of the data, through the collection, analysis, and design phases. In the final group poster presentations, students explained the meaning and value of each part. The emphasis was on their ability to communicate the significance of each part of the process, which helped them appreciate how the discipline they were working in contributed to the overall success of the project. The real-world data provided a context for students to experience working in cross-discipline teams, and sharpened communication skills.

Habitat use by mixed-species bird flocks in tropical forests of the Western Ghats, India

AbstractWhile mixed-species flocks of birds (hereafter ‘flocks’) have been widely studied, few studies have looked at the effect of habitat structure on flock presence and flocking propensity within a site. Here, we employ a use-availability approach in locations with flocks and random locations to ask whether habitat characteristics influence the presence of flocks, and whether structurally similar microhabitats support compositionally similar flocks. We also examine the effect of habitat on flock size and species richness, and the effect of intraspecifically gregarious flock participants on habitat selection. We find that flocks use a narrow subset of available tree density and canopy cover variation and prefer relatively less-dense areas with large trees and a complex foliage structure. Similar microhabitats do not result in compositionally similar flocks, and while foliage complexity was associated with flock size, no habitat characteristics influenced species richness. Flocks led by the intraspecifically gregarious western crowned warbler (Phylloscopus occipitalis), a potential nuclear species, showed preference for high foliage complexity and tree density. Thus, habitat preferences of intraspecifically gregarious species, which are followed by other species, could play a strong role in habitat selection in flocks. This suggests that degraded forests that cannot provide a suitable range of tree density, canopy cover, and/or complex vegetation structure may not support some core flock species around which flocks form, which may lead to decreased flocking in those patches.

Effect of urban street trees on pedestrian safety: A micro-level pedestrian casualty model using multivariate Bayesian spatial approach

In the past decades, trees were considered roadside hazard. Street trees were removed to provide clear zone and improve roadside safety. Nowadays, street trees are considered to play an important role in urban design. Also, street tree is considered a traffic calming measure. Studies have examined the effects of urban street trees on driver perception, driving behaviour, and general road safety. However, it is rare that the relationship between urban street trees and pedestrian safety is investigated. In this study, a micro-level frequency model is established to evaluate the effects of tree density and tree canopy cover on pedestrian injuries, accounting for pedestrian crash exposure based on comprehensive pedestrian count data from a state in Australia, Melbourne. In addition, effects of road geometry, traffic characteristics, and temporal distribution are also considered. Furthermore, effects of spatial dependency and correlation between pedestrian casualty counts of different injury severity levels are accounted using a multivariate Bayesian spatial approach. Results indicate that road width, bus stop, tram station, on-street parking, and 85th percentile speed are positively associated with pedestrian casualty. In contrast, pedestrian casualty decreases when there is a pedestrian crosswalk and increases in tree density and canopy. Also, time variation in pedestrian injury risk is significant. To sum up, urban street trees should have favorable effect on pedestrian safety. Findings are indicative to optimal policy strategies that can enhance the walking environment and overall pedestrian safety. Therefore, sustainable urban and transport development can be promoted.

Evidence-based guidelines for greener, healthier, more resilient neighbourhoods: Introducing the 3–30–300 rule

The important contributions of urban trees and green spaces to for example, climate moderation and public health have been recognized. This paper discusses guidelines and norms that promote the benefits of viewing green, living amongst green, and having easy access to green spaces for recreational use. Having trees and other vegetation in sight from one’s home, place of work, or school has important mental health and performance benefits. Local tree canopy cover is positively associated with cooling and other aspects of climate moderation. With public green spaces in proximity to one’s home stimulates regular use of these areas and results in positive impacts on mental, physical, and social health. After analyzing existing guidelines and rules for urban green space planning and provision, a new, comprehensive guideline is presented, known as the ‘3–30–300 rule’ for urban forestry. This guideline aims to provide equitable access to trees and green spaces and their benefits by setting the thresholds of having at least 3 well-established trees in view from every home, school, and place of work, no less than a 30% tree canopy in every neighbourhood; and no more than 300 m to the nearest public green space from every residence. Current implementation of this new guideline is discussed, as well as the advantages and disadvantages of using this evidence-based but also clear and simple rules.

The relationship between natural environments and subjective well-being as measured by sentiment expressed on Twitter

There is growing evidence that time spent in nature can affect well-being. Nonetheless, assessing this relationship can be difficult. We used 1,971,045 geolocated tweets sent by 81,140 users from Seattle, Washington, USA to advance our understanding of the relationship between subjective well-being and natural environments. Specifically, we quantified the relationships between sentiment (negative/neutral/positive) expressed in geolocated tweets and their surrounding environments, focusing on three environmental indicators: land-cover type, tree-canopy density, and urban parks. We allowed the relationships to vary according to the broader type of environment (i.e., land-use zoning). We estimated three random-intercept partial proportional odds models corresponding to the three environmental indicators while controlling for multiple covariates. Our results suggested that for a given land-use type, tweets sent from some natural land-cover types were less likely to be negative compared to tweets sent from the urban built land-cover type. For tweets sent in industrial zones, an increase in tree-canopy cover was associated with a lower probability of having negative sentiments and with a higher probability of having positive sentiments; but for tweets sent in commercial/mixed zones, the association was reversed. Also, urban parks were generally associated with a lower probability of having negative sentiments, but tweets sent from large natural parks in residential zones were less likely to be positive. Our results suggest that the relationship between subjective well-being and natural environments depends on where people are situated in the built environment and may be more complex than previously thought. The more nuanced understanding provided by analyzing geolocated social media has potential to inform urban planning and land management.

Tradeoffs and synergies among ecosystem services, biodiversity conservation, and food production in coffee agroforestry

Concerns over the capacity of the world’s existing agricultural land to provide food for the global population under climate change and continued biodiversity loss have set the stage for a prevailing narrative of inherent tradeoffs with agricultural production. Coffee, a major export of tropical countries, offers a unique opportunity to examine how different management practices can lead to a variety of outcomes in food security, ecosystem services, and biodiversity conservation. Our study examined this intersection to identify tradeoffs and synergies using compiled data from Puerto Rico. At the island level, we analyzed data on coffee yield and planted area under shade or sun management. At the farm level, we analyzed management variables (percent shade cover, maximum canopy height, ground cover, and food crop richness), non-provisioning ecosystem services variables (total farm carbon storage, soil organic carbon storage, coffee plant carbon biomass, and hurricane resistance and resilience), and biodiversity variables (ant, bird, and lizard richness and abundance). At the island level, we found that planted area was the most significant predictor of total production, suggesting no obvious tradeoff between production and shade management in coffee farms. At the farm level, canopy cover of shade trees was negatively correlated with ground cover and positively correlated with food crop richness, suggesting a synergy between agroforestry and subsistence food production. We detected mostly synergies associated with ecosystem services, biodiversity conservation, and agroforestry management and no tradeoffs among ecosystem service and biodiversity parameters. Shade canopy cover significantly increased total carbon storage, coffee plant biomass, hurricane resistance, and bird species richness. Shade canopy height had a similar positive effect on total farm carbon storage while food crop richness had a positive effect on farm resilience following Hurricane Maria. Ground cover was positively associated with soil carbon storage and pest-controlling lizard abundance. Tradeoffs related to agroforestry management included an inverse relationship between ground cover and hurricane resistance and more dominance of an invasive ant species in farms with higher shade canopies. We discuss the implications of practicing agroforestry principles in this smallholder coffee system and highlight opportunities to contribute to more diversified food production systems that support biodiversity and ecosystem services.

Patch and landscape features drive fire regime in a Brazilian flammable ecosystem

The flammable ecosystems are evolutionary dependent on the periodic action of fire. Several environmental factors, both at local and landscape scales, can affect fire regimes in these ecosystems differently. Here, we evaluated the influence of local and landscape features on two parameters of the fire regime of a flammable protected area of the Brazilian savanna: The Chapada Diamantina National Park. We characterized both fire frequency and the time since the last fire, from 1990 to 2019 and measured five environmental predictors (tree canopy cover, altitude, water surface, predominant land use and distance to the nearest municipality). We used Generalized Additive Models for Location, Scale and Shape (GAMLSS) to assess the influence of environmental predictors on the measured fire regime parameters. We found a large interannual variation in the total annual area burned in the studied period. In total, 68 % of the protected area (1030 km2) was burned at least once and 32 % (486 km2) was unaffected by fires during the study period. Predominant land use, distance to the nearest municipality, tree cover and the interaction between tree cover and altitude were negatively related to fire frequency, while the water surface and altitude positively influenced fire frequency in the park. Compared to older fires, recent fires occurred in landscapes at lower altitudes and with lower tree cover. Our results demonstrate that the fire frequency and time since the last fire were highly variable across the park, reflecting the strong influence of landscape heterogeneity on their parameters.