Where the not-so-wild things are in cities? The influence of social-ecological factors in urban trees at multiple scales

Green infrastructure plays an essential role in cities due to the ecosystem services it provides. However, these elements are shaped by social and ecological factors that influence their distribution and diversity, affecting ecological functions and human well-being. Here, we analyzed neighborhood tree distribution - trees in pocket parks, squares and along streets - in Lisbon (Portugal) and modelled tree abundance and taxonomic and functional diversity, at the parish and local scales, considering a comprehensive list of social and ecological factors. For the functional analyses, we included functional traits linked to dispersal, resilience to important perturbations in coastal Mediterranean cities, and ecosystem services delivery. Our results show not only that trees are unevenly distributed across the city, but that there is a strong influence of social factors on all biological indices considered. At the parish and local scales, abundance and diversity responded to different factors, with abundance being linked to both social and ecological variables. Although the influence of social factors on urban trees can be expected, by modelling their influence we can quantify how much humans modify urban landscapes at a structural and functional level. These associations can underlie potential biodiversity filters and should be analyzed over time to inform decisions that support long-term ecological resilience, maximize trait functional expression, and increase equity in ecosystem services delivery.

Time outdoors and residential greenness are associated with reduced systemic inflammation and allostatic load

Contacts with nature are linked with reduced morbidity and mortality. Hypothesized pathways include relaxation, physical activity, and improved immune function. This cross-sectional study of 320 adults in central North Carolina assessed health benefits of residential greenness using allostatic load (AL) and systemic inflammation (INFL) indices, composite biomarker-based measures of physiological dysregulation and inflammation, respectively. Distance-to-residence weighted tree cover and vegetated land cover measures were estimated within 500 m of each residence; 37 biomarkers of immune, neuroendocrine, cardiovascular, and metabolic functions were dichotomized at distribution or health-based cut-offs. AL was calculated as a sum of potentially unhealthy values of all biomarkers; INFL was based on a subset of 18 immune biomarkers. Regression analysis used generalized additive models for Poisson-distributed outcome. An interquartile range (IQR) increase in tree cover was associated with 0.89 (95 % Confidence Limits 0.82; 0.97) and 0.90 (0.79; 1.03)-fold change in AL and INFL, respectively. Greater daily outdoor time was associated with reduced AL and INFL, while leisure screen time, problems with sleeping, and common chronic infections were linked with increased AL and INFL. Among 138 individuals spending more than 1 h outdoors daily, an IQR increase in tree cover was associated with 0.76 (0.67; 0.86) and 0.81 (0.65; 1.02)-fold changes in AL and INFL, respectively. Among individuals with residential tree cover above the 50th percentile, spending more than 3 h outdoors daily was associated with 0.54 (0.37; 0.78) and 0.28 (0.15; 0.54)-fold changes in AL and INFL, respectively, compared to spending less than 30 min outdoors; there were no significant effects in the low tree cover stratum. Consistent but weaker effects were observed for vegetated land cover. Interaction effects of tree and vegetative cover and time spent outdoors on AL and INFL were statistically significant. This biomarker-based approach can help to assess public health benefits of green spaces.

Varying effects of tree cover on relationships between satellite-observed vegetation greenup date and spring temperature across Eurasian boreal forests

Earth observation satellites have facilitated the quantification of how vegetation phenology responds to climate warming on large scales. However, satellite image pixels may contain a mixture of multiple vegetation types or species with diverse phenological responses to climate variability. It is unclear how these mixed pixels affect the statistical relationships between satellite-derived vegetation phenology and climate factors. Here, we aim to investigate the impacts of percent tree cover (PTC), a measure of mixed pixel, on the statistical relationships between satellite-derived vegetation greenup date (GUD) and spring air temperature across Eurasian boreal forests at a 0.05° spatial resolution. We estimated GUD using Moderate Resolution Imaging Spectroradiometer (MODIS) time series data. The responses of GUD to interannual variation in spring temperature (April to May) during 2001-2020 were characterized by correlation coefficient (RTAM) and sensitivity (STAM). We then evaluated the local impacts of PTC on spatial variations in RTAM and STAM using partial correlation analysis through spatial moving windows. Our results indicate that, for most areas, forests with higher PTC were associated with stronger RTAM and STAM. Moreover, PTC had stronger local impacts on RTAM and STAM than mean annual temperature and temperature seasonality for 37.3% and 27.4% of the moving windows, respectively. These impacts were spatially varying and different among forest types. Specifically, deciduous broadleaf forests and deciduous needleleaf forests tend to have a higher proportion of these impacts compared to other forest types. Our findings demonstrate the nonnegligible effects of PTC on the statistical responses of GUD to temperature variability at coarse spatial resolution (0.05°) across Eurasian boreal forests.

Joint associations and pathways from greenspace, traffic-related air pollution, and noise to poor self-rated general health: A population-based study in Sofia, Bulgaria

BACKGROUND

Little is still known of how multiple urban exposures interact as health determinants. This study investigated various ways in which greenspace, traffic-related air pollution, and noise could operate together, influencing general health status.

METHODS

In 2022, a cross-sectional population-based survey was conducted in Sofia, Bulgaria. Included were 917 long-term adult residents who completed questionnaires on poor self-rated health (PSRH), total time spent in physical activity (PA), home garden presence, time spent in urban greenspace and nature, and sociodemographics. Residential greenspace was operationalized using the normalized difference vegetation index (NDVI), tree cover density, number of trees, and access to local greenspace and parks. Nitrogen dioxide (NO₂) was modeled for the study area. Road traffic, railway, and aircraft day-evening-night sound levels (L_den) were extracted from EU noise maps. Area-level income and urbanicity were considered. Analyses included multivariate ordinal regressions, interactions, and structural equation modeling (SEM).

RESULTS

Associations with PSRH were per 0.10 NDVI _300 m: OR = 0.65 (0.42-1.01), home garden: OR = 0.72 (0.49-1.07), per 5 μg/m³ NO₂: OR = 1.57 (1.00-2.48), per 5 dB(A) L_den road traffic: OR = 1.06 (0.91-1.23), railway: OR = 1.11 (1.03-1.20), and aircraft: OR = 1.22 (1.11-1.34). Spending >30 min/week in nature related to better health. In multi-exposure models, only associations with aircraft and railway L_den persisted. People with lower education and financial difficulties or living in poorer districts experienced some exposures stronger. In SEM, time spent in nature and PA mediated the effect of greenspace.

CONCLUSIONS

Greenspace was associated with better general health, with time spent in nature and PA emerging as intermediate pathways. NO₂, railway, and aircraft noise were associated with poorer general health. These results could inform decision-makers, urban planners, and civil society organizations facing urban development problems. Mitigation and abatement policies and measures should target socioeconomically disadvantaged citizens.

Spatial and temporal analysis of HCHO response to drought in South Korea

Though drought is known to affect biogenic emissions of volatile organic compounds (BVOC), its effect on isoprene and formaldehyde (HCHO), a high yield product of isoprene, has not been investigated in East Asia where incidences of drought have increased in recent years. In this work, we analyzed the impact of drought on HCHO in the South Korea region during the summer period (June, July, and August) from 2005 to 2018 and found increased HCHO due to drought. The tropospheric HCHO column density retrieved by OMI increased by 8.02 % during extreme drought compared to the non-drought period, whereas no significant effect of drought on the NO₂ column was found. Regional variation of HCHO response to drought correlates significantly with the tree percentage of the region. This correlation indicates that the drought-led HCHO increases are most likely driven by the increase in isoprene emissions during drought. Indeed, model predicts isoprene emissions to be higher by 27.87 % during the extreme drought compared to the non-drought period in South Korea. From 2005 to 2018, the HCHO column has been increasing in South Korea by 0.16 × 10¹⁵ molecules/cm²/year (1.56 % per year) during summer months, correlated with the increasing incidences of drought. HCHO increase is linked to higher ozone as most of South Korea is in the NOx-saturated or transitional regime.

Breeding in the pandemic: short-term lockdown restrictions in a European capital city did not alter the life-history traits of two urban adapters

Humans are transforming natural habitats into managed urban green areas and impervious surfaces at an unprecedented pace. Yet the effects of human presence per se on animal life-history traits are rarely tested. This is particularly true in cities, where human presence is often indissociable from urbanisation itself. The onset of the SARS-CoV-2 outbreak, along with the resulting lockdown restrictions, offered a unique, "natural experiment" to investigate wildlife responses to a sudden reduction in human activity. We analysed four years of avian breeding data collected in a European capital city to test whether lockdown measures altered nestbox occupancy and life-history traits in terms of egg laying date, incubation duration and clutch size in two urban adapters: great tits (Parus major) and blue tits (Cyanistes caeruleus). Lockdown measures, which modulated human presence, did not influence any of the life-history traits investigated. In contrast, the interaction between year and tree cover, a distinct ecological attribute of the urban space, was positively associated with clutch size, a key avian life-history and reproductive trait. This highlights the importance of inter-year variation and habitat quality over human activity on urban wildlife reproduction. We discuss our results in the light of other urban wildlife studies carried out during the pandemic, inviting the scientific community to carefully interpret all lockdown-associated shifts in biological traits.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11252-022-01309-5.

Measuring Spatial Associations between Environmental Health and Beliefs about Environmental Governance

Research has shown an increasing trend in attempts to integrate social and ecological data that use indicators to improve quality of life. This includes understanding people's beliefs about environmental governance. Understanding patterns in beliefs of environmental governance can be a powerful way to help policy makers take informed actions that meet individuals' needs and expectations. This study examines connections between spatial patterns of beliefs about environmental governance and the health of the environment where people live, measured from both a public health and ecological perspective. Data on people's beliefs about environmental governance were collected in the Puget Sound area of Washington state. Environmental health data include environmental public health disparities including effects and exposures, bird diversity, and tree cover. Results indicate local scale heterogeneity exists within the Puget Sound region. Using AIC model selection, there was strong evidence for effects of canopy cover, environmental effects and exposures, and years of residency, and moderate to strong evidence for the effects on beliefs about environmental governance of race and sex. There was little support for effects of political ideology, income, age, education, or bird diversity. The Akaike Information Criteria (AIC) top model included a negative effect of canopy cover, years of residency, race (i.e., of being non-white), and sex (i.e., of being male), and a positive effect of environmental effects and of environmental exposures. Relating data on environmental health and beliefs about environmental governance generates a more nuanced understanding of determinants of environmental governance success and public support.

cities, 2015-2020

Neighborhood segregation by race and income is a structural determinant of firearm violence. Addressing green space deficits in segregated neighborhoods is a promising prevention strategy. This study assessed the potential for reducing firearm violence disparities by increasing access to tree cover. Units of analysis were census tracts in six U.S. cities (Baltimore, MD; Philadelphia, PA; Richmond, VA; Syracuse, NY; Washington, DC; Wilmington, DE). We measured segregation using the index of concentration at the extremes (ICE) for race-income. We calculated proportion tree cover based on 2013-2014 imagery. Outcomes were 2015-2020 fatal and non-fatal shootings from the Gun Violence Archive. We modeled firearm violence as a function of ICE, tree cover, and covariates representing the social and built environment. Next, we simulated possible effects of "tree equity" programs, i.e., raising tract-level tree cover to a specified baseline level. In our fully-adjusted model, higher privilege on the ICE measure (1 standard deviation, SD) was associated with a 42% reduction in shootings (incidence rate ratio (IRR) = 0.58, 95% CI [0.54 0.62], p < 0.001). A 1-SD increase in tree cover was associated with a 9% reduction (IRR = 0.91, 95% CI [0.86, 0.97], p < 0.01). Simulated achievement of 40% baseline tree cover was associated with reductions in firearm violence, with the largest reductions in highly-deprived neighborhoods. Advancing tree equity would not disrupt the fundamental causes of racial disparities in firearm violence exposure, but may have the potential to help mitigate those disparities.

The evaluation of the 3-30-300 green space rule and mental health

BACKGROUND AND AIMS

Urban green space has many health benefits, but it is still unclear how much actually is needed for better health. Recently a new 3-30-300 rule of thumb for urban forestry and urban greening has been proposed, but this rule has not been evaluated for benefits on health. The rule requires that every citizen should be able to see at least three trees from their home, have 30 percent tree canopy cover in their neighbourhood and not live more than 300 m away from the nearest park or green space. The aim of this study was to evaluate the relationship between the 3-30-300 green space rule and its components in relation to mental health.

METHODS

We conducted a cross-sectional study based on a population-based sample of 3145 individuals aged 15-97 years from in Barcelona, Spain who participated in the Barcelona Health Survey (2016-2017). We created 3-30-300 green space indicators using questionnaire data, GIS, remote sensing and land cover maps. Mental health status was assessed with the 12-item General Health Questionnaire (GHQ-12) and also the use of tranquilizer/sedatives or antidepressants and psychiatrist or psychologist visits. Analyses were conducted using mixed effects logistic regression models with districts as the random effect, adjusted for relevant covariates.

RESULTS

We found that people in Barcelona had relatively little exposure to green space, whether through window view, living in an area with sufficient greenness, or access to a major green space, and only 4.7% met a surrogate 3-30-300 green space rule. Residential surrounding greenness, but not tree window view or access to major green space, was significantly associated with better mental health, less medication use, and fewer psychologist or psychiatrist visits. Meeting the full surrogate 3-30-300 green space rule was associated with better mental health, less medication use, and fewer psychologist or psychiatrist visits, but only for the latter combined the association was statistically significant (Odds ratio = 0.31, 95% CI: 0.11, 0.91).

CONCLUSION

Few people achieved the 3-30-300 green space in Barcelona and we used a surrogate measure. We observed health benefits when the full surrogate rule was met.

The relationship between greenspace and personal exposure to PM2.5 during walking trips in Delhi, India

The presence of urban greenspace may lead to reduced personal exposure to air pollution via several mechanisms, for example, increased dispersion of airborne particulates; however, there is a lack of real-time evidence across different urban contexts. Study participants were 79 adolescents with asthma who lived in Delhi, India and were recruited to the Delhi Air Pollution and Health Effects (DAPHNE) study. Participants were monitored continuously for exposure to PM_2.5 (particulate matter with an aerodynamic diameter of less than 2.5 μm) for 48 h. We isolated normal day-to-day walking journeys (n = 199) from the personal monitoring dataset and assessed the relationship between greenspace and personal PM_2.5 using different spatial scales of the mean Normalised Difference Vegetation Index (NDVI), mean tree cover (TC), and proportion of surrounding green land use (GLU) and parks or forests (PF). The journeys had a mean duration of 12.7 (range 5, 53) min and mean PM_2.5 personal exposure of 133.9 (standard deviation = 114.8) μg/m³. The within-trip analysis showed weak inverse associations between greenspace markers and PM_2.5 concentrations only in the spring/summer/monsoon season, with statistically significant associations for TC at the 25 and 50 m buffers in adjusted models. Between-trip analysis also indicated inverse associations for NDVI and TC, but suggested positive associations for GLU and PF in the spring/summer/monsoon season; no overall patterns of association were evident in the autumn/winter season. Associations between greenspace and personal PM_2.5 during walking trips in Delhi varied across metrics, spatial scales, and season, but were most consistent for TC. These mixed findings may partly relate to journeys being dominated by walking along roads and small effects on PM_2.5 of small pockets of greenspace. Larger areas of greenspace may, however, give rise to observable spatial effects on PM_2.5, which vary by season.

How vegetation cover characteristics response to the spread of Prosopis juliflora: a time-series remote sensing analysis in southern Iran

Plant invasion is recognized as the second most severe threat to biodiversity, following habitat loss. As one of the world's worst invasive alien plant species, Prosopis juliflora (Mesquite) has severely affected the majority of the Earth's dry ecosystems. Hence, this study attempted to identify the distribution, dominance, and changes in the vegetation characteristics of Mesquite-invaded regions along a series of coastal ecosystems in Southern Iran. Mesquite and other tree/shrub types were successfully classified using a temporarily-median-filtered Landsat 8-OLI image with acceptable kappa coefficient and overall accuracy values of 80.66 and 84.75, respectively. The multi-resolution segmentation was used to divide the region into spectrally homogenous parcels, then calculating the percentage cover (dominance) of Mesquite relative to other tree/shrub types. Analysis of MODIS NDVI products in highly invaded parcels showed a steady increase in NDVI values from 0.27 to 0.53 during 2000-2020 with a significant difference (z = -3.12, 0.183, sig ≤ .05, 2-tailed) from that of the low-invaded regions whose NDVI values oscillated constantly in a range between 0.15 and 0.28. Mesquite distribution also showed a local invasion pattern from areas with a steady or saturated status to neighboring parcels. In regions susceptible to Mesquite invasion, constant investigation of uncommon changes in NDVI whose vegetation characteristics differ significantly from that expected in poor dry vegetation covers of southern Iran can be considered as a conservation tool to identify and manage areas with early Mesquite establishment.

Neighborhood greenspace and cardiometabolic risk factors: Cross-sectional and longitudinal analysis in ELSA-Brasil participants

Greater neighborhood greenspace has been associated with better cardiometabolic risk factors, especially in high-income countries. This cross-sectional and longitudinal study assessed this association in approximately 2000 participants of the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil) residing in Belo Horizonte, a large Brazilian capital city. Neighborhood greenspace was studied through the Normalized Difference Vegetation Index (NDVI) and two additional types, percentages of tree cover and herbaceous cover. Multivariable logistic regression models estimated the cross-sectional and longitudinal associations of neighborhood greenspace with three metabolic factors - (i) obesity, (ii) abdominal obesity, and (iii) low HDL-cholesterol - after adjustment for individual sociodemographic factors and neighborhood average household income per capita. Cross-sectional results showed that higher neighborhood greenspace was associated with lower odds of obesity, abdominal obesity and low HDL-c. However, neighborhood greenspace was not associated with the incidence of any of these risk factors. The percentage of tree cover seemed to contribute more to the associations found with NDVI than the percentage of herbaceous cover. The results support the evidence that increased neighborhood greenspace contributes to maintain a better cardiometabolic health.

Associations between ultraviolet radiation, tree cover and adolescent sunburns

Background

Sunburn is the strongest risk factor for melanoma and non-melanoma skin cancers. Adolescent sunburns are related to higher risk of developing melanoma later in life. Little is known about the association of sunburns and shade, particularly tree cover, around adolescent homes and schools. This linkage study assessed associations of adolescent self-reported sunburns with ambient ultraviolet radiation (UV) and tree cover.

Methods

We analyzed a U.S. national sample of parent–child dyads (n = 1333) from the 2014 Family Life, Activity, Sun, Health, and Eating (FLASHE) study conducted by the National Cancer Institute. The outcome was adolescent sunburns reported for the previous 12 months. GIS buffers around geocoded home and school addresses were used to summarize UV and tree cover. A sensitivity analysis assessed different UV measures and tree cover buffer distances. Logistic regression models estimated the adjusted odds of any sunburns for five models: (1) no environmental variables; (2) spatial variables of latitude and longitude; (3) UV; (4) tree cover; and, (5) a combined model with UV and tree cover. Covariates included common sunburn-related items such as sun protective behaviors, socio-demographics, and latitude. Model residuals were assessed for spatial dependency and clustering.

Results

Overall, 44% of adolescents reported any sunburns in the previous 12 months. For the bivariate associations, lower categories of UV were associated with any reported sunburns (p-trend = 0.002). Home tree cover was not associated with any reported sunburns (p-trend = 0.08), whereas schools with lower categories of tree cover were associated with sunburns (p-trend = 0.008). The adjusted odds of any sunburns by UV tertiles, as a linear tread, was 0.89 (0.76–1.05) (p = 0.17); school tree cover was: 0.91 (0.78–1.07) (p = 0.25). Neither UV nor tree cover, in a combined model, were significant. Sensitivity analyses resulted in the optimal buffer size of 200 m for summarizing tree cover. Spatial dependence of residuals was not significant and clustering was significant for about 6% or less of the sample in each model.

Conclusions

We did not find significant relationships between UV or tree cover and adolescent sunburns, when adjusted by sunburn-related covariates. Better contextual data about where sunburns occurred is needed to identify environmental correlates of sunburn.

Crop proximity index for monitoring of peri-urban land use in agro-industrial crop regions

The agro-industrial production of genetically modified organisms uses great amounts of pesticides, close to cities, which generates growing concern due to the numerous evidence of their negative effects on health and the environment. In a context of the lack, or inaccessibility, of official data on crop dynamics and pesticide use, environmental indicators using satellite data are needed for the proper monitoring of peri-urban areas. The objective of this research is to make a crop proximity index using satellite information to assess and monitor peri-urban agro-industrial activity. Twenty cities in Argentina and ten in the United States were selected. The CPI index is designed to evaluate a city and its peri-urban areas as a whole by taking account of the land uses and factors that can potentially influence the proximity to agro-industrial activity to the population living in those cities. Agriculture factor was weighted by proximity or remoteness using perimeter rings from the urban edge. All the necessary data for the calculation of the CPI index were obtained through the classification and processing of Sentinel 2 satellite images with software and the Google Earth Engine platform. The results show a worrying situation, 90% of cities in Argentina and 80% in the United States have a negative CPI. Most of the cities examined are extremely close to extensive areas of crops, that use a high amount of pesticides and which do not have the protection of trees or buffer zones.

Tree cover mapping based on Sentinel-2 images demonstrate high thematic accuracy in Europe

The spatial and temporal distribution of trees has a large impact on human health and the environment through contributions to important climate mechanisms as well as commercial, recreational and social activities in society. A range of tree mapping methodologies has been presented in the literature, but tree cover estimates still differ widely between the individual datasets, and comparisons of the thematic accuracy of the resulting tree maps are rather scarce. The Copernicus Sentinel-2 satellites, which were launched in 2015 and 2017, have a combination of high spatial and temporal resolution. Given that this is a new satellite, a substantial amount of research on development of tree mapping algorithms as well as accuracy assessment of said algorithms have to be done in the years to come. To contribute to this process, a tree map produced through unsupervised classification was created for six Sentinel-2 tiles. The agreement between the tree map and the corresponding national forest inventory, as a function of the band combination chosen, was analysed and the thematic accuracy was assessed for two out of the six tiles. The results show that the highest agreement between the present tree map and the national forest inventory was found for bands 2, 3, 6 and 12. The present tree map has a relative difference in tree cover between 8% and 79% compared to previous estimates, but results are characterised by large scatter. Lastly, it is shown that the overall thematic accuracy of the present map is up to 90%, with the user's accuracy ranging from 34.85% to 92.10%, and the producer's accuracy ranging from 23.80% to 97.60% for the various thematic classes. This demonstrates that tree maps with high thematic accuracy can be produced from Sentinel-2. In the future the thematic accuracy can be increased even more through the use of temporal averaging in the mapping procedure, which will enable an accurate estimate of the European tree cover.

Socio-economic factors and management regimes as drivers of tree cover change in Nepal

Despite the local and global importance of forests, deforestation is driven by various socio-economic and biophysical factors continues in many countries. In Nepal, in response to massive deforestation, the community forestry program has been implemented to reduce deforestation and support livelihoods. After four decades of its inception, the effectiveness of this program on forest cover change remains mostly unknown. This study analyses the spatial and temporal patterns of tree cover change along with a few socio-economic drivers of tree cover change to examine the effectiveness of the community forestry program for conserving forests or in reducing deforestation. We also investigate the socio-economic factors and policy responses as manifested through the community forestry program responsible for the tree cover change at the district level. The total tree cover area in the year 2000 in Nepal was ∼4,746,000 hectares, and our analysis reveals that between 2001 and 2016, Nepal has lost ∼46,000 ha and gained ∼12,200 ha of areas covered by trees with a substantial spatial and temporal variations. After accounting socio-economic drivers of forest cover change, our analysis showed that districts with the larger number of community forests had a minimum loss in tree cover, while districts with the higher proportion of vegetation covered by community forests had a maximum gain in tree cover. This indicates a positive contribution of the community forestry program to reducing deforestation and increasing tree cover.

Green to gray: Silicon Valley of India

Rapid growth, population concentration and the expansion of urban areas towards peri-urban regions have led to changes in urban structure and composition, and consequently changes in urban ecology. The purpose of this study is to estimate trees in the urban environment through quantification of vegetation cover using multi resolution spatial data supplemented with tree data acquired from field using pre-calibrated GPS. Optimal resolution for extracting trees was attained through fusion of multi resolution (spectral and spatial) data. Results highlight region with spatial extent of 741 sq. km with 9.5 million human population has about 1.48 million trees. Further, urban growth increment is expected to cover 95% of the landscape with paved surfaces by 2020 decreasing vegetation cover while severely affecting the local ecology and environment in addition to human survival.