Assessing the Contribution of Urban Atlantic Forest Fragments in Climate Regulation in Subtropical Landscapes

Assessing the Contribution of Urban Atlantic Forest Fragments in Climate Regulation in Subtropical Landscapes | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Assessing the Contribution of Urban Atlantic Forest Fragments in Climate Regulation in Subtropical Landscapes Mauricio Solera Rodrigues Silva, Mauricio Lamano Ferreira, Rafael Souza Faria, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7197264/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract This study investigates the role of urban forest fragments from the Atlantic Forest biome in regulating microclimatic conditions in subtropical regions. Temperature and humidity sensors were installed in three contrasting environments—forest interior, forest edge, and urban area. Data was collected continuously during both the rainy and dry seasons, enabling a detailed temporal and spatial comparison of climatic variables. Results revealed that urban areas consistently exhibited significantly higher temperatures and lower humidity compared to vegetated areas. During the rainy season, urban air temperature was 26.75% higher than in forest interiors, while relative humidity was 38.67% lower in urban zones. These findings underscore the critical role of vegetation in buffering heat and conserving atmospheric moisture. Forest interiors demonstrated high environmental stability, with less thermal variation and sustained soil moisture across seasons. In contrast, urban sites showed elevated surface temperatures, particularly at night, illustrating the intensity of the urban heat island effect. Forest edges displayed intermediate conditions, reflecting their transitional ecological character. Multivariate statistical analysis (MANOVA and PCA) confirmed significant differences among the environments and between seasons. Relative humidity and dew point emerged as the most influential variables in distinguishing microclimatic conditions. The data confirms the capacity of vegetation to reduce thermal extremes and promote local climatic balance. In the context of fragmented landscapes such as the Atlantic Forest, where public policies for conservation remain limited, preserving and restoring green areas is both environmentally and socially urgent. Vegetation not only mitigates climate impacts but also enhances urban resilience, particularly for vulnerable populations disproportionately affected by heat stress. This research provides empirical support for integrating ecological structures into urban planning. Forest fragments offer essential ecosystem services and should be recognized as strategic assets in climate adaptation and sustainable urban development. Urban green infrastructure Microclimate regulation Sustainable urban planning Forest ecosystem services Climate resilience Figures Figure 1 Figure 2 Figure 3 Introduction The global impacts of climate change are increasingly evident, manifesting through rising temperatures, extreme weather events, biodiversity loss, and escalating risks to human health and security (Abbass et al. 2022 ; Zhou et al. 2022 ). These impacts are systemic, influencing environmental, economic, energy, and equity dimensions simultaneously (Loucks 2021 ). While governments are striving to reduce anthropogenic drivers of climate change, it is clear that negative consequences will persist in the coming decades—particularly for vulnerable populations who bear the brunt of these transformations (Bollettino et al. 2020). Urbanization, when combined with global warming, accelerates surface temperature increases, contributing to ecosystem degradation and exacerbating public health risks (Bounoua et al. 2021 ; Zhou et al. 2022 ). Green spaces, however, have emerged as critical nature-based solutions to mitigate urban heat and adapt cities to climate change (Hidalgo García 2023 ; Lin et al. 2021 ). More than half of the global population now experiences urban climate conditions, and the role of green infrastructure is increasingly recognized as essential for promoting climate resilience and urban livability (Best et al. 2023 ; Lamano Ferreira et al. 2024 ). Nevertheless, most studies on urban cooling are concentrated in temperate regions, underscoring the need for further investigation in tropical environments—particularly during dry seasons. The concept of ecosystem services—despite its limited application in sustainability assessment—offers a compelling framework for linking biodiversity, ecosystem functioning, and human well-being. International sustainability agendas such as the Sustainable Development Goals (SDGs) emphasize the dual imperative of environmental conservation and improved quality of life (Geijzendorffer et al. 2017 ; Li et al. 2023 ). Within this context, climate regulation is a vital service provided by urban green spaces, whose function becomes increasingly important in the face changes of rapid urban growth. Socioecological systems are particularly vulnerable to climate change in regions where human and ecological processes are deeply interconnected. Resilience thinking calls for integrated approaches that address both environmental and societal components, particularly in landscapes undergoing rapid transformation (Viñals et al. 2023 ). In cities, green spaces such as urban forests, parks, and street trees are fundamental elements of this resilience. They help regulate microclimates, reduce heat stress, support mental and physical health, and enhance environmental justice—especially for marginalized urban populations (Bratman et al. 2019 ; Macharia and Kiage 2025 ). In developing countries, including Brazil, urban expansion is often poorly regulated, resulting in the degradation of protected areas and the loss of green infrastructure. Unplanned urban growth and informal land occupation threaten the ecological integrity of these areas, diminishing their ability to deliver essential ecosystem services such as climate regulation, biodiversity conservation, and improved air quality (Luiza Petroni et al. 2022 ). Brazil’s urbanization has significantly reduced its biocapacity due to inadequate land-use planning. Although policies such as the 2012 National Urban Mobility Policy aim to encourage sustainable transport, the lack of affordable central housing pushes populations toward peri-urban areas, increasing pressure on forests and agricultural lands while undermining sustainable mobility goals (Ahmed et al. 2022 ). Among the most vulnerable ecosystems in Brazil is the Atlantic Forest—an emblematic biodiversity hotspot under severe threat from climate change and urban-industrial expansion. Today, only 11.6% of its original vegetation remains, fragmented and ecologically compromised. This fragility is particularly alarming because over 60% of Brazil’s population resides within the Atlantic Forest’s boundaries, exposing both urban and rural communities to socioenvironmental risks linked to ecosystem degradation (Scarano and Ceotto 2015 ; Sezerino and Tiepolo 2024 ). Urban green areas in Brazil are highly heterogeneous, ranging from street trees and public parks to forest remnants and conservation units. Each of these plays a distinct role in mitigating climate impacts and maintaining ecological functions. Strengthening these spaces is essential for enhancing their capacity to deliver ecosystem services and reducing the vulnerability of urban populations to climate extremes (kallett et al. 2024). This study focuses on the Mata de Santa Genebra, a relevant forest remnant in the municipality of Campinas, São Paulo, located within the Atlantic Forest biome. By monitoring microclimatic variables (air and soil temperature and humidity) across three different environments—forest interior, forest edge, and adjacent urban area—this research aims to assess the forest's contribution to local climate regulation. Given the increasing vulnerability of socioecological systems to climate change, especially in critical regions such as the Atlantic Forest, this study aims to underscore the strategic importance of conserving urban forest remnants. This study hypothesizes that the Mata de Santa Genebra, as a remnant green space within an urbanized area, plays a significant role in regulating local climate, preserving biodiversity, and enhancing human well-being. It is expected that the results will reinforce the importance of integrating ecosystem services into public policies as a strategic foundation for promoting more equitable, resilient, and sustainable urban development. Material and Methods Study area The municipality of Campinas/SP-Brazil (Fig. 1 ) has a total area of 764.4 km2 divided into an urban perimeter of 419.12 km2 and a rural area of 377.28 km2, with an altitude of 680 metres above sea level. In the past five decades, the population residing in the Municipality of Campinas has more than tripled — rising from approximately 375,000 inhabitants to 1,223,237 — with around 99% currently living in urban areas (IBGE 2025). The municipality's drainage area is comprised of three major sub-basins (i) Atibaia/Jaguari, (ii) Quilombo and (iii) Capivari. The district of Barão Geraldo, where the ARIE (Area of Relevant Ecological Interest) Mata de Santa Genebra is located, is part of the Atibaia River basin (Brasil 2021). Using the Köeppen classification, the climate is of the Cwa type with a warm, rainy season (October/March) and a dry season (April/September). A pedological analysis of the forest's soil showed that around 80% of the soil is occupied by dark red latosol with a clayey texture (Brasil, 2021). The Mata de Santa Genebra, with an area of 241.55 hectares, is a forest fragment of natural vegetation, and in 1985 was declared an Area of Relevant Ecological Interest. According to the law establishing the National System of Nature Conservation Units of the Ministry of the Environment, the Mata de Santa Genebra exhibit extraordinary natural characteristics or harbours rare specimens of regional biota and represents an important instrument for the conservation of ecosystems and the sustainable use of natural resources. The vegetation of Mata de Santa Genebra is composed of forest fragments of three types (1) Semideciduous Seasonal Forest, a predominant formation in the Campinas region with the characteristic of losing its leaves in the dry periods, autumn and winter, (2) Paludosa Forest also known as Mata de Brejo. Its main characteristic is that the soil is permanently waterlogged and, finally, (3) Cerrado, which is almost extinct in the Campinas region and whose main characteristic is the presence of twisted branches, trunks with thick, rough bark and leaves that are also thick. Land use in the contact area with the forest is very varied, with rural, industrial and urban components causing enormous pressure on the Santa Genebra Forest. Instrumentation and Data collection In this study, three sites were chosen (Fig. 1 ) for the installation of air temperature and relative humidity sensors, as well as soil temperature and humidity in two different locations in the Santa Genebra Forest, as well as in an urbanised area within campus I of PUC-Campinas. The main characteristics of the monitored areas are: Point A - Interior of the forest (INT) was established inside the forest 10 m from the edge, in an area characterised by a high diversity of plant species. The soil was covered by a thick layer of leaf litter and was protected by the shade of the canopy, which was responsible for keeping the environment shaded and moist. Point B - Edge of the forest (BOR), located on the boundary between native vegetation and a plantation area. Unlike the previous one, the soil was exposed, with no significant vegetation cover, reflecting the transition between the natural ecosystem and human interventions, such as nearby planting activities. Point C - Urbanised area (URB) located on Campus I of PUC-Campinas. The area was concentrated on an access road to the car park, with a predominance of impermeable area and few patches of exposed soil. Nearby, a residential neighbourhood reinforced the urban character of the site. To continuously monitor soil moisture and temperature, the HOBO MX2307 data logger (Onset Computer Corporation, USA) was used. It features a high-frequency capacitive sensor (70 MHz) for volumetric water content (VWC), with a measurement range of 0.00 to 0.64 m 3 /m 3 , accuracy of ± 0.031 m 3 /m 3 , and resolution range of 0.001 m 3 /m 3 . Soil temperature was recorded using a stainless-stell tip sensor, with a range of -40ºC to 100ºC, accuracy of ± 0.2ºC (0–70ºC), and resolution of 0.004ºC. The device IP67-rated, supports Bluetooth Low energy communications and offers data logging intervals from 1 second to 18 hours. The HOBO MX2301A (Onset Computer Corporation, USA) was used to monitor air temperature and relative humidity in outdoor conditions. The device features internal sensors with a temperature range of -40C to 70ºC, accuracy of ± 0.2ºC (0–70ºC), and resolution of 0.02ºC. Relative humidity was measured from 0–100% with ± 2.5% accuracy (10%-90%) and 0.001% resolution. Data were at user-defied intervals (1s to 18 h), with internal memory for ~ 63,000 readings. The logger is IP67-rated, supports Bluetooth low energy communications. At each collection point, a set of sensors was installed to monitor air temperature and humidity and soil temperature and humidity. The air sensors were positioned 2 metres above the ground, a strategy to minimise direct interference from the surface. The soil sensors were inserted perpendicular to the soil surface at a depth of 5.4 cm in order to capture surface humidity and temperature. To ensure that the data was representative, the collection period was defined as 15 days during the rainy season (summer) and 15 days during the dry season (winter). The data was taken every 30 minutes. Data analysis In the first stage, a descriptive analysis was carried out using metrics such as mean, standard deviation and variance. These methods, as highlighted by Reis & Reis (2002), made it possible to identify central tendencies, dispersion and contrasts between sets of data, offering a solid basis for exploring underlying complexities. In addition, the Wilks' lambda test used in MANOVA was applied, which aims to verify the existence of significant differences between groups, a metric that makes it possible to test main effects and interactions, improving the interpretation of multivariate patterns (Liu 2016; Pontes 2005). To go beyond the initial descriptive analysis, a multivariate analysis was applied, which examines multiple variables simultaneously. In this context, Principal Component Analysis (PCA) proved to be particularly valuable by reducing the dimensionality of the data without significant loss of critical information, transforming the original variables into principal components (Hongyu et al. 2016; Varella 2008). Results Figure 2 shows the variation in climatic conditions (temperature and air/soil humidity) in the environments analysed (interior, edge and urban) during the rainy and dry seasons, in day and night periods. The data revealed a clear pattern: the urban area recorded the highest temperatures in all scenarios. During the day, peaks reached 35.11ºC (rainy) and 33.87ºC (dry), while at night, urban temperatures were 27.26ºC (rainy) and 25.19ºC (dry). In contrast, the interior of the forest and the edge of the forest maintained significantly lower temperatures. In the rainy season, the daytime averages were 27.70ºC (interior) and 27.93ºC (edge), with night-time drops to 23.94ºC and 23.74ºC, respectively. This thermal stability, especially in the vegetated areas, reinforces the capacity of the vegetation cover to absorb heat and regulate the microclimate, even during the dry season. During the daytime in the rainy season, the interior of the forest stood out for its higher and more stable relative humidity, reaching values of over 94.31 per cent. In the dry season, this index dropped to 80 per cent, maintaining more humid conditions than other environments. In contrast, the urban region recorded average humidity of 24.40 per cent, aggravated by the high temperatures. The edge of the forest occupied an intermediate position, reflecting the gradual transition between forest areas and the urban environment. At night, this pattern persisted. Inside the forest, relative humidity reached 96.32% in the rainy season and 77.04% in the dry season, confirming the vegetation's ability to retain moisture. In the urban area, the values were much lower with 63.09% in the rainy season and 34.06% in the dry season. During the morning, the soil temperature was higher in the urban environment, both in the rainy and dry seasons. The values reached 32.31ºC (rainy season) and 32.81ºC in the dry season, a direct result of the lower amount of vegetation cover and the predominance of impermeable surfaces. In contrast, the interior of the forest recorded milder temperatures, 25.08ºC in the rainy season and 22.45ºC in the dry season. This difference highlighted the vegetation's ability to reduce soil temperature by blocking direct solar radiation and maintaining its humidity. The edge of the forest, in turn, acted as a thermal transition zone, with intermediate values between the interior of the forest and the urban area. During the night, soil temperatures dropped in all the areas analysed, but the difference between them remained evident. Inside the forest, the ground temperature was 24.92ºC, while at the edge it was 21.55ºC, a result of the thermal protection offered by the vegetation. In the urban environment, temperatures remained high, especially in the rainy season with 28.44ºC, and 25.37ºC in the dry season. Soil moisture, both in the rainy and dry seasons, show that during the day, the interior of the forest had average moisture values of around 12% and moderate variability in the rainy season. The interior of the forest, in the dry season, recorded an average value of approximately 5% and low variability compared to the rainy season. The edge area in the rainy season had a humidity of approximately 16% and in the dry season it was around 8%. The variability of the data was higher in the rainy season than in the dry season. The urban area had an average soil moisture of 17% and 7% in the wet and dry seasons, respectively. The urban area in the rainy season showed greater data variability when compared to the dry season. During the night, in the rainy season, the inland area showed similar values to the daytime period, with an average of around 12 per cent in the rainy season and 5 per cent in the dry season. They also show little variability in the observed data. The edge area in the rainy season showed average values of 16 per cent, while in the dry season this value fell to 5 per cent. The urban area in the rainy season showed values of around 17%. The multivariate analysis obtained using the MANOVA test (Table 1 ) revealed statistically significant differences between the study areas (forest interior, forest edge and urban area) and between the seasons (rainy and dry), considering the day and night periods. The Wilks' Lambda statistic values were 0.00127 during the day and 0.01127 during the night. The F-statistic values, which were 62.22 and 29.06, respectively, for the day and night periods, reinforce the differences between the groups. Furthermore, the extremely low p(same) values (3.733E-105 in the daytime and 1.78E-66 in the evening) indicate that the probability of these differences being random is insignificant. Table 1 MANOVA multivariate analysis with Wiks'Lambda index for the day and night periods DAYTIME MANOVA NIGHTTIME MANOVA Wilk’s lambda: 0.00127 Wilk’s lambda: 0.01127 F: 62.22 F: 29.06 P (same): 3.733E-105 P (same): 1.78E-66 The principal component analysis (PCA) carried out on the data collected in different areas (forest interior, forest edge and urban) during the day and night revealed distinct patterns of climatic variation (Fig. 3 ). During the day, the dominant variable (PC1) was the relative humidity, which contributed to 48.33% of the observed variability. In PC2, the dominant variable was the air temperature with 42.04%. Both variables explain around 90.00% of the total variance observed in the data. During the night, in the rainy season, the inland area showed similar values to the daytime period, with an average of around 12 per cent in the rainy season and 5 per cent in the dry season. They also show little variability in the observed data. The edge area in the rainy season showed average values of 16 per cent, while in the dry season this value fell to 5 per cent. The urban area in the rainy season showed values of around 17%. Figure 3 show a clear environmental differentiation among the humid and dry forest interiors, forest edges, and urban areas. Samples from humid forest interiors clustered distinctly from those in urban and forest edges, indicating strong environmental gradients across the three sites. The first two principal components captured the variation driven largely by relative humidity, soil moisture, and dew point on one side, and air and soil temperature on the other. Forest interior, the most humid environments, was associated with higher relative humidity and soil moisture, whereas urban and forest edges exhibited higher air and soil temperatures. These patterns suggest that urbanization and forest degradation significantly alter local microclimatic conditions, particularly by reducing moisture availability and increasing thermal exposure. The consistent separation of groups across both plots also implies that these environmental distinctions persist across seasonal or temporal variations, reinforcing the robustness of the observed trends. Discussion Urban Transformation and Heat Islands: The Critical Role of Vegetation in the Thermal Regulation of Cities Climate change and accelerated urbanisation have significantly intensified the phenomenon of urban heat islands (UHIs), creating increasingly complex challenges for environmental sustainability and public health in urban areas worldwide. These heat islands result primarily from the transformation of natural landscapes into built environments dominated by impervious surfaces, reduced vegetation, and intensified greenhouse gas emissions. Particularly, the extensive combustion of fossil fuels has increased the concentration of heat-absorbing materials in cities, which, combined with the reduction of vegetation cover, exacerbates temperature elevations (Bachendorf 2019; Wang et al. 2018 ; Zinzi et al. 2020 ).. Urban centres frequently experience air temperatures surpassing 40°C during dry seasons. These extreme conditions disproportionately affect vulnerable populations, including older adults, individuals with chronic diseases, low-income families, and family farmers, who often lack the means and infrastructure to protect themselves from climate extremes (Leap et al. 2024 ; Namgyal et al. 2025 ). The intensification of heat and its socio-spatial distribution reveal stark inequalities in exposure, demonstrating that the most affected populations are frequently those least responsible for greenhouse gas emissions, thus reinforcing the concept of climate injustice (Palmeiro-Silva et al., 2023 ). Vulnerability to climate impacts is not merely a function of exposure to environmental risks, but also of limited access to resources, low levels of formal education, poor housing, and weak infrastructure. These factors collectively reduce the adaptive capacity of communities, making them more susceptible to the negative effects of environmental hazards (Macharia and Kiage 2025 ). In this context, access to information and the development of community-based strategies are critical to building resilience and fostering environmental justice. This disparity underscores the urgent need for inclusive urban policies that prioritise equity and access to nature-based solutions. Urban green infrastructure, especially forests, tree-lined streets, and parks, plays a vital role in climate adaptation strategies. Vegetated areas act as buffers that mitigate the effects of extreme heat by providing shade, promoting evapotranspiration, and enhancing local humidity (Zimmermann et al. 2024 ). The biophysical processes of plant transpiration and soil moisture evaporation absorb and dissipate heat, cooling the air and stabilising microclimates. Furthermore, green infrastructure contributes to carbon sequestration, biodiversity conservation, and the psychological well-being of urban residents (Ghavimi et al. 2025 ; Hu et al. 2023 ; Nowak 2022 ). Our study, conducted in the municipality of Campinas, in São Paulo State, Brazil, illustrate the critical role that vegetation plays in regulating urban temperatures. Field measurements revealed that forest fragments within the city maintained significantly lower air and soil temperatures and higher relative humidity compared to adjacent urbanised zones. During the dry season, daytime air temperatures in forest interiors averaged 27.7°C, while urban areas reached 35.1°C, highlighting a cooling differential of almost 8°C. Additionally, relative humidity in the forested areas exceeded 96% during the night, while in urbanised regions, it dropped to as low as 63% (Battista et al. 2023 ). Such data demonstrate that forest fragments exert a substantial influence on surrounding urban microclimates. Their cooling effects are not confined to their interiors but also extend beyond their edges (ex. up to 60 meters) mitigating thermal discomfort in adjacent built-up areas (Grilo et al. 2020). This finding agree with similar studies across diverse geographic contexts. In Rome, for example, urban pavements covered with grass reduced surface and adjacent temperatures significantly (Battista et al. 2023 ). In Beijing and Islamabad, heavily vegetated zones recorded surface temperature reductions of between 5°C and 7°C (Khan and Li, 2024 ). In Melbourne, the loss of urban greenery between 2001 and 2014 led to increases in both daytime and nocturnal temperatures by over 1°C (Mohammad Harmay et al. 2021 ). Also, urban expansion in Delhi from 1991 to 2018, accompanied by deforestation and the loss of water bodies, exacerbated UHI effects and spatial inequalities (Shahfahad et al. 2022 ). Analyses conducted using multivariate statistical methods, including MANOVA and Principal Component Analysis, in Campinas further confirmed that relative humidity was the key variable differentiating forest and urban microclimates across both dry and rainy seasons. Night-time dew point also emerged as a significant variable, influencing thermal comfort and ecosystem functioning (Best et al., 2023 ). These climatic disparities are not only measurable but also experience-based, deeply impacting the daily lives of city dwellers. The relationship between green space and social vulnerability is complex and multifaceted. Urban areas with limited vegetation are frequently occupied by lower-income populations who lack political representation and access to quality infrastructure. These same communities often have less ability to relocate or access health services, increasing their sensitivity to heat-related health risks. This socio-environmental vulnerability results from a combination of biophysical, social, and institutional factors that intersect and compound one another (Palmeiro-Silva et al. 2023 ). In this context, inclusive green infrastructure is not simply a matter of environmental policy, it is a strategy for social equity. Urban planning must ensure that green spaces are equitably distributed, well-maintained, and accessible to all socioeconomic groups. This involves designing parks and forests with universal access features, providing public transportation links, ensuring safety, and fostering community participation in planning and management processes (Herman et al. 2018 ). Participatory governance and investment in underprivileged areas can help address historical spatial injustices and foster resilience. Moreover, the transformation towards sustainable cities involves the integration of green infrastructure with technological innovation and smart city principles. Cities can leverage data and digital platforms to monitor climate variables, model urban heat patterns, and guide interventions. Knowledge-based urban development—where research institutions, public authorities, and communities collaborate—can promote strategic land use and ecosystem service preservation (Michelam et al. 2020; Yigitcanlar and Kamruzzaman 2018 ). These strategies align with broader global initiatives, such as the United Nations Sustainable Development Goals and the European Green Deal, which advocate for nature-based solutions to promote urban resilience and human well-being (European Commission 2025 ; Geijzendorffer et al. 2017 ). The Brazilian context further illustrates the urgency of these measures. Brazil is one of the world's leading greenhouse gas emitters, and its urban regions are highly vulnerable to climate change. Land use changes, especially deforestation and ecosystem degradation, have been dramatic over the past five decades (Joly et al., 2014). As a result, there is an increasing need to adopt policies that not only mitigate emissions but also adapt to inevitable climate impacts. Enhancing green infrastructure in cities represents a low-cost, high-benefit approach that directly addresses both environmental and social vulnerabilities (Artaxo 2022 ). To build more resilient cities, public policies must integrate environmental and social dimensions through cross-sectoral coordination. This includes prioritising investments in green areas within underserved communities, promoting interdepartmental collaboration between housing, transport, health, and environmental agencies, and encouraging public-private partnerships for sustainable development. Climate adaptation strategies must also recognise and value local knowledge, empowering communities to participate in the design and implementation of green infrastructure (Leap et al., 2024 ). Future Research Challenges in Urban Heat and Climate response As urban heat islands intensify under global warming and accelerated urbanization, future research must grapple with the unequal burdens these environmental shifts impose. Beyond technical diagnostics, the challenge now lies in understanding the deeper social, spatial, and political mechanisms that shape vulnerability. Particularly in the Global South, where data scarcity intersects with structural inequalities, research must move toward place-based, interdisciplinary approaches that address both climatic and social injustices. One urgent frontier is understanding how microclimatic variation within cities exacerbates disparities in health and well-being. While studies such as those by (Wang et al. ( 2018 ) and Zinzi et al. ( 2020 ) have shown the role of impervious surfaces and fossil fuel use in increasing urban temperatures, less is known about how these factors interact with local socioeconomic and infrastructural conditions to produce differential exposure. High-resolution studies must explore how informal settlements, often excluded from planning frameworks, endure disproportionate thermal stress due to lack of vegetation and poor housing. The relationship between socio-demographic vulnerability and adaptive capacity is another critical theme. Groups with limited access to education, healthcare, or secure housing, that often intersect with race, age, and income, face significant barriers to responding to climatic threats. Leap et al. ( 2024 ) emphasize that wealthier populations, despite contributing more to emissions, are less exposed to their consequences. Future research must interrogate this injustice and develop metrics that capture the dynamic nature of vulnerability, including how communities cope, adapt, or fall through the cracks. Yet green infrastructure, while often proposed as a mitigation solution, can trigger unintended consequences such as green gentrification. Research should critically examine how adaptation strategies are governed, who benefits, and who is left behind (Herman et al. 2018 ). Finally, robust, transdisciplinary collaborations are essential. The integration of geospatial technologies with community-led research holds promise for more inclusive knowledge production. Studies like those of Palmeiro-Silva et al. ( 2023 ) suggest frameworks that evaluate exposure, sensitivity, and adaptive capacity—yet these must be tailored to local realities through participatory processes. Only by bridging scientific insight and social equity can future research support policies that build urban resilience and climate justice. Conclusion The results of this study clearly highlight the impact of urban transformation on local microclimatic conditions. Urban areas, characterized by extensive impervious surfaces and minimal vegetation, consistently recorded the highest air and soil temperatures and the lowest relative humidity, both during daytime and nighttime, across rainy and dry seasons. Conversely, forested environments, particularly forest interiors, maintained cooler and more humid conditions, underscoring the critical role of vegetation in buffering thermal extremes and regulating the microclimate. Multivariate statistical analyses confirmed these patterns, revealing statistically significant differences between forest interior, forest edge, and urban areas. Relative humidity emerged as the most influential variable in distinguishing microclimatic conditions across environments, followed by air temperature, soil temperature and moisture, and dew point. These findings highlight the capacity of vegetated areas not only to mitigate heat but also to enhance moisture retention, promoting thermal comfort and urban climate resilience. The persistence of urban heat islands, especially during nighttime, and the unequal exposure to climate-related stressors emphasize the need for inclusive, nature-based urban policies. When equitably distributed and maintained, urban green infrastructure plays a pivotal role in climate adaptation, environmental justice, and public health by reducing heat-related risks and improving overall livability. In this context, conserving and restoring green areas should be a policy priority, particularly in municipalities within the Atlantic Forest biome, where forest fragmentation remains high and public environmental initiatives are limited. Vegetated areas directly contribute to population well-being by creating healthier urban environments and mitigating the effects of extreme weather events such as heatwaves. This research confirms that integrating green areas into urban planning is not an option but a pressing necessity. The data presented provides technical support for concrete actions, including the establishment of thermal buffer zones and the reforestation of degraded areas. The climatic regulation offered by ecosystems such as the Mata de Santa Genebra represents an often invisible yet essential ecological service. Its protection must guide municipal and regional decision-making to ensure both present well-being and the preservation of environmental heritage for future generations. Declarations Ethics statement All fieldwork was approved by local governing entities. Conflict of interest The authors declare no competing interests. Funding This research was funded by the Coordination for the Improvement of Higher Education Personnel (CAPES) under Finance Code 001 and grant number 88887.691909/2022-00 - CAPES - PDPG-POSDOC and was funded by Fundação de Amparo a Pesquisa do Estado de São Paulo FAPESP, (grant number 22/05062-3). Author Contribution Author Contributions: Conceptualization, Regina Márcia Longo. and Mauricio Solera Rodrigues da Silva Methodology, Mauricio Solera Rodrigues da Silva; Validation, Regina Márcia Longo, Mauricio Solera Rodrigues da Silva, Adélia Nobre Nunes, and Rafael Souza de Faria; Investigation, Mauricio Solera Rodrigues da Silva; Data curation, Mauricio Solera Rodrigues da Silva and Mauricio Lamano Ferreira; Statistical analysis, Mauricio Solera Rodrigues da Silva, Mauricio Lamano Ferreira, and , Admilson Irio Ribeiro; Writing—original draft preparation, Mauricio Solera Rodrigues da Silva; Writing—review and editing, Regina Márcia Longo, Adélia Nobre Nunes, Rafael Souza de Faria, and Admilson Irio Ribeiro; Project administration, Regina Márcia Longo; Funding acquisition, Regina Márcia Longo. All authors have read and agreed to the published version of the manuscript.DeclarationsEthics statement All fieldwork was approved by local governing entities.Conflict of interest The authors declare no competing interests. Acknowledgements We thank the Mata de Santa Genebra and the ontifical Catholic University of Campinas for providing the necessary infrastrucuture to carry out this study. References Abbass K, Qasim MZ, Song H, Murshed, M, Mahmood H, & Younis I (2022) A review of the global climate change impacts, adaptation, and sustainable mitigation measures. Environmental Science and Pollution Research, 29(28):42539–42559. https://doi.org/10.1007/s11356-022-19718-6 Ahmed Z, Le HP, Shahzad SJH (2022) Toward environmental sustainability: how do urbanization, economic growth, and industrialization affect biocapacity in Brazil? Environment, Development and Sustainability 24(10):11676–11696. https://doi.org/10.1007/s10668-021-01915-x Artaxo P. 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Landscape and Urban Planning, 223:104404. https://doi.org/10.1016/j.landurbplan.2022.104404 Macharia CW, and Kiage L (2025) Examining the nexus of social vulnerability, land cover dynamics, and heat exposure in Reno, Nevada, USA. Remote Sensing Applications: Society and Environment, 37:101400. https://doi.org/10.1016/j.rsase.2024.101400 Michela, LD, Cortese TTP, Yigitcanlar T and Vils L (2020) Knowledge-based urban development as a strategy to promote smart and sustainable cities. In Revista de Gestao Ambiental e Sustentabilidade 9(1). Universidade Nove de Julho-UNINOVE. https://doi.org/10.5585/geas.v9i1.18740 Mohammad Harmay NS, Kim D and Choi M (2021) Urban Heat Island associated with Land Use/Land Cover and climate variations in Melbourne, Australia. Sustainable Cities and Society, 69:102861. https://doi.org/10.1016/j.scs.2021.102861 Namgyal P, Sarkar S and Kumar R (2025) Vulnerability assessment of rural households to climate change using livelihood vulnerability framework approach in the trans-Himalayan region of Ladakh, India. Anthropocene, 49:100467. https://doi.org/10.1016/j.ancene.2025.100467 Nowak DJ (2022) Regulating Ecosystem Services – Forests and Climate Regulation. In Imperiled: The Encyclopedia of Conservation (pp. 98–101). Elsevier. https://doi.org/10.1016/B978-0-12-821139-7.00193-8 Palmeiro-Silva YK, Lescano AG, Flore, EC, Astorga EY, Rojas L, Chavez MG, Mora-Rivera W and Hartinger SM (2023) Identifying gaps on health impacts, exposures, and vulnerabilities to climate change on human health and wellbeing in South America: a scoping review. The Lancet Regional Health - Americas, 26: 100580. https://doi.org/10.1016/j.lana.2023.100580 Scarano FR and Ceotto P (2015) Brazilian Atlantic forest: impact, vulnerability, and adaptation to climate change. Biodiversity and Conservation, 24(9):2319–2331. https://doi.org/10.1007/s10531-015-0972-y Sezerino F de S and Tiepolo LM (2024) Integrated indicators for the analysis of vulnerability in a socio-ecological system of the Atlantic Forest in southern Brazil. Environmental Development, 49:100962. https://doi.org/10.1016/j.envdev.2023.100962 Shahfahad, Naikoo MW, Towfiqul Islam ARMd, Mallick J and Rahman A (2022) Land use/land cover change and its impact on surface urban heat island and urban thermal comfort in a metropolitan city. Urban Climate, 41:101052. https://doi.org/10.1016/j.uclim.2021.101052 Viñals E, Maneja R, Rufí-Salís M, Martí M and Puy N (2023) Reviewing social-ecological resilience for agroforestry systems under climate change conditions. Science of The Total Environment, 869:161763. https://doi.org/10.1016/j.scitotenv.2023.161763 Wang W, Wang H, Xiao L, He X, Zhou W, Wang Q and Wei C (2018) Microclimate regulating functions of urban forests in Changchun City (north-east China) and their associations with different factors. IForest - Biogeosciences and Forestry, 11(1):140–147. https://doi.org/10.3832/ifor2466-010 Yigitcanlar T and Kamruzzaman M (2018) Does smart city policy lead to sustainability of cities? Land Use Policy, 73:49–58. https://doi.org/10.1016/j.landusepol.2018.01.034 Zhou D, Xiao J, Frolking S, Zhang L and Zhou G. (2022) Urbanization Contributes Little to Global Warming but Substantially Intensifies Local and Regional Land Surface Warming. Earth’s Future, 10(5). https://doi.org/10.1029/2021EF002401 Zimmermann B, Kruber S, Nendel C, Munack H and Hildmann, C (2024) Assessing the cooling potential of climate change adaptation measures in rural areas. Journal of Environmental Management, 366:121595. https://doi.org/10.1016/j.jenvman.2024.121595 Zinzi M, Agnoli S, Burattini C and Mattoni B (2020) On the thermal response of buildings under the synergic effect of heat waves and urban heat island. Solar Energy , 211 :1270–1282. https://doi.org/10.1016/j.solener.2020.10.050 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7197264","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":498612423,"identity":"d5610efe-adb9-4777-b51a-33cf84a53d6f","order_by":0,"name":"Mauricio Solera Rodrigues 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Paulo","correspondingAuthor":false,"prefix":"","firstName":"Mauricio","middleName":"Lamano","lastName":"Ferreira","suffix":""},{"id":498612425,"identity":"061045f8-e8d5-413a-88ef-594697c5fdcf","order_by":2,"name":"Rafael Souza Faria","email":"","orcid":"","institution":"Pontifícia Universidade Católica de Campinas","correspondingAuthor":false,"prefix":"","firstName":"Rafael","middleName":"Souza","lastName":"Faria","suffix":""},{"id":498612426,"identity":"34050f82-216b-4cc1-8353-6bc9f06094f1","order_by":3,"name":"Admilson Irio Ribeiro","email":"","orcid":"","institution":"São Paulo State University","correspondingAuthor":false,"prefix":"","firstName":"Admilson","middleName":"Irio","lastName":"Ribeiro","suffix":""},{"id":498612427,"identity":"48fcf063-3abc-4a8a-a7fe-9c56b0d83fb3","order_by":4,"name":"Regina Márcia Longo","email":"","orcid":"","institution":"Pontifícia Universidade Católica de Campinas","correspondingAuthor":false,"prefix":"","firstName":"Regina","middleName":"Márcia","lastName":"Longo","suffix":""},{"id":498612428,"identity":"75c6291e-59c1-4430-9769-99ec12586078","order_by":5,"name":"Adélia Nobre Nunes","email":"","orcid":"","institution":"University of Coimbra","correspondingAuthor":false,"prefix":"","firstName":"Adélia","middleName":"Nobre","lastName":"Nunes","suffix":""}],"badges":[],"createdAt":"2025-07-23 14:08:29","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7197264/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7197264/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":89062027,"identity":"6e277f87-476e-4f73-bc49-47d73e896f3f","added_by":"auto","created_at":"2025-08-14 09:37:35","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1322640,"visible":true,"origin":"","legend":"\u003cp\u003eA Map of locatins of Santa Genebra forest: (a) Brazil, (b) State of São Paulo (c) City Campinas and (d) Location of data collection areas: (1) Inside the forest, (1) Forest edge and (3) Urban área\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7197264/v1/0668b04070370bc910b57c5f.png"},{"id":89062029,"identity":"d3fb0ea4-952a-4296-b3f0-a3bd5164d1c3","added_by":"auto","created_at":"2025-08-14 09:37:35","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1140798,"visible":true,"origin":"","legend":"\u003cp\u003eVariation in air temperature and humidity, soil temperature and humidity in the rainy and dry seasons (day and night)\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7197264/v1/14d45ace000ce4480676ab4a.png"},{"id":89062030,"identity":"777f5574-c2d1-456e-812d-f6512d4dbab6","added_by":"auto","created_at":"2025-08-14 09:37:35","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":861334,"visible":true,"origin":"","legend":"\u003cp\u003ePrincipal component analysis (PCA) of three different areas and periods (a) day and (b) night and seasons (rainy and dry)\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7197264/v1/ac235a4f85866abf78591160.png"},{"id":90784129,"identity":"e35b5d3a-7889-47fb-a5fc-1ac84cfe4f79","added_by":"auto","created_at":"2025-09-08 06:32:41","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3577893,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7197264/v1/db628789-cafb-44ca-bcc5-1041f3cd88c1.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eAssessing the Contribution of Urban Atlantic Forest Fragments in Climate Regulation in Subtropical Landscapes\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe global impacts of climate change are increasingly evident, manifesting through rising temperatures, extreme weather events, biodiversity loss, and escalating risks to human health and security (Abbass et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Zhou et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). These impacts are systemic, influencing environmental, economic, energy, and equity dimensions simultaneously (Loucks \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). While governments are striving to reduce anthropogenic drivers of climate change, it is clear that negative consequences will persist in the coming decades\u0026mdash;particularly for vulnerable populations who bear the brunt of these transformations (Bollettino et al. 2020).\u003c/p\u003e\u003cp\u003eUrbanization, when combined with global warming, accelerates surface temperature increases, contributing to ecosystem degradation and exacerbating public health risks (Bounoua et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Zhou et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Green spaces, however, have emerged as critical nature-based solutions to mitigate urban heat and adapt cities to climate change (Hidalgo Garc\u0026iacute;a \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Lin et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). More than half of the global population now experiences urban climate conditions, and the role of green infrastructure is increasingly recognized as essential for promoting climate resilience and urban livability (Best et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Lamano Ferreira et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Nevertheless, most studies on urban cooling are concentrated in temperate regions, underscoring the need for further investigation in tropical environments\u0026mdash;particularly during dry seasons.\u003c/p\u003e\u003cp\u003eThe concept of ecosystem services\u0026mdash;despite its limited application in sustainability assessment\u0026mdash;offers a compelling framework for linking biodiversity, ecosystem functioning, and human well-being. International sustainability agendas such as the Sustainable Development Goals (SDGs) emphasize the dual imperative of environmental conservation and improved quality of life (Geijzendorffer et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Li et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Within this context, climate regulation is a vital service provided by urban green spaces, whose function becomes increasingly important in the face changes of rapid urban growth.\u003c/p\u003e\u003cp\u003eSocioecological systems are particularly vulnerable to climate change in regions where human and ecological processes are deeply interconnected. Resilience thinking calls for integrated approaches that address both environmental and societal components, particularly in landscapes undergoing rapid transformation (Vi\u0026ntilde;als et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). In cities, green spaces such as urban forests, parks, and street trees are fundamental elements of this resilience. They help regulate microclimates, reduce heat stress, support mental and physical health, and enhance environmental justice\u0026mdash;especially for marginalized urban populations (Bratman et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Macharia and Kiage \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn developing countries, including Brazil, urban expansion is often poorly regulated, resulting in the degradation of protected areas and the loss of green infrastructure. Unplanned urban growth and informal land occupation threaten the ecological integrity of these areas, diminishing their ability to deliver essential ecosystem services such as climate regulation, biodiversity conservation, and improved air quality (Luiza Petroni et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eBrazil\u0026rsquo;s urbanization has significantly reduced its biocapacity due to inadequate land-use planning. Although policies such as the 2012 National Urban Mobility Policy aim to encourage sustainable transport, the lack of affordable central housing pushes populations toward peri-urban areas, increasing pressure on forests and agricultural lands while undermining sustainable mobility goals (Ahmed et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAmong the most vulnerable ecosystems in Brazil is the Atlantic Forest\u0026mdash;an emblematic biodiversity hotspot under severe threat from climate change and urban-industrial expansion. Today, only 11.6% of its original vegetation remains, fragmented and ecologically compromised. This fragility is particularly alarming because over 60% of Brazil\u0026rsquo;s population resides within the Atlantic Forest\u0026rsquo;s boundaries, exposing both urban and rural communities to socioenvironmental risks linked to ecosystem degradation (Scarano and Ceotto \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Sezerino and Tiepolo \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eUrban green areas in Brazil are highly heterogeneous, ranging from street trees and public parks to forest remnants and conservation units. Each of these plays a distinct role in mitigating climate impacts and maintaining ecological functions. Strengthening these spaces is essential for enhancing their capacity to deliver ecosystem services and reducing the vulnerability of urban populations to climate extremes (kallett et al. 2024).\u003c/p\u003e\u003cp\u003eThis study focuses on the Mata de Santa Genebra, a relevant forest remnant in the municipality of Campinas, S\u0026atilde;o Paulo, located within the Atlantic Forest biome. By monitoring microclimatic variables (air and soil temperature and humidity) across three different environments\u0026mdash;forest interior, forest edge, and adjacent urban area\u0026mdash;this research aims to assess the forest's contribution to local climate regulation.\u003c/p\u003e\u003cp\u003eGiven the increasing vulnerability of socioecological systems to climate change, especially in critical regions such as the Atlantic Forest, this study aims to underscore the strategic importance of conserving urban forest remnants. This study hypothesizes that the Mata de Santa Genebra, as a remnant green space within an urbanized area, plays a significant role in regulating local climate, preserving biodiversity, and enhancing human well-being. It is expected that the results will reinforce the importance of integrating ecosystem services into public policies as a strategic foundation for promoting more equitable, resilient, and sustainable urban development.\u003c/p\u003e"},{"header":"Material and Methods","content":"\u003cp\u003e\u003cem\u003eStudy area\u003c/em\u003e\u003c/p\u003e\u003cp\u003eThe municipality of Campinas/SP-Brazil (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) has a total area of 764.4 km2 divided into an urban perimeter of 419.12 km2 and a rural area of 377.28 km2, with an altitude of 680 metres above sea level. In the past five decades, the population residing in the Municipality of Campinas has more than tripled \u0026mdash; rising from approximately 375,000 inhabitants to 1,223,237 \u0026mdash; with around 99% currently living in urban areas (IBGE 2025).\u003c/p\u003e\u003cp\u003eThe municipality's drainage area is comprised of three major sub-basins (i) Atibaia/Jaguari, (ii) Quilombo and (iii) Capivari. The district of Bar\u0026atilde;o Geraldo, where the ARIE (Area of Relevant Ecological Interest) Mata de Santa Genebra is located, is part of the Atibaia River basin (Brasil 2021). Using the K\u0026ouml;eppen classification, the climate is of the Cwa type with a warm, rainy season (October/March) and a dry season (April/September). A pedological analysis of the forest's soil showed that around 80% of the soil is occupied by dark red latosol with a clayey texture (Brasil, 2021). The Mata de Santa Genebra, with an area of 241.55 hectares, is a forest fragment of natural vegetation, and in 1985 was declared an Area of Relevant Ecological Interest. According to the law establishing the National System of Nature Conservation Units of the Ministry of the Environment, the Mata de Santa Genebra exhibit extraordinary natural characteristics or harbours rare specimens of regional biota and represents an important instrument for the conservation of ecosystems and the sustainable use of natural resources.\u003c/p\u003e\u003cp\u003eThe vegetation of Mata de Santa Genebra is composed of forest fragments of three types (1) Semideciduous Seasonal Forest, a predominant formation in the Campinas region with the characteristic of losing its leaves in the dry periods, autumn and winter, (2) Paludosa Forest also known as Mata de Brejo. Its main characteristic is that the soil is permanently waterlogged and, finally, (3) Cerrado, which is almost extinct in the Campinas region and whose main characteristic is the presence of twisted branches, trunks with thick, rough bark and leaves that are also thick. Land use in the contact area with the forest is very varied, with rural, industrial and urban components causing enormous pressure on the Santa Genebra Forest.\u003c/p\u003e\u003cp\u003e\u003cem\u003eInstrumentation and Data collection\u003c/em\u003e\u003c/p\u003e\u003cp\u003eIn this study, three sites were chosen (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) for the installation of air temperature and relative humidity sensors, as well as soil temperature and humidity in two different locations in the Santa Genebra Forest, as well as in an urbanised area within campus I of PUC-Campinas. The main characteristics of the monitored areas are:\u003c/p\u003e\u003cp\u003e\u003cb\u003ePoint A -\u003c/b\u003e Interior of the forest (INT) was established inside the forest 10 m from the edge, in an area characterised by a high diversity of plant species. The soil was covered by a thick layer of leaf litter and was protected by the shade of the canopy, which was responsible for keeping the environment shaded and moist.\u003c/p\u003e\u003cp\u003e\u003cb\u003ePoint B\u003c/b\u003e - Edge of the forest (BOR), located on the boundary between native vegetation and a plantation area. Unlike the previous one, the soil was exposed, with no significant vegetation cover, reflecting the transition between the natural ecosystem and human interventions, such as nearby planting activities.\u003c/p\u003e\u003cp\u003e\u003cb\u003ePoint C\u003c/b\u003e - Urbanised area (URB) located on Campus I of PUC-Campinas. The area was concentrated on an access road to the car park, with a predominance of impermeable area and few patches of exposed soil. Nearby, a residential neighbourhood reinforced the urban character of the site.\u003c/p\u003e\u003cp\u003eTo continuously monitor soil moisture and temperature, the HOBO MX2307 data logger (Onset Computer Corporation, USA) was used. It features a high-frequency capacitive sensor (70 MHz) for volumetric water content (VWC), with a measurement range of 0.00 to 0.64 m\u003csup\u003e3\u003c/sup\u003e/m\u003csup\u003e3\u003c/sup\u003e, accuracy of \u0026plusmn;\u0026thinsp;0.031 m\u003csup\u003e3\u003c/sup\u003e/m\u003csup\u003e3\u003c/sup\u003e, and resolution range of 0.001 m\u003csup\u003e3\u003c/sup\u003e/m\u003csup\u003e3\u003c/sup\u003e. Soil temperature was recorded using a stainless-stell tip sensor, with a range of -40\u0026ordm;C to 100\u0026ordm;C, accuracy of \u0026plusmn;\u0026thinsp;0.2\u0026ordm;C (0\u0026ndash;70\u0026ordm;C), and resolution of 0.004\u0026ordm;C. The device IP67-rated, supports Bluetooth Low energy communications and offers data logging intervals from 1 second to 18 hours.\u003c/p\u003e\u003cp\u003eThe HOBO MX2301A (Onset Computer Corporation, USA) was used to monitor air temperature and relative humidity in outdoor conditions. The device features internal sensors with a temperature range of -40C to 70\u0026ordm;C, accuracy of \u0026plusmn;\u0026thinsp;0.2\u0026ordm;C (0\u0026ndash;70\u0026ordm;C), and resolution of 0.02\u0026ordm;C. Relative humidity was measured from 0\u0026ndash;100% with \u0026plusmn;\u0026thinsp;2.5% accuracy (10%-90%) and 0.001% resolution. Data were at user-defied intervals (1s to 18 h), with internal memory for ~\u0026thinsp;63,000 readings. The logger is IP67-rated, supports Bluetooth low energy communications.\u003c/p\u003e\u003cp\u003eAt each collection point, a set of sensors was installed to monitor air temperature and humidity and soil temperature and humidity. The air sensors were positioned 2 metres above the ground, a strategy to minimise direct interference from the surface. The soil sensors were inserted perpendicular to the soil surface at a depth of 5.4 cm in order to capture surface humidity and temperature. To ensure that the data was representative, the collection period was defined as 15 days during the rainy season (summer) and 15 days during the dry season (winter). The data was taken every 30 minutes.\u003c/p\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eData analysis\u003c/h2\u003e\u003cp\u003eIn the first stage, a descriptive analysis was carried out using metrics such as mean, standard deviation and variance. These methods, as highlighted by Reis \u0026amp; Reis (2002), made it possible to identify central tendencies, dispersion and contrasts between sets of data, offering a solid basis for exploring underlying complexities. In addition, the Wilks' lambda test used in MANOVA was applied, which aims to verify the existence of significant differences between groups, a metric that makes it possible to test main effects and interactions, improving the interpretation of multivariate patterns (Liu 2016; Pontes 2005).\u003c/p\u003e\u003cp\u003eTo go beyond the initial descriptive analysis, a multivariate analysis was applied, which examines multiple variables simultaneously. In this context, Principal Component Analysis (PCA) proved to be particularly valuable by reducing the dimensionality of the data without significant loss of critical information, transforming the original variables into principal components (Hongyu et al. 2016; Varella 2008).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eFigure \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows the variation in climatic conditions (temperature and air/soil humidity) in the environments analysed (interior, edge and urban) during the rainy and dry seasons, in day and night periods. The data revealed a clear pattern: the urban area recorded the highest temperatures in all scenarios. During the day, peaks reached 35.11\u0026ordm;C (rainy) and 33.87\u0026ordm;C (dry), while at night, urban temperatures were 27.26\u0026ordm;C (rainy) and 25.19\u0026ordm;C (dry).\u003c/p\u003e\u003cp\u003eIn contrast, the interior of the forest and the edge of the forest maintained significantly lower temperatures. In the rainy season, the daytime averages were 27.70\u0026ordm;C (interior) and 27.93\u0026ordm;C (edge), with night-time drops to 23.94\u0026ordm;C and 23.74\u0026ordm;C, respectively. This thermal stability, especially in the vegetated areas, reinforces the capacity of the vegetation cover to absorb heat and regulate the microclimate, even during the dry season.\u003c/p\u003e\u003cp\u003eDuring the daytime in the rainy season, the interior of the forest stood out for its higher and more stable relative humidity, reaching values of over 94.31 per cent. In the dry season, this index dropped to 80 per cent, maintaining more humid conditions than other environments. In contrast, the urban region recorded average humidity of 24.40 per cent, aggravated by the high temperatures. The edge of the forest occupied an intermediate position, reflecting the gradual transition between forest areas and the urban environment.\u003c/p\u003e\u003cp\u003eAt night, this pattern persisted. Inside the forest, relative humidity reached 96.32% in the rainy season and 77.04% in the dry season, confirming the vegetation's ability to retain moisture. In the urban area, the values were much lower with 63.09% in the rainy season and 34.06% in the dry season.\u003c/p\u003e\u003cp\u003eDuring the morning, the soil temperature was higher in the urban environment, both in the rainy and dry seasons. The values reached 32.31\u0026ordm;C (rainy season) and 32.81\u0026ordm;C in the dry season, a direct result of the lower amount of vegetation cover and the predominance of impermeable surfaces.\u003c/p\u003e\u003cp\u003eIn contrast, the interior of the forest recorded milder temperatures, 25.08\u0026ordm;C in the rainy season and 22.45\u0026ordm;C in the dry season. This difference highlighted the vegetation's ability to reduce soil temperature by blocking direct solar radiation and maintaining its humidity. The edge of the forest, in turn, acted as a thermal transition zone, with intermediate values between the interior of the forest and the urban area.\u003c/p\u003e\u003cp\u003eDuring the night, soil temperatures dropped in all the areas analysed, but the difference between them remained evident. Inside the forest, the ground temperature was 24.92\u0026ordm;C, while at the edge it was 21.55\u0026ordm;C, a result of the thermal protection offered by the vegetation. In the urban environment, temperatures remained high, especially in the rainy season with 28.44\u0026ordm;C, and 25.37\u0026ordm;C in the dry season.\u003c/p\u003e\u003cp\u003eSoil moisture, both in the rainy and dry seasons, show that during the day, the interior of the forest had average moisture values of around 12% and moderate variability in the rainy season. The interior of the forest, in the dry season, recorded an average value of approximately 5% and low variability compared to the rainy season. The edge area in the rainy season had a humidity of approximately 16% and in the dry season it was around 8%. The variability of the data was higher in the rainy season than in the dry season. The urban area had an average soil moisture of 17% and 7% in the wet and dry seasons, respectively. The urban area in the rainy season showed greater data variability when compared to the dry season.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eDuring the night, in the rainy season, the inland area showed similar values to the daytime period, with an average of around 12 per cent in the rainy season and 5 per cent in the dry season. They also show little variability in the observed data. The edge area in the rainy season showed average values of 16 per cent, while in the dry season this value fell to 5 per cent. The urban area in the rainy season showed values of around 17%.\u003c/p\u003e\u003cp\u003eThe multivariate analysis obtained using the MANOVA test (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) revealed statistically significant differences between the study areas (forest interior, forest edge and urban area) and between the seasons (rainy and dry), considering the day and night periods. The Wilks' Lambda statistic values were 0.00127 during the day and 0.01127 during the night. The F-statistic values, which were 62.22 and 29.06, respectively, for the day and night periods, reinforce the differences between the groups. Furthermore, the extremely low p(same) values (3.733E-105 in the daytime and 1.78E-66 in the evening) indicate that the probability of these differences being random is insignificant.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eMANOVA multivariate analysis with Wiks'Lambda index for the day and night periods\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eDAYTIME MANOVA\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003eNIGHTTIME MANOVA\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWilk\u0026rsquo;s lambda:\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.00127\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eWilk\u0026rsquo;s lambda:\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.01127\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eF:\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e62.22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eF:\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e29.06\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eP (same):\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.733E-105\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eP (same):\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.78E-66\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThe principal component analysis (PCA) carried out on the data collected in different areas (forest interior, forest edge and urban) during the day and night revealed distinct patterns of climatic variation (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). During the day, the dominant variable (PC1) was the relative humidity, which contributed to 48.33% of the observed variability. In PC2, the dominant variable was the air temperature with 42.04%. Both variables explain around 90.00% of the total variance observed in the data.\u003c/p\u003e\u003cp\u003eDuring the night, in the rainy season, the inland area showed similar values to the daytime period, with an average of around 12 per cent in the rainy season and 5 per cent in the dry season. They also show little variability in the observed data. The edge area in the rainy season showed average values of 16 per cent, while in the dry season this value fell to 5 per cent. The urban area in the rainy season showed values of around 17%.\u003c/p\u003e\u003cp\u003eFigure \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e show a clear environmental differentiation among the humid and dry forest interiors, forest edges, and urban areas. Samples from humid forest interiors clustered distinctly from those in urban and forest edges, indicating strong environmental gradients across the three sites. The first two principal components captured the variation driven largely by relative humidity, soil moisture, and dew point on one side, and air and soil temperature on the other. Forest interior, the most humid environments, was associated with higher relative humidity and soil moisture, whereas urban and forest edges exhibited higher air and soil temperatures.\u003c/p\u003e\u003cp\u003eThese patterns suggest that urbanization and forest degradation significantly alter local microclimatic conditions, particularly by reducing moisture availability and increasing thermal exposure. The consistent separation of groups across both plots also implies that these environmental distinctions persist across seasonal or temporal variations, reinforcing the robustness of the observed trends.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003e\u003cem\u003eUrban Transformation and Heat Islands: The Critical Role of Vegetation in the Thermal Regulation of Cities\u003c/em\u003e\u003c/p\u003e\u003cp\u003eClimate change and accelerated urbanisation have significantly intensified the phenomenon of urban heat islands (UHIs), creating increasingly complex challenges for environmental sustainability and public health in urban areas worldwide. These heat islands result primarily from the transformation of natural landscapes into built environments dominated by impervious surfaces, reduced vegetation, and intensified greenhouse gas emissions. Particularly, the extensive combustion of fossil fuels has increased the concentration of heat-absorbing materials in cities, which, combined with the reduction of vegetation cover, exacerbates temperature elevations (Bachendorf 2019; Wang et al. \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Zinzi et al. \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2020\u003c/span\u003e)..\u003c/p\u003e\u003cp\u003eUrban centres frequently experience air temperatures surpassing 40\u0026deg;C during dry seasons. These extreme conditions disproportionately affect vulnerable populations, including older adults, individuals with chronic diseases, low-income families, and family farmers, who often lack the means and infrastructure to protect themselves from climate extremes (Leap et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Namgyal et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). The intensification of heat and its socio-spatial distribution reveal stark inequalities in exposure, demonstrating that the most affected populations are frequently those least responsible for greenhouse gas emissions, thus reinforcing the concept of climate injustice (Palmeiro-Silva et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eVulnerability to climate impacts is not merely a function of exposure to environmental risks, but also of limited access to resources, low levels of formal education, poor housing, and weak infrastructure. These factors collectively reduce the adaptive capacity of communities, making them more susceptible to the negative effects of environmental hazards (Macharia and Kiage \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). In this context, access to information and the development of community-based strategies are critical to building resilience and fostering environmental justice. This disparity underscores the urgent need for inclusive urban policies that prioritise equity and access to nature-based solutions.\u003c/p\u003e\u003cp\u003eUrban green infrastructure, especially forests, tree-lined streets, and parks, plays a vital role in climate adaptation strategies. Vegetated areas act as buffers that mitigate the effects of extreme heat by providing shade, promoting evapotranspiration, and enhancing local humidity (Zimmermann et al. \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The biophysical processes of plant transpiration and soil moisture evaporation absorb and dissipate heat, cooling the air and stabilising microclimates. Furthermore, green infrastructure contributes to carbon sequestration, biodiversity conservation, and the psychological well-being of urban residents (Ghavimi et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Hu et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Nowak \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eOur study, conducted in the municipality of Campinas, in S\u0026atilde;o Paulo State, Brazil, illustrate the critical role that vegetation plays in regulating urban temperatures. Field measurements revealed that forest fragments within the city maintained significantly lower air and soil temperatures and higher relative humidity compared to adjacent urbanised zones. During the dry season, daytime air temperatures in forest interiors averaged 27.7\u0026deg;C, while urban areas reached 35.1\u0026deg;C, highlighting a cooling differential of almost 8\u0026deg;C. Additionally, relative humidity in the forested areas exceeded 96% during the night, while in urbanised regions, it dropped to as low as 63% (Battista et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eSuch data demonstrate that forest fragments exert a substantial influence on surrounding urban microclimates. Their cooling effects are not confined to their interiors but also extend beyond their edges (ex. up to 60 meters) mitigating thermal discomfort in adjacent built-up areas (Grilo et al. 2020). This finding agree with similar studies across diverse geographic contexts. In Rome, for example, urban pavements covered with grass reduced surface and adjacent temperatures significantly (Battista et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). In Beijing and Islamabad, heavily vegetated zones recorded surface temperature reductions of between 5\u0026deg;C and 7\u0026deg;C (Khan and Li, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). In Melbourne, the loss of urban greenery between 2001 and 2014 led to increases in both daytime and nocturnal temperatures by over 1\u0026deg;C (Mohammad Harmay et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Also, urban expansion in Delhi from 1991 to 2018, accompanied by deforestation and the loss of water bodies, exacerbated UHI effects and spatial inequalities (Shahfahad et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAnalyses conducted using multivariate statistical methods, including MANOVA and Principal Component Analysis, in Campinas further confirmed that relative humidity was the key variable differentiating forest and urban microclimates across both dry and rainy seasons. Night-time dew point also emerged as a significant variable, influencing thermal comfort and ecosystem functioning (Best et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). These climatic disparities are not only measurable but also experience-based, deeply impacting the daily lives of city dwellers.\u003c/p\u003e\u003cp\u003eThe relationship between green space and social vulnerability is complex and multifaceted. Urban areas with limited vegetation are frequently occupied by lower-income populations who lack political representation and access to quality infrastructure. These same communities often have less ability to relocate or access health services, increasing their sensitivity to heat-related health risks. This socio-environmental vulnerability results from a combination of biophysical, social, and institutional factors that intersect and compound one another (Palmeiro-Silva et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn this context, inclusive green infrastructure is not simply a matter of environmental policy, it is a strategy for social equity. Urban planning must ensure that green spaces are equitably distributed, well-maintained, and accessible to all socioeconomic groups. This involves designing parks and forests with universal access features, providing public transportation links, ensuring safety, and fostering community participation in planning and management processes (Herman et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Participatory governance and investment in underprivileged areas can help address historical spatial injustices and foster resilience.\u003c/p\u003e\u003cp\u003eMoreover, the transformation towards sustainable cities involves the integration of green infrastructure with technological innovation and smart city principles. Cities can leverage data and digital platforms to monitor climate variables, model urban heat patterns, and guide interventions. Knowledge-based urban development\u0026mdash;where research institutions, public authorities, and communities collaborate\u0026mdash;can promote strategic land use and ecosystem service preservation (Michelam et al. 2020; Yigitcanlar and Kamruzzaman \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). These strategies align with broader global initiatives, such as the United Nations Sustainable Development Goals and the European Green Deal, which advocate for nature-based solutions to promote urban resilience and human well-being (European Commission \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Geijzendorffer et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe Brazilian context further illustrates the urgency of these measures. Brazil is one of the world's leading greenhouse gas emitters, and its urban regions are highly vulnerable to climate change. Land use changes, especially deforestation and ecosystem degradation, have been dramatic over the past five decades (Joly et al., 2014). As a result, there is an increasing need to adopt policies that not only mitigate emissions but also adapt to inevitable climate impacts. Enhancing green infrastructure in cities represents a low-cost, high-benefit approach that directly addresses both environmental and social vulnerabilities (Artaxo \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eTo build more resilient cities, public policies must integrate environmental and social dimensions through cross-sectoral coordination. This includes prioritising investments in green areas within underserved communities, promoting interdepartmental collaboration between housing, transport, health, and environmental agencies, and encouraging public-private partnerships for sustainable development. Climate adaptation strategies must also recognise and value local knowledge, empowering communities to participate in the design and implementation of green infrastructure (Leap et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cem\u003eFuture Research Challenges in Urban Heat and Climate response\u003c/em\u003e\u003c/p\u003e\u003cp\u003eAs urban heat islands intensify under global warming and accelerated urbanization, future research must grapple with the unequal burdens these environmental shifts impose. Beyond technical diagnostics, the challenge now lies in understanding the deeper social, spatial, and political mechanisms that shape vulnerability. Particularly in the Global South, where data scarcity intersects with structural inequalities, research must move toward place-based, interdisciplinary approaches that address both climatic and social injustices.\u003c/p\u003e\u003cp\u003eOne urgent frontier is understanding how microclimatic variation within cities exacerbates disparities in health and well-being. While studies such as those by (Wang et al. (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) and Zinzi et al. (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) have shown the role of impervious surfaces and fossil fuel use in increasing urban temperatures, less is known about how these factors interact with local socioeconomic and infrastructural conditions to produce differential exposure. High-resolution studies must explore how informal settlements, often excluded from planning frameworks, endure disproportionate thermal stress due to lack of vegetation and poor housing.\u003c/p\u003e\u003cp\u003eThe relationship between socio-demographic vulnerability and adaptive capacity is another critical theme. Groups with limited access to education, healthcare, or secure housing, that often intersect with race, age, and income, face significant barriers to responding to climatic threats. Leap et al. (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) emphasize that wealthier populations, despite contributing more to emissions, are less exposed to their consequences. Future research must interrogate this injustice and develop metrics that capture the dynamic nature of vulnerability, including how communities cope, adapt, or fall through the cracks.\u003c/p\u003e\u003cp\u003eYet green infrastructure, while often proposed as a mitigation solution, can trigger unintended consequences such as green gentrification. Research should critically examine how adaptation strategies are governed, who benefits, and who is left behind (Herman et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eFinally, robust, transdisciplinary collaborations are essential. The integration of geospatial technologies with community-led research holds promise for more inclusive knowledge production. Studies like those of Palmeiro-Silva et al. (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) suggest frameworks that evaluate exposure, sensitivity, and adaptive capacity\u0026mdash;yet these must be tailored to local realities through participatory processes. Only by bridging scientific insight and social equity can future research support policies that build urban resilience and climate justice.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe results of this study clearly highlight the impact of urban transformation on local microclimatic conditions. Urban areas, characterized by extensive impervious surfaces and minimal vegetation, consistently recorded the highest air and soil temperatures and the lowest relative humidity, both during daytime and nighttime, across rainy and dry seasons. Conversely, forested environments, particularly forest interiors, maintained cooler and more humid conditions, underscoring the critical role of vegetation in buffering thermal extremes and regulating the microclimate.\u003c/p\u003e\u003cp\u003eMultivariate statistical analyses confirmed these patterns, revealing statistically significant differences between forest interior, forest edge, and urban areas. Relative humidity emerged as the most influential variable in distinguishing microclimatic conditions across environments, followed by air temperature, soil temperature and moisture, and dew point. These findings highlight the capacity of vegetated areas not only to mitigate heat but also to enhance moisture retention, promoting thermal comfort and urban climate resilience.\u003c/p\u003e\u003cp\u003eThe persistence of urban heat islands, especially during nighttime, and the unequal exposure to climate-related stressors emphasize the need for inclusive, nature-based urban policies. When equitably distributed and maintained, urban green infrastructure plays a pivotal role in climate adaptation, environmental justice, and public health by reducing heat-related risks and improving overall livability.\u003c/p\u003e\u003cp\u003eIn this context, conserving and restoring green areas should be a policy priority, particularly in municipalities within the Atlantic Forest biome, where forest fragmentation remains high and public environmental initiatives are limited. Vegetated areas directly contribute to population well-being by creating healthier urban environments and mitigating the effects of extreme weather events such as heatwaves.\u003c/p\u003e\u003cp\u003eThis research confirms that integrating green areas into urban planning is not an option but a pressing necessity. The data presented provides technical support for concrete actions, including the establishment of thermal buffer zones and the reforestation of degraded areas. The climatic regulation offered by ecosystems such as the Mata de Santa Genebra represents an often invisible yet essential ecological service. Its protection must guide municipal and regional decision-making to ensure both present well-being and the preservation of environmental heritage for future generations.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cb\u003eEthics statement\u003c/b\u003e All fieldwork was approved by local governing entities.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConflict of interest\u003c/strong\u003e\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e\u003cp\u003eThis research was funded by the Coordination for the Improvement of Higher Education Personnel (CAPES) under Finance Code 001 and grant number 88887.691909/2022-00 - CAPES - PDPG-POSDOC and was funded by Funda\u0026ccedil;\u0026atilde;o de Amparo a Pesquisa do Estado de S\u0026atilde;o Paulo FAPESP, (grant number 22/05062-3).\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eAuthor Contributions: Conceptualization, Regina M\u0026aacute;rcia Longo. and Mauricio Solera Rodrigues da Silva Methodology, Mauricio Solera Rodrigues da Silva; Validation, Regina M\u0026aacute;rcia Longo, Mauricio Solera Rodrigues da Silva, Ad\u0026eacute;lia Nobre Nunes, and Rafael Souza de Faria; Investigation, Mauricio Solera Rodrigues da Silva; Data curation, Mauricio Solera Rodrigues da Silva and Mauricio Lamano Ferreira; Statistical analysis, Mauricio Solera Rodrigues da Silva, Mauricio Lamano Ferreira, and , Admilson Irio Ribeiro; Writing\u0026mdash;original draft preparation, Mauricio Solera Rodrigues da Silva; Writing\u0026mdash;review and editing, Regina M\u0026aacute;rcia Longo, Ad\u0026eacute;lia Nobre Nunes, Rafael Souza de Faria, and Admilson Irio Ribeiro; Project administration, Regina M\u0026aacute;rcia Longo; Funding acquisition, Regina M\u0026aacute;rcia Longo. All authors have read and agreed to the published version of the manuscript.DeclarationsEthics statement All fieldwork was approved by local governing entities.Conflict of interest The authors declare no competing interests.\u003c/p\u003e\u003ch2\u003eAcknowledgements\u003c/h2\u003e\u003cp\u003eWe thank the Mata de Santa Genebra and the ontifical Catholic University of Campinas for providing the necessary infrastrucuture to carry out this study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAbbass K, Qasim MZ, Song H, Murshed, M, Mahmood H, \u0026amp; Younis I (2022) A review of the global climate change impacts, adaptation, and sustainable mitigation measures. 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Journal of Environmental Management, 366:121595. https://doi.org/10.1016/j.jenvman.2024.121595\u003c/li\u003e\n\u003cli\u003eZinzi M, Agnoli S, Burattini C and Mattoni B (2020) On the thermal response of buildings under the synergic effect of heat waves and urban heat island. \u003cem\u003eSolar Energy\u003c/em\u003e, \u003cem\u003e211\u003c/em\u003e:1270\u0026ndash;1282. https://doi.org/10.1016/j.solener.2020.10.050\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Urban green infrastructure, Microclimate regulation, Sustainable urban planning, Forest ecosystem services, Climate resilience","lastPublishedDoi":"10.21203/rs.3.rs-7197264/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7197264/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis study investigates the role of urban forest fragments from the Atlantic Forest biome in regulating microclimatic conditions in subtropical regions. Temperature and humidity sensors were installed in three contrasting environments\u0026mdash;forest interior, forest edge, and urban area. Data was collected continuously during both the rainy and dry seasons, enabling a detailed temporal and spatial comparison of climatic variables. Results revealed that urban areas consistently exhibited significantly higher temperatures and lower humidity compared to vegetated areas. During the rainy season, urban air temperature was 26.75% higher than in forest interiors, while relative humidity was 38.67% lower in urban zones. These findings underscore the critical role of vegetation in buffering heat and conserving atmospheric moisture. Forest interiors demonstrated high environmental stability, with less thermal variation and sustained soil moisture across seasons. In contrast, urban sites showed elevated surface temperatures, particularly at night, illustrating the intensity of the urban heat island effect. Forest edges displayed intermediate conditions, reflecting their transitional ecological character. Multivariate statistical analysis (MANOVA and PCA) confirmed significant differences among the environments and between seasons. Relative humidity and dew point emerged as the most influential variables in distinguishing microclimatic conditions. The data confirms the capacity of vegetation to reduce thermal extremes and promote local climatic balance. In the context of fragmented landscapes such as the Atlantic Forest, where public policies for conservation remain limited, preserving and restoring green areas is both environmentally and socially urgent. Vegetation not only mitigates climate impacts but also enhances urban resilience, particularly for vulnerable populations disproportionately affected by heat stress. This research provides empirical support for integrating ecological structures into urban planning. Forest fragments offer essential ecosystem services and should be recognized as strategic assets in climate adaptation and sustainable urban development.\u003c/p\u003e","manuscriptTitle":"Assessing the Contribution of Urban Atlantic Forest Fragments in Climate Regulation in Subtropical Landscapes","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-14 09:37:30","doi":"10.21203/rs.3.rs-7197264/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"35b553e3-b572-4312-9387-a586e348216d","owner":[],"postedDate":"August 14th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-09-08T06:24:29+00:00","versionOfRecord":[],"versionCreatedAt":"2025-08-14 09:37:30","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7197264","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7197264","identity":"rs-7197264","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}