The study, led by Hellen Naigaga of Uganda Martyrs University together with Runyararo Jolyn Rukarwa of RUFORUM and Joseph Ssekandi of Uganda Martyrs University, surveyed 384 respondents across the Bulambuli and Kapchorwa districts of the Mount Elgon region. The research team deliberately restricted participation to individuals aged 40 and above who had lived in their villages for at least 20 years, ensuring that respondents possessed the accumulated observational experience on which local ecological knowledge depends. Using a multi-stage stratified sampling design that moved from districts through counties and sub-counties down to households, the researchers interviewed farmers alongside district environment officers and district agriculture officers, who served as key informants.

The findings are striking in their breadth. Fully 88 percent of respondents demonstrated familiarity with plant species used to anticipate weather changes, and nearly all of those asked about awareness of such species reported knowing them. Knowledge proved remarkably uniform across demographic lines: chi-square tests of independence found no statistically significant association between phenological knowledge and gender, marital status, or occupation. The researchers interpret this as evidence that botanical weather forecasting is deeply embedded across the community rather than confined to a particular social group, a pattern consistent with the idea that indigenous climate knowledge is socially shared because of its direct relevance to household food security.

The indicators themselves follow clear physiological logic. Leaf shedding in species such as Cordia africana, Erythrina abyssinica, Milicia excelsa, and Ficus species signals an impending dry season, reflecting the water stress that trees experience as moisture becomes scarce. The emergence of new leaves and buds marks the transition toward rainfall, prompting farmers to prepare their gardens. Flowering adds a further layer of information: blossoms on Mangifera indica and Coffea species announce the start of the rainy season, and farmers even use the abundance and quality of the flowers to gauge how intense the coming rains will be. Cordia africana was the most frequently cited predictor, mentioned by 71 percent of respondents, followed by Erythrina abyssinica at 64 percent and Coffea species at 28 percent.

To test whether these local forecasts hold up empirically, the researchers compared community-reported rainy and dry months with meteorological data drawn from the TerraClimate dataset. The convergence was substantial. Farmers identified January as the driest month, with 98.7 percent agreeing, and April as the rainiest, cited by 87 percent. Both local knowledge and meteorological records pointed to April, May, September, October, and November as the wettest months. The only divergence involved minimal rainfall of less than 50 millimeters in January and December, which the instruments detect but farmers disregard, since drizzles of that magnitude have no bearing on farming decisions.

A Pearson correlation analysis comparing locally identified dry-spell months with monthly temperature records, used as a proxy for atmospheric dryness, revealed a positive relationship, with a correlation coefficient of 0.183. Although the correlation is modest and not statistically significant, with temperature explaining only about 3.4 percent of the variability, the direction of the trend indicates that community perceptions of dry spells rise in tandem with observed heat stress. The regression model, y = 4.1011x – 70.393, reinforces this positive tendency. In practical terms, farmers’ seasonal judgments track real atmospheric conditions closely enough to suggest genuine predictive value, even if the relationship is looser than a one-to-one correspondence.

The influence of phenological forecasting on farm management is profound. Planting time is the decision most governed by tree signals, with 93 percent of farmers relying on phenological changes to determine when to sow. Garden management followed at 71 percent, while food storage and harvesting decisions were influenced at 51 and 45 percent respectively. Land preparation, at 17 percent, depends more on labor and resource availability than on botanical cues. Farmers reported that this well-timed planning translates into tangible gains: 55 percent credited phenology-based scheduling with enabling timely planting, weeding, manuring, and pest control that help escape disease cycles and maximize resource use, while 22 percent attributed higher yields to careful planning combined with the soil fertility benefits of decomposed leaf litter from the very trees they monitor.

Knowledge of these indicators travels through an intricate web of social channels. Clan meetings, evening gatherings, family assemblies, circumcision ceremonies, drinking spots, church congregations, NGO-led trainings, and agricultural extension initiatives all serve as conduits for weather information, with village saving groups acting as particularly active hubs. This dense communication network matters for adaptation policy, the authors argue, because it shows that climate information in rural communities flows through existing socio-cultural structures rather than formal channels, and any effort to deliver improved forecasts must work with these systems rather than around them.

The broader context gives the findings urgency. Respondents consistently reported that the timing and reliability of rainy seasons have shifted away from historically stable calendars, injecting uncertainty into farming schedules across the region. Mount Elgon, with its humid subtropical climate, mean annual temperature of roughly 23 degrees Celsius, and rainfall averaging around 1,500 millimeters, has been among the Ugandan regions most intensely affected by climate change impacts. In settings where access to meteorological forecasts is limited, phenological indicators function as an accessible early warning system, and similar plant-based forecasting traditions have been documented from Indonesia to Tanzania, where Erythrina abyssinica and Ficus species serve comparable roles.

The study’s conclusions point toward integration rather than replacement. The authors recommend that conservation strategies prioritize the key indicator species, recognizing their dual ecological and informational value, and that meteorological institutions formally incorporate local phenological indicators into localized forecasting services to improve relevance, timeliness, and accessibility for smallholder farmers. They also call for community-based training programs that strengthen farmers’ capacity to interpret phenological signals alongside scientific forecasts, support intergenerational knowledge transmission, and institutionalize participatory research frameworks involving farmers, scientists, and policymakers. In a warming world where seasonal predictability is eroding, the trees of Mount Elgon suggest that the most resilient forecast may be one written jointly by satellites and leaves.

Subject of Research: Indigenous plant-phenology knowledge for anticipating seasonal weather changes among smallholder farmers in Uganda's Mount Elgon region

Article Title: Integrating local plant-phenology knowledge into anticipating seasonal weather changes: evidence from smallholder farmers in Uganda’s Mount Elgon region (cross-sectional survey)

Article References: Naigaga, H., Rukarwa, R. J., & Ssekandi, J. (2026). Integrating local plant-phenology knowledge into anticipating seasonal weather changes: evidence from smallholder farmers in Uganda’s Mount Elgon region (cross-sectional survey). BMC Environmental Science, 3(1), Article 11. https://doi.org/10.1186/s44329-026-00052-y

Image Credits: AI Generated

DOI: 10.1186/s44329-026-00052-y

Keywords: plant phenology, indigenous knowledge, weather forecasting, smallholder farmers, Mount Elgon, Uganda, climate change adaptation, Cordia africana, Erythrina abyssinica, meteorological data, seasonal rainfall, agricultural decision-making

The scientific rationale behind the study begins with a fundamental measurement problem. Climate change adaptation, as defined by the Intergovernmental Panel on Climate Change, is the process of adjustment to actual or expected climate effects in order to moderate harm or exploit beneficial opportunities. Yet adaptation outcomes are inherently context dependent, varying with local priorities, values, and environmental conditions, which makes them notoriously difficult to define, measure, and compare across countries and sectors. No universal set of indicators has emerged to evaluate adaptation consistently. International climate governance has responded by pushing for measurable indicators through the Sustainable Development Goals and the Global Goal on Adaptation under the Paris Agreement, but these global frameworks provide broad directions rather than detailed, sector-specific metrics that can be directly applied within national institutional contexts. The new study tackles precisely this operationalization gap, using Thailand as its testing ground.

Thailand provides a particularly instructive case. The country faces a wide array of climate-related hazards, including flooding, heat stress, drought, and sea-level rise, risks that have been formally recognized in its National Adaptation Plan. The plan identifies impacts on water resources, urban systems, infrastructure, ecosystems, and vulnerable communities as key adaptation challenges requiring coordinated responses across sectors and administrative levels. Many Thai cities, especially those in low-lying river basins and coastal zones, are highly exposed to these hazards, while governance and planning systems have historically struggled to coordinate adaptation across different levels of administration. Vulnerability is also unevenly distributed: metropolitan areas, medium-sized cities, and smaller communities differ substantially in infrastructure capacity, governance arrangements, and socioeconomic conditions, meaning that climate risk does not fall equally across the settlement hierarchy.

Despite these policy commitments, the study identifies a critical weakness in Thailand’s National Adaptation Plan: it provides only broad strategic directions and does not specify systematic, sector-specific indicators for assessing adaptation outcomes at the community and household levels. Previous research has likewise noted that Thailand continues to lack operational indicators capable of translating adaptation policies into measurable outcomes. Existing monitoring frameworks, both in Thailand and internationally, tend to emphasize administrative outputs, such as plans and projects implemented, rather than whether those interventions actually reduce vulnerability and strengthen resilience within communities and households. This is the methodological gap the new framework is engineered to close.

The methodology is as notable as the framework itself. The study adopts a qualitative and conceptual research approach built on four iterative steps that move from global evidence to context-specific indicators. First, a comprehensive literature review drew on the Global Goal on Adaptation indicator framework, UNFCCC guidance, IPCC reports, and peer-reviewed studies on climate adaptation, urban resilience, disaster risk reduction, and adaptive social protection. Two GGA indicators anchored the work: increasing the resilience of infrastructure and human settlements to climate impacts to ensure continuous essential services, and reducing adverse effects of climate change on poverty eradication and livelihoods, particularly through adaptive social protection. The review also incorporated Sustainable Development Goal 11, which targets inclusive, safe, resilient, and sustainable cities, and Thailand’s National Adaptation Plan, which served as the primary national policy reference.

The second and third steps grounded the framework in Thailand’s administrative reality. Candidate indicators were mapped against the national policy context and assessed for institutional applicability and feasibility. To ensure institutional relevance, seven government agencies were purposively selected based on their statutory mandates under the Reorganization of Ministries, Sub Ministries, and Departments Act of 2002, spanning the Ministry of Interior and the Ministry of Social Development and Human Security. These included the Department of Public Works and Town & Country Planning, the Department of Community Development, the Department of Disaster Prevention and Mitigation, the Department of Social Development and Welfare, the National Housing Authority, and the Department of Women’s Affairs and Family Development. Semi-structured stakeholder consultation meetings were conducted with 38 agency representatives, followed by a refinement workshop with 11 representatives, providing cross-agency dialogue on institutional responsibilities, data availability, and implementation challenges. Consultation data were analyzed using a framework analysis approach, and candidate indicators were retained only if they satisfied four criteria: alignment with the GGA and the National Adaptation Plan, fit within statutory agency responsibilities, confirmed data availability or feasible collection, and suitability for routine reporting to the Department of Climate Change and Environment, which compiles Thailand’s adaptation progress reporting to international platforms. A final expert review involving 18 participants, including executives, technical staff, and external experts from sectors ranging from agriculture to public health, refined the framework iteratively.

The resulting framework operationalizes climate adaptation through five interrelated dimensions: urban planning, infrastructure quantity and quality, disaster preparedness and risk reduction mechanisms, social protection and resilience mechanisms, and quality of life and household resilience. The indicators span different stages of the adaptation results chain. Process indicators capture institutional arrangements and policy implementation, such as the number of comprehensive urban plans initiated and evaluated each fiscal year and the number of government buildings inspected under Bangkok’s Building Control Act. Output indicators measure immediate products of adaptation actions, including infrastructure and urban landscape improvement projects funded, urban plans updated with GIS data to support climate risk mapping, the volume of aquatic weeds removed from waterways to maintain flood conveyance capacity, flood prevention and mitigation projects, and the use of hydraulic low-carbon cement for durable, lower-carbon construction. Outcome indicators capture changes in adaptive capacity and living conditions, such as the percentage of flood prevention infrastructure meeting engineering standards, the percentage of the population receiving timely disaster warnings with a target of at least 95 percent, and the percentage of provinces with completed emergency response plans for floods, storms, and landslides.

What distinguishes the framework from conventional monitoring systems is its fifth dimension, which reaches directly into household life. Indicators track the percentage of households with secure housing tenure, durable housing, adequate environmental settings, and sufficient access to clean drinking water, as well as the percentage of households with savings of at least 100,000 baht, access to formal financial services, members possessing life and occupational skills, and preparedness for disaster response. Social protection coverage is measured through the percentage of low-income households receiving State Welfare Card benefits, overall social protection coverage, and the proportions of elderly people and people with disabilities receiving care from family, community, or institutions. A final output indicator counts housing units improved for vulnerable households, including those in informal settlements. Together these metrics reflect a conceptual argument at the heart of the study: adaptation capacity is not generated exclusively through external interventions but emerges through the interaction between institutional support and the resources, capabilities, and security conditions available to households. Public policies and infrastructure investments provide enabling conditions, while household-level capacities determine whether those interventions can effectively reduce vulnerability.

The discussion within the paper situates the framework within broader debates on adaptation measurement. Existing international approaches differ in emphasis: the GGA provides a global structure for tracking progress across countries but does not prescribe how broad objectives should be operationalized in specific sectors, while SDG 11 focuses on sustainable settlements within the wider development agenda, and conventional urban resilience indicator systems tend to prioritize urban capacities and governance preparedness over household-level vulnerability. The proposed framework instead operationalizes international adaptation priorities into sector-specific indicators explicitly aligned with institutional mandates, administrative responsibilities, and national monitoring systems. This governance-sensitive approach matters especially in developing countries, where adaptation monitoring systems are still evolving and responsibilities remain fragmented across sectors and agencies. In such contexts, indicator development is shaped not only by conceptual definitions of resilience but by the practical capacity of institutions to collect, interpret, and use adaptation-related information.

The framework is candid about its limits. Because it relies primarily on existing administrative data, which vary in availability, quality, and consistency across agencies, some dimensions of household resilience, including informal coping strategies, social networks, and community-based adaptive capacities, remain difficult to capture quantitatively. Weighting, aggregation, and empirical validation were beyond the study’s scope, meaning further work is needed before the framework can function as a composite adaptation index. Impact indicators, which would require long-term monitoring and robust evidence linking interventions to changes in climate-related risks and losses, are not yet systematically incorporated and represent an important direction for future refinement. The study also acknowledges that perspectives from ecology, economics, culture, and Indigenous knowledge systems could identify additional dimensions beyond its current scope. Still, as national adaptation priorities and monitoring requirements evolve, the framework provides the structural foundation on which outcome- and impact-based assessment can later be built, and it demonstrates how sector-specific indicator systems can serve as intermediate tools linking international commitments, such as the Global Goal on Adaptation, to measurable actions by national institutions, offering a model that other developing countries facing similar institutional fragmentation may adapt to their own governance contexts.

The study addresses a problem that is frequently obscured by citywide averages. A single temperature reading can suggest that an entire city is experiencing the same conditions, while residents in different neighborhoods may face dramatically different levels of heat exposure. Informal settlements often contain dense housing, limited tree cover, narrow pathways, extensive metal or concrete surfaces and inadequate ventilation. Homes may be built with materials that absorb solar radiation during the day and release heat slowly at night, preventing the body from recovering between consecutive hot days. In many communities, unreliable electricity, limited access to cooling and insufficient water infrastructure further increase exposure. These factors can transform an extreme-weather event into a prolonged physiological stress test.

Heat affects the human body through several interacting mechanisms. Under normal conditions, the body sheds excess heat through radiation, convection and evaporation, especially sweating. During a heatwave, high air temperatures reduce the efficiency of radiation and convection, while high humidity slows the evaporation of sweat. The result is a rising core temperature that can impair cardiovascular, renal and neurological function. The danger is particularly acute at night, when persistently warm indoor conditions interfere with sleep and prevent thermal recovery. Older adults, infants, people with chronic illnesses, outdoor workers and residents taking medications that alter hydration or cardiovascular responses may be especially vulnerable. The study’s focus on infrastructure recognizes that health outcomes are shaped not only by individual behavior, but also by the physical environments in which people live.

Urban infrastructure can influence heat exposure at multiple scales, from an individual dwelling to an entire neighborhood. Roofing materials, wall construction, window placement and ventilation determine how quickly heat enters and leaves a home. At the street level, pavement and unshaded surfaces can absorb solar energy and intensify the urban heat island effect, in which built-up areas become warmer than surrounding rural or less developed landscapes. Vegetation can cool the environment through shade and evapotranspiration, the process by which plants release water vapor into the atmosphere. Water access, drainage systems, sanitation and reliable electricity can also affect whether residents can cool themselves safely, remain hydrated and avoid secondary health threats during extreme weather. An infrastructure upgrade, therefore, is not a single intervention but a network of changes that may alter exposure, vulnerability and the ability to recover.

Prosdocimi, Klima and DeYoreo frame slum upgrading as a potential pathway to climate resilience rather than solely as a housing or economic-development policy. The distinction matters because adaptation measures can produce unequal outcomes if they ignore how neighborhoods actually function. A new road may improve emergency access but also replace permeable ground with heat-retaining pavement. A roof replacement may reduce indoor temperatures, while poorly planned construction could restrict airflow. Tree planting can provide shade, but only if species are suited to local conditions and maintenance is sustained. Electrification may allow households to use fans or cooling systems, yet it can also increase costs or place pressure on fragile power networks. Evaluating infrastructure through a health lens helps reveal these trade-offs before they are treated as evidence of resilience.

The technical challenge is connecting physical changes in the built environment to measurable health effects. Researchers studying heat risk commonly combine meteorological data with indicators such as air temperature, humidity, wind speed and radiant heat. Measures including the heat index, wet-bulb globe temperature and physiological heat-balance models can provide more realistic estimates of human stress than air temperature alone. Indoor conditions may require separate monitoring because walls, roofs and ventilation can produce temperatures that differ substantially from outdoor weather-station readings. Health analysis can then consider outcomes such as heat exhaustion, heatstroke, dehydration, cardiovascular strain, kidney stress, hospital admissions or excess mortality. By evaluating infrastructure in relation to these pathways, the study speaks to a growing field of climate-health research that treats the city itself as part of the exposure system.

The paper is also significant because informal settlements are not interchangeable. Their risks depend on local climate, topography, housing materials, population density, access to services and social networks. A community in a humid tropical region may face dangerous nighttime heat and limited evaporative cooling, while a dry-climate settlement may experience intense daytime solar exposure and severe water scarcity. Hillside neighborhoods may have different airflow patterns from settlements built in low-lying basins. Residents may develop local strategies—sharing water, opening communal spaces or checking on vulnerable neighbors—that reduce risk but are difficult to capture in conventional datasets. Any meaningful assessment of upgrading must therefore account for social capacity as well as concrete, asphalt and building envelopes.

The research arrives as cities and governments search for adaptation strategies that can be implemented before the next record-breaking summer. Large-scale cooling centers, heat-warning systems and emergency medical responses remain essential, but they are often activated only after dangerous conditions have already emerged. Infrastructure upgrades offer the possibility of reducing exposure in advance. Reflective or insulated roofs, improved ventilation, shaded public areas, permeable surfaces, expanded vegetation, dependable water supplies and better access to electricity could function as layers of protection. The most effective interventions may be those that deliver multiple benefits at once, improving thermal comfort while also reducing energy demand, supporting public health and strengthening everyday living conditions.

Yet upgrading carries a political risk: improvements intended to protect residents can trigger displacement. When infrastructure raises land values without guaranteeing secure tenure or affordable housing, existing communities may be pushed out and replaced by wealthier populations. Climate resilience can then become a mechanism of climate exclusion. A health-centered approach must ask not only whether a neighborhood becomes cooler, but also who remains able to live there, who receives the benefits and who bears the cost. The study’s emphasis on slum upgrading therefore connects heat adaptation to environmental justice. Protecting residents from extreme heat requires investment in physical systems, but it also requires policies that preserve community stability and ensure that resilience is not measured solely through property values or redevelopment.

The broader message is that heatwaves expose the hidden architecture of inequality. Climate change raises the temperature hazard, but infrastructure determines how much of that hazard reaches the body. By evaluating the relationship between urban upgrades and health during heatwaves, Prosdocimi, Klima and DeYoreo contribute to a debate that cities can no longer postpone. The future of heat adaptation may depend less on isolated technological fixes than on coordinated improvements to housing, streets, vegetation, water, electricity and public services. If upgrading informal settlements can reduce dangerous exposure while protecting residents from displacement, it could become one of the most consequential climate-health strategies available to rapidly growing cities. As heat records continue to fall, the question is no longer whether urban infrastructure affects health, but whether cities will redesign it quickly enough to prevent extreme heat from becoming a routine cause of illness and death.

Subject of Research: Urban infrastructure, slum upgrading, climate resilience and health risks during heatwaves

Article Title: Upgrading slums as pathway to climate resiliency: evaluating urban infrastructure impact on health during heatwaves

Article References: Prosdocimi, D.O.B., Klima, K. & DeYoreo, M. “Upgrading slums as pathway to climate resiliency: evaluating urban infrastructure impact on health during heatwaves.” npj Urban Sustainability (2026). https://doi.org/10.1038/s42949-026-00442-w

Image Credits: AI Generated

DOI: 10.1038/s42949-026-00442-w

Keywords: Heatwaves, informal settlements, slum upgrading, urban infrastructure, climate resilience, public health, urban heat, environmental justice, climate adaptation