Impact Of Future Climate Change Research Articles

Impact of Future Climate Change on Energy Consumption in Residential Buildings: A case study for representative cities in Japan

This study examines the impact of future climate change on energy consumption in residential buildings in Japan, taking into account both the current and future typical meteorological year (TMY) database. TMY data is widely used in the building sector for energy performance assessments, system sizing, and optimization. To investigate the impact of current and future TMY databases on energy consumption of buildings, the study predicts the cooling and heating loads of residential buildings in four cities of Japan under the current (2020 ver.) and future (2086 ver.) TMY databases. Results show that the use of future TMY database leads to significant changes in air-conditioning heat loads of residential buildings in Japan. It finds that the annual cooling load in residential buildings of four cites of Japan increases by approximately 12% for Tokyo, approximately 9% for Toyohashi, approximately 8% for Osaka, and approximately 7% for Nagoya, respectively, however the annual heating load decreases by approximately 8% for Tokyo, approximately 9% for Toyohashi, approximately 6% for Osaka, and approximately 5% for Nagoya, respectively, compared to the current TMY database. This finding suggests that climate change will have a significant impact on future building energy consumption, and proposes energy-efficient building design as a solution to mitigate the impact of climate change on building energy consumption.

Climate change and healthy ageing: An assessment of the impact of climate hazards on older people.

Climate change not only directly impacts older people's longevity but also healthy ageing, which is the process of maintaining physical and mental capacities while optimising functional abilities. The urgency to address both population ageing and climate change necessitates a rethink and assessment of the impact of climate change on older people. This includes identifying what can be done to anticipate, mitigate and adapt to climate change and engage older persons. A review of climate change and healthy ageing forms the basis of evidence in this report. We developed a comprehensive search to assess current literature, combining terms related to ageing and climate change across four major data sets and assessing articles published up to the end of 2021. We summarised the current and future impact of climate change on older people and developed a framework identifying climate change impacts on older persons, recognising social and environmental determinants of healthy ageing. Major hazards and some key exposure pathways include extreme temperatures, wildfire, drought, flooding, storm and sea level rise, air quality, climate-sensitive infectious diseases, food and water insecurities, health and social care system displacement, migration, and relocation. Strategies to address climate change require interventions to improve systems and infrastructure to reduce vulnerability and increase resilience. As a heterogeneous group, older people's perceptions of climate change should be integrated into climate activism. Increasing climate change literacy among older people and enabling them to promote intergenerational dialogue will drive the development and implementation of equitable solutions. Pathways may operate via direct or indirect exposures, requiring longitudinal studies that enable assessment of exposures and outcomes at multiple time points, and analyses of cumulative impacts of hazards across the life course. The lack of systematic reviews and primary research on the impact of most climate hazards, except for heat, on older people is apparent. Future research should include outcomes beyond mortality and morbidity and assess how older people interact with their environment by focusing on their capacities and optimising abilities for being and doing what they value.

The impact of future UK offshore wind farm distribution and climate change on generation performance and variability

The UK plans to significantly increase offshore wind generation capacity as part of the effort to achieve net zero targets. Current installation is densely located in a few areas, particularly off the east coast of England, and although current siting proposals include new offshore regions, significant volumes of wind generation capacity are yet to be located to meet 2050 installation targets. This paper uses a recent dataset of multi-decadal offshore wind power capacity factor timeseries to assess how UK offshore wind generation is likely to be affected by both the spatial distribution of future wind farms, and by the impacts of near-future (2020–2050) climate change. We determine that a wider geographic spread of offshore capacity results in a much-improved and less-variable UK-aggregated power generation profile, with substantial reductions in periods of low generation and extreme wind power ramping events, without negatively impacting mean or peak generation outputs. The impact of near-term climate change appears to be minor, slightly reducing overall generation and possibly resulting in an underestimation of future installation requirements, but this climate signal is outweighed by the effects of spatial distribution, and even more so by inherent hourly to inter-annual wind speed variability. This study implies that the intermittency of wind generation can be partly mitigated through increasing the spatial diversity of the existing wind farm distribution. Alongside a more in depth investigation of future climate change, and a holistic assessment of relevant geospatial factors such as Levelised Cost of Energy, infrastructure, and environmental constraints, this study could be used for optimisation of future offshore wind siting.

Comparative Assessment of Impacts of Future Climate Change on Runoff in Upper Daqinghe Basin, China

Comparative Assessment of Impacts of Future Climate Change on Runoff in Upper Daqinghe Basin, China

Impact of climate change and genetic development on Iowa corn yield

The vulnerability of corn yield to high temperature and insufficient rainfall in the US mid-west is widely acknowledged. The impact of extreme weather and genetic development on corn yield is less well known. One of the main reasons is that the multicollinearity in the variables can lead to confounding results. Here we model the impact of climate and genetic development by employing an elastic net regression model to address the multicollinearity issue. This allows us to develop a more robust multiple regression model with higher predictive accuracy. Using granular data for Iowa from 1981-2018, we find that corn yield is vulnerable to high mean summer temperatures particularly in July, a widening diurnal temperature range in June and dry summer conditions (due to extremely low rainfall) from June-August. We find that overall climate impact reduced average annual yield by 0.7%. We also find that genetic development which led to earlier planting dates, widening duration of the reproductive interval, higher growing degree day accumulation and larger net planted area had a beneficial impact on the Iowa corn yield during 1981-2018 resulting in an average annual yield improvement of 1.8% per annum. This provides a basis for optimism that these genetic developments and management practices will continue to adapt and improve in the future to counter the impact of climate change on corn yield. We have also modelled the impact of future climate change using the latest climate projections from the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR6). These climate projections show that the average temperature during the growing season (MayO-October) will increase by 2.4 -2.9 o C by mid-century while the average spring temperature (March and April) will increase by a relatively slower 1.9 -2.3 o C by mid-century. Additionally, climate projections show that both temperature and rainfall will also become more extreme in the future with the changes varying from spring to summer. Our results show that, just due to climate change alone in Iowa corn yield will decline between 1.4-1.7% per annum until mid-century (or 1.2-2.1% per annum until the late twenty first century).

Future Climate Change Impacts on Rice in Uttar Pradesh, India's Most Populous Agrarian State

AbstractUttar Pradesh, with a population of 237 million, is the largest agrarian state in India, located in the Indo‐Gangetic plains. Rice cultivation is widespread across all districts of Uttar Pradesh, which have varying climate regimes, irrigation infrastructures, crop management practices, and farm sizes. The state is characterized by different agroecological zones (AEZs) with semi‐arid to sub‐humid climates with significant variability in monsoon rainfall. In this study, the impact of climate change on Kharif‐season rice is estimated using crop‐climate scenarios in Uttar Pradesh. A process‐based Crop Simulation Model, Crop Estimation through Resource and Environment Synthesis‐Rice, was simulated with bias‐corrected and downscaled climate data for historical (1995–2014) and three future periods (the 2030s, 2050s, and 2090s) for two mitigation pathways (SSP2‐4.5 and SSP5‐8.5) from the Coupled Model Intercomparison Project 6. Phenology, irrigation amount, crop evapotranspiration, yield, and water use efficiency were evaluated and assessed for all AEZs. Based on the ensemble of 16 climate models, rainfed rice yield increased in the AEZs of western Uttar Pradesh due to increased rainfall, while in eastern Uttar Pradesh yield decreased, under both shared socioeconomic pathways (SSPs). Irrigated rice yield decreased in all AEZs under both SSPs due to an increase in temperature and a decrease in the length of the growing period, with reductions of up to 20% by the 2090s. Irrigation requirements decreased from the 2030s to the 2090s due to increased rainfall and decreased crop evapotranspiration. Despite the projected increase in rainfed yield, the overall rice yield is expected to decrease in the future under both SSPs.

How will future climate change impact prescribed fire across the contiguous United States?

As of 2023, the use of prescribed fire to manage ecosystems accounts for more than 50% of area burned annually across the United States. Prescribed fire is carried out when meteorological conditions, including temperature, humidity, and wind speed are appropriate for its safe and effective application. However, changes in these meteorological variables associated with future climate change may impact future opportunities to conduct prescribed fire. In this study, we combine climate projections with information on prescribed burning windows for ecoregions across the contiguous United States (CONUS) to compute the number of days when meteorological conditions allow for the safe and effective application of prescribed fire under present-day (2006–2015) and future climate (2051–2060) conditions. The resulting projections, which cover 57% of all vegetated area across the CONUS, indicate fewer days with conditions suitable for prescribed burning across ecoregions of the eastern United States due to rising maximum daily temperatures, but opportunities increase in the northern and northwestern United States, driven primarily by rising minimum temperatures and declining wind speeds.

Climate change impact assessments on the Andean genus Menonvillea (Brassicaceae) reveal uneven vulnerability among major phylogenetic and biogeographic groups

Climate change impact on species can be heterogeneous depending on their environments, exposure, and intrinsic characteristics. Likewise, global warming may have an uneven effect on lineages, depending on whether phylogenetic conservatism or divergence of ecological niches predominates during clade diversification, imposing a higher risk to species groups from certain regions, habitats and lineages. This study evaluates the impact of future climate change on Menonvillea, a genus with 24 species distributed along the Andes and contiguous regions of the Southern Cone. The impact on the main phylogenetic, ecological and biogeographic groups is evaluated, also analyzing the effect on its richness and phylogenetic diversity. Results show a strongly negative impact on most species of the genus. However, the greatest pressure seems to be recovered for high Andean species, mainly from the southern portion of the Southern Andes (between 34°S–53S°), and mostly included in Menonvillea sect. Cuneata. Richness appears to be more impacted in high Andean regions, and the loss of phylogenetic diversity is greater than expected at random. These results highlight the strong negative impact that climate change can induce on lineages distributed in the Andean-Patagonian region, and that show patterns of phylogenetic niche conservatism.

Root proliferation adaptation strategy improved maize productivity in the US Great Plains: Insights from crop simulation model under future climate change

Adaptation measures are essential for reducing the impact of future climate risks on agricultural production systems. The present study focuses on implementing an adaptation strategy to mitigate the impact of future climate change on rainfed maize production in the Eastern Kansas River Basin (EKSRB), an important rainfed maize-producing region in the US Great Plains, which faces potential challenges of future climate risks due to a significant east-to-west aridity gradient. We used a calibrated CERES-Maize crop model to evaluate the impacts of baseline climate conditions (1985–2014), late-term future climate scenarios (under the SSP245 emission pathway and CMIP6 models), and a novel root proliferation adaptation strategy on regional maize yield and rainfall productivity. Changes in the plant root system by increasing the root density could lead to yield benefits, especially under drought conditions. Therefore, we modified the governing equation of soil root growth in the CERES-Maize model to reflect the genetic influence of a maize cultivar to improve root density by proliferation. Under baseline conditions, maize yield values ranged from 6522 to 12,849 kgha−1, with a regional average value of 9270 kgha−1. Projections for the late-term scenario indicate a substantial decline in maize yield (36 % to 50 %) and rainfall productivity (25 % to 42 %). Introducing a hypothetical maize cultivar by employing root proliferation as an adaptation strategy resulted in a 27 % increase in regional maize yield, and a 28 % increase in rainfall productivity compared to the reference cultivar without adaptation. We observed an indication of spatial dependency of maize yield and rainfall productivity on the regional precipitation gradient, with counties towards the east having an implicit advantage over those in the west. These findings offer valuable insights for the US Great Plains maize growers and breeders, guiding strategic decisions to adapt rainfed maize production to the region's impending challenges posed by climate change.

The Impact of Climate Change on Health Services in Low- and Middle-Income Countries: A Systematised Review and Thematic Analysis.

Aim: The aim of this study was to assess the impact of climate change on health services as categorized by the WHO's Building Blocks for creating Climate-Resilient Health Systems. Objective: The objective was to conduct a systematized review of the published literature concerning the impact of climate change, using a thematic analysis approach to address our aim and identify areas for further research. Design: A search was conducted on 8 February 2022 using the Embase and PubMed research databases. Peer-reviewed scientific studies that were published in English from 2012 to 2022, which described at least one report concerning the impact of climate change on health services in LMICs, were included. Studies were organized based on their key characteristics, which included the date of publication, objective, method, limitations, participants, and geographical focus. The Mixed-Methods Appraisal Tool (MMAT) was used to assess the risk of bias in the included studies. Results: Twenty-three studies were included in this review. Five areas of health services which align with the WHO building blocks framework were impacted by climate change. These health service areas included: (1) Service Delivery, (2) Human Resources, (3) Health Finance, (4) Healthcare Products and Technology, and (5) Leadership and Governance. However, research concerning the impact of climate change on health information systems, which is part of the WHO building blocks framework, did not feature in our study. The climatic effects were divided into three themes: meteorological effects, extreme weather events, and general. The research in this study found that climate change had a detrimental impact on a variety of health services, with service delivery being the most frequently reported. The risk of bias varied greatly between studies. Conclusions: Climate change has negatively impacted health services in a variety of different ways, and without further actions, this problem is likely to worsen. The WHO building blocks have provided a useful lens through which to review health services. We built an aligned framework to describe our findings and to support future climate change impact assessments in this area. We propose that further research concerning the impact of climate change on health information systems would be valuable, as well as further education and responsible policy changes to help build resilience in health services affected by climate change.

Analysis of climate change impacts on the biogeographical patterns of species-specific productivity of socioeconomically important edible fungi in Mediterranean forest ecosystems

In Mediterranean forests, many species of fungi produce fruiting bodies every autumn, some of which are of great social and economic interest as NTFPs. In addition, these fungi are an essential part of the biodiversity network that ensures the proper functioning of natural ecosystems and that is currently in check due to global change. Therefore, understanding the biogeographic patterns of species-specific fungal productivity is fundamental to anticipate possible changes in the socioeconomic value of our forests and to understand the role they play in the functioning of ecosystems in terms of mitigation and adaptation to climate change. In this study we estimate the future impact of climate change (in Catalonia region, between 2023 and 2100) on five fungal species with high socioeconomic interest in a broad bioclimatic gradient representative of the Mediterranean basin using high resolution at the landscape scale. To achieve this, we use predictive models based on machine learning algorithms and a fungal database resulting from the sampling of more than 100 permanent sampling plots over 20 years. We estimate that current and future productivity patterns differ among species, under different climate change scenarios and bioclimatic regions. Our results suggest that optimal productivity areas may be shifted to higher elevations, making those species with higher productivity at higher elevations the most affected by climate change. This would mean that some species with high socioeconomic value, such as Lactarius deliciosus and Boletus edulis, could be negatively affected in their total productivity in the study area. This study highlights the need to anticipate the potential effects of climate change on fungal productivity and in particular on high socioeconomic value species and to develop management policies oriented to maintain the important role of fungi in natural ecosystems.

Plastic film mulching increases crop yields and reduces global warming potential under future climate change

Identifying suitable cropping systems and planting areas with high yields and low greenhouse gas (GHG) emissions to adapt to climate change is essential for sustainable agricultural development. The DeNitrification-DeComposition (DNDC) model and the Coupled Model Inter-comparison Project Phase 6 (CMIP6) dataset were used to evaluate the impact of climate scenarios on the crop yields and global warming potential (GWP) of maize, winter wheat, and potato under plastic film mulching (PM) and without mulching (CK) systems on the Loess Plateau for 2020–2100. The result showed that the DNDC model could simulate crop yields and carbon dioxide, nitrous oxide, and methane emissions (adjusted R2 > 0.55, normalized root mean square error (nRMSE) < 0.32). Under multiple emission scenarios, the yields of maize and winter wheat increased linearly with time (p < 0.05), the GWP decreased linearly with time (p < 0.05), and the coefficients of variation of both were lower for the PM than CK, indicating that the impact of future climate change on PM system was small and can achieve synergy between food security and carbon reduction. The results of regional divergence characteristics suggested that areas with precipitation below 400 mm were suitable for maize cultivation, especially the PM system, while areas with precipitation above 400 mm were suitable for winter wheat cultivation – both of which could achieve the goals of high yield and low GHG emissions. This study presents an overview of spatiotemporal changes in production and ecological effects, providing a basis for developing agricultural management practices and cultivation areas to address climate change, and could promote the development of dryland agroecosystems in China in a green and sustainable direction.

Determination of crop water requirements and potential evapotranspiration for sustainable coffee farming in response to future climate change scenarios

Climate change (CC) is causing a significant threat to agriculture, a sector complicatedly tied to natural resources. Changes in precipitation patterns, atmospheric water content, and rising temperatures intensely affect global agriculture, especially in tropical regions. In this intense CC scenario, potential evapotranspiration (PET) and crop water requirement (CWR) are critical components of agricultural water management. This study evaluates the future impact of CC on precipitation, CWR, and PET in different provinces of Thailand's northern and northeastern regions. Three bias correction methods (Delta (DT), Empirical Quantile Mapping (EQM), and Quantile Mapping (QM)) were employed for precipitation downscaling from the CanESM5 CMIP6-GCM across selected 13 coffee farms with different coffee species. Arabica and Robusta coffee were carefully selected for this analysis. The DT method demonstrated superiority, exhibiting lower RMSE and higher correlation coefficients than EQM and QM. Farm-specific assessments illuminated water demand's complex dynamics during critical growth stages, showcasing variable CWR and PET. During the blooming stage in N-F1, CWR ranged from 16.7 to 33.7 mm/stage, highlighting the variability in water needs. Projected CC impacts on Arabica and Robusta coffee farms in Chiang Rai and Sisaket presented challenges, emphasizing farm-specific strategies to address potential water deficits or surpluses during critical growth phases. Projected 2023, 2028, and 2033 precipitation demonstrated incongruities with CWR and PET. The findings emphasize the crucial role of farm-specific adaptive strategies in mitigating the impacts of changing precipitation patterns on coffee cultivation.

Topography-mediated light environment regulates intra-specific seasonal and diurnal patterns of photosynthetic plasticity and plant ecophysiological adaptation strategies.

Due to substantial topographic variations in the Himalaya, incident solar radiation in the forest canopy is highly unequal. This results in significant environmental differences at finer scales and may lead to considerable differences in photosynthetic productivity in montane forests. Therefore, local-scale ecophysiological investigations, may be more effective and instructive than landscape-level inventories and models. We investigated leaf ecophysiological differences and related adaptations between two Quercus semecarpifolia forests in aspect-mediated, significantly varying light regimes in the same mountain catchment. Seasonal and diurnal rates of photosynthesis (A) were significantly higher in south aspect (S) than the north (N). Although temperature was a key contributor to seasonal fluctuations in photosynthetic physiology, photoperiod significantly determined intraspecific variations in seasonal and diurnal plasticity of leaf ecophysiological traits between the two topography-mediated light environments. The regression model for A as a function of stomatal conductivity (gsw) explained the critical role of gsw in triggering photosynthetic plasticity as an adaptive function against varying environmental stresses due to seasonal solar differences. We also examined, modifications in chlorophyll content between the two light regimes across seasons to determine the chlorophyll adaptation strategy. The N aspect had higher leaf chl a, b, and chl a + b and a lower chl-allocation ratio (a/b) than S, which helped to optimize the required light reception in the photoreaction centers for improved photosynthetic performance. The leaf light response curves for A and gsw were observed against varying incident photosynthetic photon flux densities (0-2000mol.m2s-1PPFD) for both aspects. We found that the same species developed significantly distinct light response strategies and photosynthetic capacities in S than in N for the given magnitudes of PPFD. Such acquired ecophysiological adaptations owing to varying light environments may provide significant clues for understanding the impact of future climate change on Himalayan tree species.

Impact of Climate Change on Global Security and Cooperation in Mexico

Purpose: The aim of the study was to investigate impact of climate change on global security and cooperation in Mexico&#x0D; Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries.&#x0D; Findings: Climate change exacerbates security risks in Mexico through extreme weather events, economic instability, and social tensions. This poses threats to food and water security, increases vulnerability to natural disasters, and fuels conflicts over resources. To address these challenges, Mexico collaborates with international partners, develops adaptation strategies, and invests in renewable energy. Cooperation at national and global levels is crucial to build resilience and mitigate the impacts of climate change on security.&#x0D; Unique Contribution to Theory, Practice and Policy: Realism theory, complex interdependence theory &amp; environmental security theory may be used to anchor future studies impact of climate change on global security and cooperation in Mexico. Governments and international organizations should prioritize climate diplomacy as a cornerstone of foreign policy. Governments should conduct climate-security risk assessments to identify vulnerable regions and potential hotspots.

Challenges and Opportunities of Digital Diplomacy and Cyberwarfare in Kenya

Purpose: The aim of the study was to investigate challenges and opportunities of digital diplomacy and cyberwarfare&#x0D; Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries.&#x0D; Findings: Climate change exacerbates security risks in Mexico through extreme weather events, economic instability, and social tensions. This poses threats to food and water security, increases vulnerability to natural disasters, and fuels conflicts over resources. To address these challenges, Mexico collaborates with international partners, develops adaptation strategies, and invests in renewable energy. Cooperation at national and global levels is crucial to build resilience and mitigate the impacts of climate change on security.&#x0D; Unique Contribution to Theory, Practice and Policy: Realism theory, constructivism theory &amp; cybersecurity deterrence theory may be used to anchor future studies impact of climate change on global security and cooperation in Mexico. Invest in capacity building for diplomats and foreign service personnel in the field of digital diplomacy and cybersecurity. Implement robust national and international cybersecurity legislation that includes provisions specific to the protection of diplomatic communications and infrastructure.

Ecophysiological traits of seedlings from different accessions of Stipa tenacissima along a climatic gradient

Predicting the future impact of climate change on Stipa tenacissima steppes is of paramount importance to prevent desertification. From this perspective, we selected seven populations, covering a rainfall range from 100 to 600 mm/year at the sites of seed collection, and we grew the seedlings at the same site. Gas exchange measurements of CO2, light response curves, chlorophyll content and isotopic analysis were investigated. Thala and Valencia populations displayed a contrasted gas exchange response. Both populations were subjected to A-Ci curve analysis. No significant difference was detected between these two different populations in the maximum rate of carboxylation (Vcmax) and the maximum rate of electron transport (Jmax). Stipa tenacissima exhibited a variable response in relation to different light intensities. Photosynthesis and chlorophyll fluorescence parameters proved to be significantly different among populations in response to light intensities. All populations exhibited similar chlorophyll content. The isotopic analysis highlighted a different carbon and nitrogen isotopic composition (δ13C and δ15N) and carbon content © among populations. Mesic populations presented a higher gas exchange activity and light response. The xeric populations performed a photosynthesis adjustment along with minimizing chlorophyll content. Under climate change, S. tenacissima limits productivity, which may lead to desertification.

Potential impact of future climate change on grassland cover in Burkina Faso.

The objective of this study was to analyse the potential impact of future climate change on grassland cover in Burkina Faso. MODIS NDVI 250m time series were used to monitor changes in grassland over 2000-2022. The random forest regression (RFR) model was fit by regressing reference data of grassland cover against current climatic and other environmental predictors to predict the current grassland cover map (2022). Projected climate model data of CMIP6 used under SSP 126 and SSP 585 scenarios were integrated into the fit RFR model to predict future change. The results revealed that grassland areas were largely dominated by non-significant productivity change (55%) during 2000-2022. In this period, grassland area knew more increased productivity (35%) than decrease (10%). Burkina Faso is predicted to face more decreased areas of grassland cover than increase by 2061-2080 under SSP 126 and SSP 585 scenarios. The findings of this study can help to set up appropriate adaptation measures to combat climate change in Burkina Faso.

Climate and biodiversity change constrain the flow of cultural ecosystem services to people: A case study modeling birding across Africa under future climate scenarios

Global change is currently impacting ecosystems and their contributions to people (i.e. ecosystem services). These impacts have consequences for societies and human well-being, especially in Africa. Historically, efforts have focused on assessing global change from a social or biophysical perspective, treating them as separate entities. Yet, our understanding of impacts to social-ecological systems remains limited, particularly in the Global South, due to a lack of data, tools, and approaches accounting for social and ecological aspects of ecosystem services. This is especially relevant for cultural ecosystem services as they are less tangible. We use a simple indicator and important provider of a multitude of cultural ecosystem services, birding, to understand how climate, biodiversity, and land use change will impact cultural ecosystem services across Africa. We explore how emerging tools and data can overcome limitations in mapping and modeling cultural ecosystem services, particularly in analyzing human preferences and behavior at large spatiotemporal scales and in data-poor regions. Leveraging crowdsourced data from eBird and using machine learning techniques we map and model recreational birding to assess the underlying social-ecological relationships and the impact of future climate and environmental change. We show that bird species richness, protected areas, accessibility, and max temperature contribute most to birding suitability across the continent. Further, we show spatial shifts in the suitability of birding under three future climate scenarios (SSP126, 370, and 585). Models suggest climate and biodiversity change will increasingly constrain the flow of birding related cultural ecosystem services across Africa. This has implications for human-nature interactions, development of countries, management of protected areas, and overall human well-being in the future. More generally, we highlight opportunities for crowdsourced datasets and machine learning to integrate non-material ecosystem services in models and thus, enhance the understanding of future impacts to ecosystem services and human well-being.

A systematic review on the potential impact of future climate change on India’s biodiversity using species distribution model (SDM) studies: trends, and data gaps

A systematic review on the potential impact of future climate change on India’s biodiversity using species distribution model (SDM) studies: trends, and data gaps