Molecular characteristics of dissolved organic phosphorus in watershed runoff: Coupled influences of land use and precipitation.

Land use and precipitation are two major factors affecting phosphorus (P) pollution of watershed runoff. However, molecular characterization of dissolved organic phosphorus (DOP) in runoff under the joint influences of land use and precipitation remains limited. This study used Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS) to study the molecular characteristics of DOP in a typical P-polluted watershed with spatially variable land use and precipitation. The results showed that low precipitation and intense human activity, including phosphate mining and associated industries, resulted in the accumulation of aliphatic DOP compounds in the upper reaches, characterized by low aromaticity and low biological stability. Higher precipitation and widespread agriculture in the middle and lower reaches resulted in highly unsaturated DOP compounds with high biological stability constituting a higher proportion, compared to in the upper reaches. While, under similar precipitation, more aliphatic DOP compounds characterized by lower aromaticity and higher saturation were enriched in the lower reaches due to more influence from urban runoff relative to the middle reaches. Photochemical and/or microbial processes did result in changes in the characteristics of DOP compounds during runoff processes due to the prevalence of low molecular weight and low O/C bioavailable aliphatic DOP molecules in the upper reaches, which were increasingly transformed into refractory compounds from the upper to middle reaches. The results of this study can increase the understanding of the joint impacts of land use and precipitation on DOP compounds in watershed runoff.

Rainfall impacts on nonpoint nitrogen and phosphorus dynamics in an agricultural river in subtropical montane reservoir region of southeast China.

The increased frequency and intensity of heavy rainfall events due to climate change could potentially influence the movement of nutrients from land-based regions into recipient rivers. However, little information is available on how the rainfall affect nutrient dynamics in subtropical montane rivers with complex land use. This study conducted high-frequency monitoring to study the effects of rainfall on nutrients dynamics in an agricultural river draining to Lake Qiandaohu, a montane reservoir of southeast China. The results showed that riverine total nitrogen (TN) and total phosphorus (TP) concentrations increased continuously with increasing rainfall intensity, while TN:TP decreased. The heavy rainfall and rainstorm drove more than 30% of the annual N and P loading in only 5.20% of the total rainfall period, indicating that increased storm runoff is likely to exacerbate eutrophication in montane reservoirs. NO3--N is the primary nitrogen form lost, while particulate phosphorus (PP) dominated phosphorus loss. The main source of N is cropland, and the main source of P is residential area. Spatially, forested watersheds have better drainage quality, while it is still a potential source of nonpoint pollution during rainfall events. TN and TP concentrations were significantly higher at sites dominated by cropland and residential area, indicating their substantial contributions to deteriorating river water quality. Temporally, TN and TP concentrations reached high values in May-August when rainfall was most intense, while they were lower in autumn and winter than that in spring and summer under the same rainfall intensities. The results emphasize the influence of rainfall-runoff and land use on dynamics of riverine N and P loads, providing guidance for nutrient load reduction planning for Lake Qiandaohu.

Assessing bioavailability risks of heavy metals in polymetallic mining regions: a comprehensive analysis of soils with varied land uses.

To accurately assess the bioavailability risk of heavy metals (HMs) in a representative polymetallic mining region, we undertook an exhaustive analysis of Cu, Pb, Ni, Co, Cd, Zn, Mn, and Cr in soils from diverse land-use types, encompassing agricultural, forest, residential, and mining areas. We employed speciation analysis methods and a modified risk assessment approach to ascertain potential ecological threats posed by the HMs. Our findings reveal that both the total potential ecological risk and the modified bioavailability risks are most pronounced in the soil of the mining area. The modified bioavailability threats are primarily caused by Pb, Ni, Cd, and Co. Although the total potential ecological risk of Cu is high in the local soil, the predominance of its stable forms reduces its mobility, thereby mitigating its detrimental impact on the ecosystem. Additionally, medium modified bioavailability risks were identified in the peripheries of agricultural and forest areas, potentially attributable to geological processes and agricultural activities. Within the urban district, medium risks were observed in residential and mining areas, likely resulting from mining, metallurgy, industrial operations, and traffic-related activities. This study provides critical insights that can assist governmental authorities in devising targeted policies to alleviate health hazards associated with soils in polymetallic mining regions.

Evolution of land system reforms in China: Dynamics of stakeholders and policy transitions toward sustainable farmland use (2004-2019).

China's central government has prioritized land system reforms in rural parts of the country in the past two decades. The transformation of property rights in lands was a significant step for China to pursue the sustainability of farms and permanent food security. The evolution of land system reforms in China involved constant interplay between stakeholders and policy content in terms of policy objectives and instruments, which exhibited various dynamics in different periods. This study adopted a content analysis method to systematically identify the active, passive, and supportive roles of all kinds of stakeholders as well as policy objectives and instruments in the transitional processes of land system reforms in China. We in sum collected 111 policy texts as samples and modeled the relationships of policy keywords. We found Peasants' Households and New Agricultural Business Entities were the most active stakeholders in different periods. Policy objectives are inclined to the stability of legal rights among stakeholders and the scale production of lands, while policy instruments intensively focused on legal regulations with little attention on financial instruments and human resources. We generated two further policy implications, the protection for the exploitation of lands and the involvement of actual operators, based on our findings.

Resilience to climate change by improving air circulation efficiency and pollutant dispersion in cities: A 3D-UFO approach to urban block design.

Urbanization presents significant challenges to air quality and climate resilience, necessitating pioneering urban design solutions to enhance air circulation and mitigate pollutants. This urgency intensifies in densely populated and rapidly evolving regions like Wuhan, China, where effective strategies are crucial for sustainable development. This study introduces an innovative 3D Urban Form Optimization (3D-UFO) methodology aimed at advancing urban block design configurations to improve urbanization quality. The 3D-UFO approach systematically addresses the multifaceted challenges of climate change and air quality degradation in rapidly urbanizing areas. Integrating GIS-based analysis for comprehensive Land-Use and Land-Cover Change (LULCC) evaluation with Computational Fluid Dynamics (CFD), our approach employs systematic exploration guided by established urban airflow study protocols. Robust metrics-Airspeed-Ratio (ASR) and Average-Age-of-Local-Air (ALA)-quantify the impact of diverse urban block design strategies on air-circulation efficiency and pollutant dispersion. Analysis across various urban scenarios, yielded by the proposed 3D-UFO approach, reveal significant variations in air-circulation efficiency at street and building levels (SBLs). Optimal urban air circulation achieves efficiency levels of 50-70 % when airflow aligns orthogonally across and parallel to streets. Adjusting street-level building heights, especially incorporating taller structures, boosts ventilation efficiency by 20-30 %, which is crucial for improving airflow dynamics in urban settings. Higher Height-to-Width (H/W) ratios (>5.5) yield a 218.5 % increase in ventilation in specific urban layouts. Notably, the synergy of street-aspect-ratio and building-height-ratio adjustments significantly enhance ASR and ALA, providing a quantitative foundation for sustainable urban development. This 3D-UFO methodology, fusing LULCC analysis, CFD simulations, and systematic exploration, emerge as a valuable framework for urban planners and designers. The study offers informed insights into urban sustainability challenges, demonstrating advancements in addressing environmental concerns and improving living conditions within densely populated environments.

Evolution characteristics and driving factors of potential non-point source pollution risks in a watershed affected by land use changes.

Land use types, land development and utilization intensity within watersheds have changed based on intensifying human activities and climate change, thereby inducing spatiotemporal variations in non-point source pollution (NPS), significantly impacting soil and water quality. This study performed a case study on an ecological environment functional zone at the northern foot of Qinling Mountains, an area strongly affected by human activities and land use changes. It employed an improved potential non-point pollution index (PNPI) model to analyze potential non-point source pollution (PNPS) and associated risk evolution characteristics in watershed over the past 30 years. The results indicate that from 1990 to 2020, the dominant land use categories were forest and arable land, making up 95 % of the entire watershed area. Notably, urban residential land presented the most significant expansion rates and nearly doubled in area between 1990 and 2020, whereas shrubland, grassland, and unused land showed a decreasing trend. With the application of the quantile classification method, PNPS risk values were divided into five categories: very low, low, moderate, high, and very high. A polarized trend in risk was observed, with increases in areas influenced by human activities and rapid expansion of very high-risk regions. Concurrently, the pollution risk in the upstream water source area decreased. In recent years, accelerated urbanization has been the main driver causing expansion of high PNPS risk regions. This study explores the spatial and temporal evolution of PNPS risk in the Heihe Basin by using an improved PNPI model. The improved model is more accurate in calculations and provides a better understanding of the distribution of PNPS, which is an important reference for watershed management and water resource governance.

Hydrology and water quality drive multiple biological indicators in a dam-modified large river.

Freshwater biodiversity is increasingly threatened by dams and many other anthropogenic stressors, yet our understanding of the complex responses of different biotas and their multiple facets remains limited. Here, we present a multi-faceted and integrated-indices approach to assess the differential responses of freshwater biodiversity to multiple stressors in the Yangtze River, the third longest and most dam-densely river in the world. By combining individual biodiversity indices of phytoplankton, zooplankton, periphyton, macroinvertebrates, and fish with a novel integrated aquatic biodiversity index (IABI), we disentangled the effects of hydrology, water quality, land use, and natural factors on both α and ß diversity facets in taxonomic, functional, and phylogenetic dimensions. Our results revealed that phytoplankton and fish species and functional richness increased longitudinally, while fish taxonomic and phylogenetic ß diversity increased but phytoplankton and macroinvertebrate ß diversity remained unchanged. Hydrology and water quality emerged as the key drivers of all individual biodiversity indices, followed by land use and natural factors, with fish and phytoplankton showed the strongest responses. Importantly, we found that natural, land use, and hydrological factors indirectly affected biodiversity by altering water quality, which in turn directly influenced taxonomic and phylogenetic IABIs. Our findings highlight the complex interplay of multiple stressors in shaping freshwater biodiversity and underscore the importance of considering both individual and integrated indices for effective conservation and management. We propose that our multi-faceted and integrated-indices approach can be applied to other large, dam-modified river basins globally.

Migration of heavy metals in soil-plant system after land use of sewage sludge at high application ratio.

As one of the reclamation methods of sewage sludge, land application is commonly used. Because almost all organic waste is supposed to be recycled in land use, higher application ratio is necessary. This study conducted sludge land use experiments under high application ratio, and the migration of heavy metals in soil-plant system were studied. The mixture ratio of sludge to soil was 0:1, 0.00862:1, 0.2:1 (240 DS t/hm2), and 0.75:1 (900 DS t/hm2), which is higher than ISO 19698: 2020 and all the Chinese standards. The results showed that the high ratio of sludge application increased the concentration of heavy metals in soil, but after planting plants, the concentration of heavy metals decreased. And compared to sunflower and black-eyed Susan, ryegrass had the best bioaccumulation and transport capacity for heavy metals. As for the residual heavy metals in the soil, compared to the application ratio of 0.00862:1, increasing the application ratio to 0.2:1 did not significantly increase the risk of heavy metals. And if sludge was applied continuously for 15 years, only Hg may have a cumulative risk at the ratio of 0.2:1, but did not exceed GB 36600-2018. Controlling the maximum application rate at 0.2 and planting ryegrass can be a feasible strategy.

Quantifying future carbon emissions uncertainties under stochastic modeling and Monte Carlo simulation: Insights for environmental policy consideration for the Belt and Road Initiative Region.

This study critically examines future carbon (CO2) emissions in the Belt & Road Initiative (BRI) region, considering factors such as energy consumption, economic growth, population growth, and population density. The objective of this study is to identify critical areas of higher emissions, which require policy intervention capable of strengthening sustainability in the BRI compact. A combined approach of stochastic modeling and Monte Carlo simulations was employed, utilizing panel data from 45 countries in the BRI region from 1990 to 2021. Results confirm that emissions are higher in all scenarios in direct proportion to electric power consumption, population growth, and Gross Domestic Product (GDP) growth. In scenarios with high emissions, a continuous and significant upward trend in CO2 emissions was observe. The medium emissions scenario exhibited a more moderated rise in emissions, suggesting a balance between economic development and environmental considerations. Critical areas for future environmental policy-making resides in electric power consumption, population growth, and GDP growth. The study strongly recommends for a shift from the current focus on road and railway infrastructure to renewable energy infrastructure, green innovations and efficient technology transfer to member countries. Without this, the BRI region is likely to face increased emissions, posing significant challenges to future sustainable development and global environmental sustainability.

A dataset of crop succession indicators for 2015-2021.

The current agroecological transition of agriculture pushes to a diversification of cropping systems, which requires quantified data describing crop successions. "Crop successions indicators 2015-2021" dataset provides a set of twenty synthesis indicators to characterize crop diversity, crop seasonality, particular components of crop successions and duration of crop rotations. Indicators are computed for a seven-year period from 2015 to 2021. Data source are raw crop sequences open access dataset. Indicators are available for municipalities, departments, regions and the whole mainland France, for arable land. A group of experts in agronomy has been associated to this work, in order to define relevant themes, relevant indicators and relevant indicator definitions. This dataset could be useful to characterize agricultural practices on a given territory, for researchers, local actors as decentralized state services, water agencies, territorial collectivities, chambers of agriculture, or agricultural cooperatives. Proposed indicators could be useful for policy makers to monitor the evolution of cultivation practices, in order to design, implement or evaluate measures targeting cultivation practices.

Stability and heavy metals accumulation of soil aggregates under different land uses in the southwest coastal Bangladesh.

Agricultural soil contamination is increasing day-by-day and becoming a major problem over the globe. Trace elements accumulation in the bulk soil is frequently documented, however, there is no precise mechanism of their distribution in the different soil aggregates level. We collected twelve composite soil samples from banana fields, fallow land, rice cultivated with pond water (rice field-I), and rice cultivated with rain water (rice field-II). We separated soil samples into four different size of aggregates (4-2, 2-0.25, 0.25-0.053, <0.053-mm) and then, aggregate stability (MWD), soil organic carbon (SOC), and heavy metals content (Pb, Cd, Cr, As, Fe, Mn, Zn, Ni, Co, Cu) in the soil samples were measured with different techniques. Results showed that MWD was higher in the rice-based land use, which was significantly contributed by SOC (p < 0.001). The concentration of Pb, As, Cd, Fe, and Mn were increased, while Cu and Zn concentration were reduced with increasing aggregate size (p < 0.05). In contrast, aggregate size did not influence on Ni and Co accumulation (p > 0.05). Moreover, macroaggregate acted as an accumulator for Fe, Mn, and As, while all the aggregate fractions acted as accumulators for Cu and Zn. Our study indicated that MWD, SOC, aggregate size and composition, and metal species were the controlling factors of trace elements accumulation and distribution in the various sizes of soil aggregates.

Assessing the influence of land use, agricultural, industrialization, CO2 emissions, and energy intensity on cereal production.

In light of the growing global demand for food and the urgent need to address environmental challenges, it is essential to understand the factors that influence cereal production. This research set out to examine the intricate relationships between land use practices, agricultural methods, industrialization, energy intensity, carbon emissions, urban population growth, gross domestic savings, and cereal production across fifteen key cereal-producing states in the Americas. The study employs a Panel VAR/GMM model with data spanning from 2000 to 2021. The findings indicate that the lag of all variables exerts a strong, positive, and statistically significant effect on their current values. However, the lag of cereal production on other variables reveals a mixed and weaker effect, with cereal production showing a slight negative impact on land use and carbon dioxide (CO2) emissions. Conversely, the lag of land use positively influences cereal production, underscoring land management's crucial role. Meanwhile, the lag of agricultural practices, while mostly insignificant on other variables including cereal production, negatively affects urban population growth, suggesting that agricultural activities may slow urbanization. Additionally, industrialization has no significant effect on cereal production, except a weak negative influence on CO2 emissions and energy intensity. In contrast, Carbon dioxide emissions, exhibit a significant negative effect on cereal production, highlighting their detrimental impact on agricultural output. Moreover, the lag of energy intensity negatively affects CO2 emissions, suggesting more efficient energy use could help reduce emissions. Meanwhile, Urban population growth also has a significant negative impact on cereal production, indicating that urbanization may harm food security. The effect of gross domestic savings is generally weak and statistically insignificant across variables, though it shows some negative influence on both cereal production and urban population growth. Lastly, Granger causality tests show significant bidirectional causality between land use and cereal production, as well as between CO2 emissions and cereal production. The stability tests indicate that the model remains stable with impulse response functions. Based on these findings, the study offers practical policy implications, acknowledges limitations, and suggests future research directions, providing valuable insights for balancing agricultural productivity, environmental sustainability, and urban development.

Variability in N2O emission controls among different ponds within a hilly watershed.

While it is well established that small water bodies like ponds play a disproportionately large role in contributing to N2O emissions, few studies have focused on lowland ponds in hilly watersheds. Here, we explored the characteristics of N2O concentrations and emissions from various typical ponds (village, tea, forested, and aquaculture ponds) in a hilly watershed and examined the specific controls influencing N2O production. Our findings revealed that tea ponds exhibited the highest N2O flux (8.42 ± 8.23 µmol m-2 d-1), which was 2.8 to 3.3 times greater than other types of ponds. Remarkable seasonal variations were observed in tea and forested ponds due to the seasonality of nutrient-enriched runoff, whereas such variations were less pronounced in village and aquaculture ponds. Key factors such as nitrogen levels, temperature, and dissolved oxygen (DO) emerged as the primary controls of N2O concentrations in ponds, heavily influenced by land use and human activities in their drainage areas. Specifically, N2O production in tea and aquaculture ponds was driven by N inputs from fertilization and feed, respectively, while DO levels governed the process in village and forested ponds, influenced by abundant algae and forest vegetation. This study emphasizes that environmental factors predominantly drive N2O production in ponds within hilly watersheds, but land use in the pond drainages acts as an indirect yet crucial influence. This highlights the need for future research to develop targeted emission reduction strategies based on land use to effectively mitigate N2O emissions, promising a path toward more sustainable and climate-friendly watershed management.

Quantitative assessment of interplay between urbanization dynamics and land surface temperature variations using generalized additive model coupled PDP for sustainable urban planning and management.

The mountainous region of Asir is experiencing rapid and unsystematic urbanization leading to an increase in land surface temperatures (LST), which poses a challenge to human well-being and ecological balance. Therefore, it is necessary to study the interaction between land use and land cover (LULC)-induced urbanization and LST using advanced geostatistical techniques. In addition, understanding the urbanization process and urban density is essential for effective urban planning and management. The aim of this study was to investigate the interaction between the urbanization process, urban density and the associated LST. Using the Random Forest Algorithm, LULC mapping was conducted for the years 1990, 2000 and 2020. Metrics such as land cover change rate (LCCR), land cover index (LCI), landscape expansion index (LEI), mean landscape expansion index (MLEI) and area-weighted landscape expansion index (AWLEI) were used to understand urbanization processes and LULC changes. Convolutional kernels were used to model urban density, and the mono-window algorithm was applied to analyse LST in the selected years. In addition, the study assessed the Surface Urban Heat Island (SUHI) contribution index to LULC and used Generalized Additive Models (GAMs) in conjunction with Partial Dependence Plots (PDPs) to understand the relationship between urbanization processes, urban density and LST. In a detailed 30-year study, the application of the RF algorithm showed significant shifts in LULC with an overall validation accuracy of over 85%. Urban areas grew dramatically from 69.40 km2 in 1990 to 338.74 km2 in 2020, while water areas decreased from 1.51 to 0.54 km2. Dense vegetation increased from 43.36 to 52.22 km2, indicating positive ecological trends. The LST analysis showed a general warming, with the mean LST increasing from 40.51 °C in 1990 to 46.73 °C in 2020 and the highest temperature category (50-60 °C) increasing from 0.78 to 33.35 km2. The built-up area of cities tripled between 1990 and 2020, with the Landscape Expansion Index reflecting significant growth in suburban areas. The modeling of urban density shows increasing urbanization in the centre, which will expand significantly to the east by 2020. The contribution of LULC to LST and the Urban Heat Island (SUHI) effect was evident, with built-up areas showing a constant temperature increase. GAMs confirmed a statistically significant relationship between urban density and LST, with different effects for different types of urban expansion. This comprehensive study quantitatively sheds light on the complicated dynamics of urbanization, land cover change and temperature variation and provides important insights for sustainable urban development.

Co-occurrence and spatial distribution of organic micropollutants in surface waters of the River Aconcagua and Maipo basins in Central Chile.

Organic Micropollutants (OMPs) might pose significant risks to aquatic life and have potential toxic effects on humans. These chemicals typically occur as complex mixtures rather than individually. Information on their co-occurrence and their association with land use is largely lacking, even in industrialized countries. Furthermore, data on the presence of OMPs in freshwater ecosystems in South America is insufficient. Consequently, we assessed the co-occurrence and distribution of OMPs, including pharmaceuticals, pesticides, personal care products, surfactants, and other industrial OMPs, in surface waters of two river basins in central Chile. We focused on identifying and ranking quantified chemicals, classifying their mode of actions, as well as correlating their occurrence with distinct land uses. We identified and quantified 311 compounds that occurred at least once in the River Aconcagua and River Maipo basins, encompassing compounds from urban, agricultural, industrial, and pharmaceutical sectors. Pharmaceuticals were the most frequently occurring chemicals, followed by pesticides, personal care and household products. OMPs with neuroactive properties dominated surface waters in Central Chile, along with OMPs known to alter the cardiovascular and endocrine systems of humans and aquatic animals. Finally, we observed positive correlations between agricultural and urban land uses and OMPs. Our findings represent a step forward in extending current knowledge on the co-occurrence patterns of OMPs in aquatic environments, particularly in developing countries of the southern hemisphere.

Intensifying droughts render more Sahel drylands unsuitable for cultivation.

Two-fifth of the world's population will be confronted by dire land and water shortage for food production by 2050. Here we provide nuanced insights into the Sahel dryland dynamics and rationale behind its underperforming croplands amid climate extremes. We develop a gridded multi-criteria drought index and analyze its spatial and temporal degree of uniformity to designate the drought, climate and cultivable zones. Evidence is drawn from Sahelian Sudan, representing 1.03 million km2 of the African Sahel, during 1940-2020. Cultivation of marginal lands has persisted apace. The peak areas of these marginal lands explain ~50 % of the variations in crop yield, considering the two staple crops, sorghum and millet. Accordingly, the low yields mismatch the steadily growing planted areas of these crops. Droughts expand (shrink) the median size of hyper-arid (arid) area by 466 % (46 %) compared to wet conditions, limiting farming opportunities for 3.5-35.8 % of the croplands. The northernmost borderline of the arid zone determines the rainfed suitability, but potentially cultivable arid areas require contingency risk-reduction plans. Conversely, semi-arid and dry sub-humid zones reveal areas endowed with uniform climate. Skillful climate forecasting should thus guide policymaking towards sustainable agriculture therein. The paper suggests paths towards more effective agricultural policy interventions. Agricultural production entails the Sahel drought being defined in terms of agricultural impacts instead of meteorological conditions. Land use planners and inhabitants must relieve this plight of misconceiving and overlooking the fact of intrinsic interannual rainfall variability. Determining what a dangerous drought is crucial for the Sahel agriculture sector or system. Sahel farming systems should opt for highly flexible agricultural practices based on the above-identified cultivable areas.

Landscape transition-induced ecological risk modeling using GIS and remote sensing techniques: a case of Saint Martin Island, Bangladesh.

Uncontrolled human activity and nature are causing the deterioration of Saint Martin Island, Bangladesh's only tropical island, necessitating sustainable land use strategies and ecological practices. Therefore, the present study measures the land use/cover transition from 1974 to 2021, predicts 2032 and 2042, and constructs the spatiotemporal features of the Landscape Ecological Risk Index based on land use changes. The study utilized Maximum Likelihood Classification (MLC) on Landsat images from 1974, 1988, 2001, 2013, and Sentinel 2B in 2021, achieving ≥ 80% accuracy. The MLP-MC approach was also used to predict 2032 and 2042 LULC change patterns. The eco-risk index was developed using landscape disturbance and vulnerability indices, Bayesian Kriging interpolation, and spatial autocorrelations to indicate spatial clustering. The research found that settlements increased from 2.06 to 28.62 ha between 1974 and 2021 and would cover 41.22 ha in 2042, causing considerable losses in agricultural areas, waterbodies, sand, coral reefs, and vegetation. The area under study showed a more uniform and homogenous environment as Shannon's diversity and evenness scores decreased. The ecological risk of Saint Martin Island increased from 4.31 to 31.05 ha between 1974 and 2042 due to natural and human factors like erosion, tidal bores, population growth, coral mining, habitat destruction, and intensive agricultural practices and tourism, primarily in Nazrul Para, Galachipa, and Western Dakhin Para. The findings will benefit St. Martin Island stakeholders and policymakers by providing insights into current and potential landscape changes and land eco-management.

Spatiotemporal Modelling of Airborne Birch and Grass Pollen Concentration across Switzerland: a comparison of statistical, machine learning and ensemble methods.

BACKGROUND: Statistical and machine learning models are commonly used to estimate spatial and temporal variability in exposure to environmental stressors, supporting epidemiological studies. We aimed to compare the performances, strengths and limitations of six different algorithms in the retrospective spatiotemporal modeling of daily birch and grass pollen concentrations at a spatial resolution of 1 km across Switzerland. METHODS: Daily birch and grass pollen concentrations were available from 14 measurement sites in Switzerland for 2000-2019. To develop the spatiotemporal models, we considered spatial-temporal, spatial and temporal predictors including meteorological factors, land-use, elevation, species distribution and Normalized Difference Vegetation Index (NDVI). We used six statistical and machine learning algorithms: LASSO, Ridge, Elastic net, Random forest, XGBoost and ANNs. We optimized model structures through feature selection and grid search techniques to obtain the best predictive performance. We used train-test split and cross-validation to avoid overfitting and overoptimistic performance indicators. We then combined these six models through multiple linear regression to develop an ensemble hybrid model. RESULTS: The 5th-95th percentiles of birch and grass pollen concentrations were 0-151 and 0-105 grains/m3, respectively. The hybrid ensemble model achieved the best RMSE on the test dataset for both birch and grass pollen with 94.4 and 19.7 grains/m3, respectively. Nonlinear models (Random forest, XGBoost and ANNs) achieved lower test RMSE's than linear models (LASSO, Ridge, Elastic net) for both pollen types, with RMSE's ranging from 105.9 to 140.5 grains/m3 for birch and from 20 to 25.4 grains/m3 for grass pollen. The Random forest algorithm yielded the best spatial and temporal performance among the six evaluated modelling methods. The ensemble hybrid model outperformed the six linear and nonlinear algorithms. Country-wide pollen concentration, land use, weather, and NDVI were important predictors. CONCLUSION: Nonlinear algorithms outperformed linear models and accurately explained complex, nonlinear relationships between environmental factors and measured concentrations.

Human-animal contact to inform zoonotic disease risk across gradients of agricultural land use change in the Central River Region (CRR) of The Gambia (ZooContact): a formative study.

Introduction: Pilot studies are important initial steps in research, providing a preliminary assessment of the practicality, feasibility, and potential challenges of a proposed study. This study attempts to assess the feasibility, practicality, and acceptability of a study that integrates a human-animal contact (HAC) questionnaire, animal biodiversity survey using acoustic analysis, and zoonotic disease investigation in animals among rural households in the Central River Region (CRR) of The Gambia. The pilot study revealed granular insights that would otherwise go unnoticed, providing vital information that directly guided the design and implementation of the subsequent full-scale study on zoonotic disease risk. Methods: A pilot study was conducted in five villages in the CRR of The Gambia. Community sensitization was carried out together with the village leadership, followed by a familiarization tour of the study setting. Questionnaire-based interview was conducted among participants (n = 50) randomly selected to assess the acceptability and reliability of the questionnaire. The feasibility and acceptability of biodiversity surveys and animal sampling were assessed using verbal inquiries from participants and community leaders. Results: The recruitment rate was 96%, and most participants, 50 out of 52, were willing to participate without compensation for lost time during interviews. For animal sampling, 45 out of 50 participants were willing to allow the study team to sample blood and feces from their animals without any form of incentive. All five village heads agreed to the usage of sound recorders to be placed within their community for animal biodiversity assessment. For the survey effort, one field assistant interviewed 25 participants per week. It took a total of 1 h to complete an interview, including random household selection, consenting, and questionnaire interview. Discussion: The pilot study confirmed the feasibility of the research and informed the design of the larger study. Key parameters, such as community access, acceptability, recruitment success, and logistical requirements, contributed to robust sample size calculations and realistic project cost estimates. Additionally, the study enabled the research team to familiarize themselves with the communities and refine the methods for the full study.

Global suitability and spatial overlap of land-based climate mitigation strategies.

Land-based mitigation strategies (LBMS) are critical to reducing climate change and will require large areas for their implementation. Yet few studies have considered how and where LBMS either compete for land or could be deployed jointly across the Earth's surface. To assess the opportunity costs of scaling up LBMS, we derived high-resolution estimates of the land suitable for 19 different LBMS, including ecosystem maintenance, ecosystem restoration, carbon-smart agricultural and forestry management, and converting land to novel states. Each 1 km resolution map was derived using the Earth's current geographic and biophysical features without socioeconomic constraints. By overlaying these maps, we estimated 8.56 billion hectares theoretically suitable for LBMS across the Earth. This includes 5.20 Bha where only one of the studied strategies is suitable, typically the strategy that involves maintaining the current ecosystem and the carbon it stores. The other 3.36 Bha is suitable for more than one LBMS, framing the choices society has among which LBMS to implement. The majority of these regions of overlapping LBMS include strategies that conflict with one another, such as the conflict between better management of existing land cover types and restoration-based strategies such as reforestation. At the same time, we identified several agricultural management LBMS that were geographically compatible over large areas, including for example, enhanced chemical weathering and improved plantation rotations. Our analysis presents local stakeholders, communities, and governments with the range of LBMS options, and the opportunity costs associated with scaling up any given LBMS to reduce global climate change.