Version 4 of the CRU TS monthly high-resolution gridded multivariate climate dataset

Growth trends clustering: A novel method for detecting forest disturbances and extracting climate signals in tree rings

Tree-ring widths contain valuable historical information related to both forest disturbances and climate variability and changes within forests. However, current methods are still unable to accurately distinguish between disturbances and climate signals in tree rings, especially in the case of climate anomalies. To address this issue, we developed a novel method, called Growth Trends Clustering (GTC) that uses the distribution characteristics of tree-ring widths within a stand to distinguish the effects of climate and other forest disturbances. GTC employed a Gaussian mixture model to fit the probability density distribution of annual ring-width index (RWI) in a stand. Discriminative criteria were established to cluster diverse sub-distributions from the Gaussian mixture model into categories of growth release, suppression, or normal trends. This approach allowed us to identify the occurrence, duration, and severity of forest disturbances based on percentage changes in the growth release or suppression categories of trees. And the effect of climate on tree growth was assessed according to the mean statistics of the growth normal categories. Using common forest disturbances such as defoliating insects and thinning as examples, we validated our method using tree-ring collections from six sites in British Columbia and Quebec, Canada. We found that the GTC method was superior to traditional time-series analysis methods (e.g., Radial Growth Averaging, Boundary Line, Absolute Increase, and Curve Intervention Detection) for detecting past forest disturbances and was able to significantly enhance climate signals. In summary, the GTC method presented in this study introduces a novel statistical approach for accurately distinguishing between forest disturbances and climate signals in tree rings. This is particularly important for understanding forest disturbance regimes under climate change and for developing future disturbance mitigation strategies.

Soil properties modulate actual evapotranspiration and precipitation impacts on crop yields in the USA

Crop yields are affected by hydroclimatic and edaphic conditions, but their interacting roles are often neglected when assessing crop yields at the regional scale. Moreover, often used hydroclimatic conditions such as precipitation and temperature are not as physiologically linked to primary production and yields as actual evapotranspiration. Using statistical models, we quantified the combined effects of edaphic and hydroclimatic conditions on county yields of irrigated rice and rainfed corn, soybean, and spring and winter wheat in the USA (2000-2019). Precipitation and temperature, or actual evapotranspiration, aggregated during the growing season or before and after flowering/silk emergence, in interaction with soil sand content or bulk density, explained up to 87 % of the yield variability. However, actual evapotranspiration explained yields better than precipitation and temperature and their interactions for most combinations of crops and growth periods. At high actual evapotranspiration, yield plateaued or, for spring wheat, decreased. Yields were generally most sensitive to changes in hydroclimatic conditions during part of rather than the entire growing season, and most often after flowering. Soil texture and bulk density modulated the impacts of hydroclimatic conditions: corn and soybean yields were higher in finer soils compared with sandy soils under high evapotranspiration, but lower at low evapotranspiration. Additionally, the yield-maximizing precipitation decreased with sand content and increased with bulk density for most crops. Increasingly available actual evapotranspiration estimates, combined with soil properties, offer an alternative, and more physiologically-based, yield predictor over large climatic gradients to the more widely used precipitation and temperature.

Divergent determinants on interannual variability of terrestrial water cycle across the globe

Intensifying variability in precipitation under a changing climate is projected to amplify fluctuation in terrestrial hydrological cycle, leading to more severe water-related disasters. The connections between interannual variability of hydrological components and factors influencing these connections have not been clearly defined yet. Based on terrestrial water budget from Climate Data Record, we identify dominant factors influencing partitioning interannual variability of precipitation (P) into that of evapotranspiration (E), runoff (Q), and water storage deviation (ΔS) across the globe by employing geographical detector model (GDM). Sensitivities of the variability partitioning to dominant factors are quantified for different hydroclimate regions by linear regression model and law of total differential. Results show that dominant factors influencing precipitation variability partitioning (VP) are different across distinct hydroclimate conditions. Comparing the statistical index (q value) of the GDM, it can be seen that surface air temperature (Ta), snow water equivalent (SWE) and water storage capacity (Smax) are dominant factors of VP in humid, semi-arid and arid regions, respectively. Changes in P variability largely can transfer into Q variability in humid region. The P variability partitioned into Q variability is dramatically reduced in semi-arid region with SWE decreasing, while P variability partitioned into ΔS variability increases with Smax increasing in arid region. Joint effects of Ta and coefficient of variation of precipitation (Pcv) are found to be the most important interaction in determining VP across the globe. Furthermore, warmer temperatures in humid region cause >90 % of the change in precipitation variability to be transferred to Q variability change. In semi-arid region with snowfall, decreased SWE has strong effect on changes in ΔS (30-40 %) and Q (20-40 %) variability. Our findings imply a changing VP and more severe impacts of hydrological extremes under future climate, where intensive changes in Ta, SWE and land cover are projected.

Climate and land use changes impact the trajectories of ecosystem service bundles in an urban agglomeration: Intricate interaction trends and driver identification under SSP-RCP scenarios

The delivery of ecosystem services (ESs), particularly in urban agglomerations, faces substantial threats from impending future climate change and human activity. Assessing ES bundles (ESBs) is critical to understanding the spatial allocation and interactions between multiple ESs. However, dynamic projections of ESBs under various future scenarios are still lacking, and their underlying driving mechanisms have received insufficient attention. This study examined the Beijing-Tianjin-Hebei urban agglomeration and proposed a framework that integrates patch-generating land use simulation into three shared socioeconomic pathway (SSP) scenarios and clustering analysis to assess spatiotemporal variations in seven ESs and ESBs from 1990 to 2050. The spatial trajectories of ESBs were analyzed to identify fluctuating regions susceptible to SSP scenarios. The results indicated that (1) different scenarios exhibited different loss rates of regulating and supporting services, where the mitigation of degradation was most significant under SSP126. The comprehensive ES value was highest under SSP245. (2) Bundles 1 and 2 (dominated by regulating and supporting services) had the largest total proportion under SSP126 (51.92 %). The largest total proportion of Bundles 4 and 5 occurred under SSP585 (48.96 %), with the highest provisioning services. The SSP126 scenario was projected to have the least ESB fluctuation at the grid scale, while the most occurred under SSP585. (3) Notably, synergies between regulating/supporting services were weaker under SSP126 than under either SSP245 or SSP585, while trade-offs between water yield and non-provisioning services were strongest. (4) Forestland and grassland proportions significantly affected carbon sequestration and habitat quality. Climatic factors (precipitation and temperature) acted as the dominant drivers of provisioning services, particularly water yield. Our findings advocate spatial strategies for future regional ES management to address upcoming risks.

The impacts of rising vapour pressure deficit in natural and managed ecosystems

An exponential rise in the atmospheric vapour pressure deficit (VPD) is among the most consequential impacts of climate change in terrestrial ecosystems. Rising VPD has negative and cascading effects on nearly all aspects of plant function including photosynthesis, water status, growth and survival. These responses are exacerbated by land-atmosphere interactions that couple VPD to soil water and govern the evolution of drought, affecting a range of ecosystem services including carbon uptake, biodiversity, the provisioning of water resources and crop yields. However, despite the global nature of this phenomenon, research on how to incorporate these impacts into resilient management regimes is largely in its infancy, due in part to the entanglement of VPD trends with those of other co-evolving climate drivers. Here, we review the mechanistic bases of VPD impacts at a range of spatial scales, paying particular attention to the independent and interactive influence of VPD in the context of other environmental changes. We then evaluate the consequences of these impacts within key management contexts, including water resources, croplands, wildfire risk mitigation and management of natural grasslands and forests. We conclude with recommendations describing how management regimes could be altered to mitigate the otherwise highly deleterious consequences of rising VPD.

Pyrethroid resistance distribution in Triatoma infestans and environmental association along the Argentine endemic zone

Insecticide resistance is considered a barrier to chemical control of Triatoma infestans, the main vector of Chagas disease in the Southern Cone of South America. Although initiatives to reduce the incidence of the disease in the region have integrated different strategies, they have mainly relied on vector elimination using pyrethroid insecticides such as deltamethrin. Reports of pyrethroid resistance in connection with T. infestans control failures first emerged in northern Argentina and southern Bolivia. Recently, a mosaic pyrethroid-resistant focus has been described in the center of the Argentine Gran Chaco (Department of General Güemes, Chaco Province), characterized by the presence of susceptible and very highly resistant populations in the same area. The involvement of different resistance mechanisms has been proposed, together with the contribution of environmental variables that promote the toxicological heterogeneity described. In the endemic zone of Argentina, however, new questions arise: Are there any other clusters of resistance? Is there a relationship between the distribution of resistance and environmental variables (as has been observed at smaller scale)? We studied toxicological data from insects collected and analyzed at 224 localities between 2010 and 2020 as part of the resistance monitoring conducted by the Chagas National Program. The sites were classified according to the survival rate of insects exposed to a discriminant dose of deltamethrin: 0-0.19 were considered susceptible, 0.2-0.79 low-resistance, and 0.8-1 high-resistance. Localities were georeferenced to describe the spatial distribution of resistance and to identify environmental variables (demographics, land use, urbanization, connectivity, and climate) potentially associated with resistance. We used Generalized Linear Models (GLMs) to examine the association between resistance and environmental predictors, selecting error distributions based on the response variable definition. For the entire period, 197 susceptible localities were distributed across the endemic zone. Localities with different survival rates were found throughout the area; 9 high-resistance localities circled the two previously identified resistant foci, and 18 low-resistance in 6 provinces, highlighting their relevance for control planning. Precipitation variables were linked to resistance in all the GLMs evaluated. Presence/absence models were the most accurate, with precipitation, distance from the capital city, and land use contributing to the distribution of resistance. This information could be valuable for improving T. infestans control strategies in future scenarios characterized by unpredictable changes in land use and precipitation.

Strong and consistent effects of waterbird composition on HPAI H5 occurrences across Europe

Since 2014, highly pathogenic avian influenza (HPAI) H5 viruses of clade 2.3.4.4 have been dominating the outbreaks across Europe, causing massive deaths among poultry and wild birds. However, the factors shaping these broad-scale outbreak patterns, especially those related to waterbird community composition, remain unclear. In particular, we do not know whether these risk factors differ from those of other H5 clades. Addressing this knowledge gap is important for predicting and preventing future HPAI outbreaks. Using extensive waterbird survey datasets from about 6883 sites, we here explored the effect of waterbird community composition on HPAI H5Nx (clade 2.3.4.4) spatial patterns in the 2016/2017 and 2020/2021 epidemics in Europe, and compared it with the 2005/2006 HPAI H5N1 (clade 2.2) epidemic. We showed that HPAI H5 occurrences in wild birds in the three epidemics were strongly associated with very similar waterbird community attributes, which suggested that, in nature, similar interspecific transmission processes operate between the HPAI H5 subtypes or clades. Importantly, community phylogenetic diversity consistently showed a negative association with H5 occurrence in all three epidemics, suggesting a dilution effect of phylogenetic diversity. In contrast, waterbird community variables showed much weaker associations with HPAI H5Nx occurrence in poultry. Our results demonstrate that models based on previous epidemics can predict future HPAI H5 patterns in wild birds, implying that it is important to include waterbird community factors in future HPAI studies to predict outbreaks and improve surveillance activities.

The origin and morphological character evolution of the paleotropical woody bamboos

The woody bamboos (Bambusoideae) exhibit distinctive biological traits within Poaceae, such as highly lignified culms, rapid shoot growth, monocarpic mass flowering and nutlike or fleshy caryopses. Much of the remarkable morphological diversity across the subfamily exists within a single hexaploid clade, the paleotropical woody bamboos (PWB), making it ideal to investigate the factors underlying morphological evolution in woody bamboos. However, the origin and biogeographical history of PWB remain elusive, as does the effect of environmental factors on the evolution of their morphological characters. We generated a robust and time-calibrated phylogeny of PWB using single nucleotide polymorphisms retrieved from optimized double digest restriction site associated DNA sequencing, and explored the evolutionary trends of habit, inflorescence, and caryopsis type in relation to environmental factors including climate, soil, and topography. We inferred that the PWB started to diversify across the Oligocene-Miocene boundary and formed four major clades, that is, Melocanninae, Racemobambosinae s.l. (comprising Dinochloinae, Greslanlinae, Racemobambosinae s.str. and Temburongiinae), Hickeliinae and Bambusinae s.l. (comprising Bambusinae s.str. plus Holttumochloinae). The ancestor of PWB was reconstructed as having erect habit, indeterminate inflorescence and basic caryopsis. The characters including climbing/scrambling habit, determinate inflorescence, and nucoid/bacoid caryopsis have since undergone multiple changes and reversals during the diversification of PWB. The evolution of all three traits was correlated with, and hence likely influenced by, aspects of climate, topography, and soil, with climate factors most strongly correlated with morphological traits, and soil factors least so. However, topography had more influence than climate or soil on the evolution of erect habit, whereas both factors had greater effect on the evolution of bacoid caryopsis than did soil. Our results provide novel insights into morphological diversity and adaptive evolution in bamboos for future ecological and evolutionary research.

Cryosphere and land cover influence on stream water quality in Central Asia's glacierized catchments

This work helps address recent calls for systematic water quality assessment in Central Asia and considers how nutrient and salinity sources, and transport, affect water quality along the continuum from the cryosphere to the lowland plains. Spatial and, for the first time, temporal variations in stream water pH, temperature, electrical conductivity, and nitrate and phosphate concentrations are presented for four catchments (485-13,500 km2), all with glaciers and major urban areas. The catchments studied were: Kaskelen (Kazakhstan), Ala-Archa (Kyrgyzstan), Chirchik (Uzbekistan) and the Kofarnihon (Tajikistan). Measurements were made in cryosphere, stream water, groundwater, reservoir and lake samples over a 22-month period at fortnightly intervals from 35 sites. The results highlight that glacier, permafrost and rock glacier outflows were primary and secondary nitrate sources (>1 mg N L-1) to the headwaters, and there were major increases in salinity and nitrate concentrations where rivers receive inputs from agriculture and settlements. Overall, the water quality complied with national and World Health Organization standards, however there were pollution hot-spots with shallow urban groundwaters contaminated with nitrate (>11 mg N L-1) and stream electrical conductivity above 800 μS cm-1 in some agricultural areas indicative of high salinity. Phosphate concentrations were generally low (<0.06 mg P L-1) throughout the catchments, though elevated (>0.2 mg P L-1) in urban areas due to effluent contamination. A melt water dilution effect along the main river channels was discernible, in the electrical conductivity and nitrate concentration seasonal dynamics, 100 s of km from the headwaters. Thus, the input of relatively clean water from the cryosphere is an important regulator of main channel water quality in the urban and farmed lowland plains adjacent to the Tien Shan and Pamir. Improved sewage treatment is needed in urban areas.

Assessing flash flood erosion following storm Daniel in Libya

The eastern Mediterranean basin is witnessing increased storm activity impacting populous urban coastal areas that historically were not prone to catastrophic flooding. In the fall of 2023, Storm Daniel struck the eastern coast of Libya, causing unprecedented flash floods with a tragic death toll and large-scale infrastructure damages. We use Sentinel-1A C-band SAR images to characterize the resulting flash flood erosion and sediment load dynamics across the watersheds and to map damages within coastal cities at their outlets. Our results suggest that sediment loading, resulting from surface erosion, increased the density of turbid streams. The above exacerbated the catastrophic impact of the flash floods in the coastal cities of Derna and Susah, where 66% and 48% of their respective urban surface have experienced moderate-to-high damages. Our findings highlight the increased vulnerability of coastal watersheds in arid areas within the eastern Mediterranean basin due to the forecasted increase in hydroclimatic extremes and call for a transformative coastal management approach to urgently implement nature-based solutions and land-use changes to mitigate these rising risks.

Warming-driven increased synchrony of tree growth across the southernmost part of the Asian boreal forests

Climate change has profoundly affected the synchrony of tree growth at multiple scales, thereby altering the structure and function of forest ecosystems. The Asian boreal forests extend southward to the Greater Khingan Range in northeast China. Given the ecological importance and susceptibility to climate change, the impacts of warming on this marginal forest community have been extensively investigated. Nonetheless, how tree growth synchrony changes across this region remains less understood. Focusing on this knowledge gap, we compiled a contiguously-distributed tree-ring network, containing 18 sampling populations and 475 individual larch trees, to explore the changes in multiple-scale growth synchrony across this region. We found increasing growth synchrony at both the individual and population levels over the past decades. The increasing trend of the regional inter-population growth synchrony was well in line with the increasing temperature and PDSI. Furthermore, 11 of the 18 sampling populations showed significant increases in their intra-population growth synchrony. We further associated the sliding intra-population growth synchrony with local climates. Intra-population growth synchrony of 13 and 11 sampling populations were significantly positively correlated with local temperature, and negatively correlated with local PDSI, respectively, demonstrating the driving role of warming-induced drought on growth synchrony. The linear regression model quantifying this relationship suggested that an increase of 1 °C in annual mean temperature would drive the intra-population growth synchrony to increase by 0.047. As warming trends in the study area are projected to continue over this century, our study warns of the further consequences of the increasing growth synchrony may have on the functioning, resilience, and persistence of forests.

Isotopic signature of plutonium accumulated in cryoconite on glaciers worldwide

Glaciers are recognized as repositories for atmospheric pollutants, however, due to climate change and enhanced melting rates, they are rapidly transitioning from being repositories to secondary sources of such apollutants. Artificial radionuclides are one of the pollutants found on glaciers that efficiently accumulate onto glacier surfaces within cryoconite deposits; a dark, often biogenic sediment. This work provides information about the accumulation, distribution and sources of plutonium (Pu) isotopes in cryoconite samples from glaciers worldwide. Plutonium is an artificial radionuclide spread into the environment in the last decades as a consequence of nuclear test explosions, accidents and nuclear fuel re-processing. Samples collected from 49 glaciers across nine regions of Earth are considered. Activity concentrations of plutonium in cryoconite are orders of magnitude higher than in other environmental matrices typically used for environmental monitoring (e.g. lichens, mosses, soils and sediments), particularly in the Northern Hemisphere. Isotopic ratios indicate that plutonium contamination of cryoconite is dominated by the global signal of stratospheric fallout related to atmospheric nuclear tests. However, specific glaciers in Svalbard reveal a signature compatible with a contribution from the re-entry of the SNAP-9A satellite in 1964, which was equipped with a 238Pu radioisotope thermoelectric generator. Similarly, an excess of 238Pu is observed in cryoconite from the Exploradores Glacier (Chile). This could be associated with the November 1996 crash of the automatic Interplanetary Station "Mars '96" which was carrying a 238Pu thermoelectric generator. This is the first time ever that an isotopic evidence for this event is reported. These findings highlight the role that cryoconite can play in reconstructing the radioactive contamination history of different glaciated regions of the Earth.

GLocal: A global development dataset of subnational administrative areas

The purpose of the GLocal dataset is to enable research in international development that requires both global scope and local precision. Leveraging modern geospatial analysis tools, we process a diverse array of sources to provide researchers with a growing set of economic, demographic, ecological and socio-political variables for geographic units relevant to public policy. We provide separate data files for different levels of administrative and periodic aggregation, along with ad-hoc files with more detailed information on specific topics. In this data descriptor paper, we discuss both our data processing methodologies and validation pipelines, and provide a short case study to illustrate the research potential of the dataset. We also introduce a simple web app, glocal.streamlit.app , which offers a user-friendly interface for exploring and visualizing the dataset. Given the growing number of public and granular sources of relevance for international development research, we hope to continue adding features and expand the GLocal dataset in the future.

Tree Resilience Indices of Norway Spruce Provenances Tested in Long-Term Common Garden Experiments in the Romanian Carpathians

Provenance trials provide a valuable opportunity to evaluate the impact of extreme events on growth and wood properties. In this study, we have evaluated 81 Norway spruce provenances, tested in three provenance trials established in the Romanian Carpathians in 1972. The response to drought of the Norway spruce provenances has been examined using the following tree resilience indices: resistance, recovery, resilience, and relative resilience. The relationship between climate and growth, the correlations between wood traits, and the coordinates of the origin and tree resilience indices were also analysed. In each provenance trial, there were significant differences between provenances and years regarding wood widths and latewood percentage (LWP). Regarding drought extreme events, the years when they occurred in all three provenance trials were 2000 and 2003. Significant differences between provenances for at least one tree resilience index have been found in all provenance trials, for the year 2000. By using subperiods of 25 years, changes in the relationship between climate and growth have been observed. Several provenances with high radial growth and good resistance and/or recovery have been identified. Provenances that performed better in common garden experiments could be used in assisted migration, even in the proximity of the current natural range.

Widening global variability in grassland biomass since the 1980s

Global change is associated with variable shifts in the annual production of aboveground plant biomass, suggesting localized sensitivities with unclear causal origins. Combining remotely sensed normalized difference vegetation index data since the 1980s with contemporary field data from 84 grasslands on 6 continents, we show a widening divergence in site-level biomass ranging from +51% to -34% globally. Biomass generally increased in warmer, wetter and species-rich sites with longer growing seasons and declined in species-poor arid areas. Phenological changes were widespread, revealing substantive transitions in grassland seasonal cycling. Grazing, nitrogen deposition and plant invasion were prevalent in some regions but did not predict overall trends. Grasslands are undergoing sizable changes in production, with implications for food security, biodiversity and carbon storage especially in arid regions where declines are accelerating.

Temporal variation characteristics in the association between climate and vegetation in Northwest China

Northwest China has undergone notable alterations in climate and vegetation growth in recent decades. Nevertheless, uncertainties persist concerning the response of different vegetation types to climate change and the underlying mechanisms. This study utilized the Normalized Difference Vegetation Index (NDVI) and three sets of meteorological data to investigate the interannual variations in the association between vegetation and climate (specifically precipitation and temperature) from 1982 to 2015. Several conclusions were drawn. (1) RNDVI-GP (relationship between Growing Season NDVI and precipitation) decreased significantly across all vegetation, while RNDVI-GT (relationship between Growing Season NDVI and temperature) showed an insignificant increase. (2) Trends of RNDVI-GP and RNDVI-GT exhibited great variations across various types of vegetation, with forests displaying notable downward trends in both indices. The grassland exhibited a declining trend in RNDVI-GP but an insignificant increase in RNDVI-GT, while no significant temporal changes in RNDVI-GP or RNDVI-GT were observed in the barren land. (3) The fluctuations in RNDVI-GP and RNDVI-GT closely aligned with variations in drought conditions. Specifically, in regions characterized by VPD (vapor pressure deficit) trends less than 0.02 hpa/yr, which are predominantly grasslands, a rise in SWV (soil water volume) tended to cause a reduction in RNDVI-GP but an increase in RNDVI-GT. However, a more negative trend in SWV was associated with a more negative trend in both RNDVI-GP and RNDVI-GT when the VPD trend exceeded 0.02 hPa/yr, primarily in forests. Our results underscore the variability in the relationship between climate change and vegetation across different vegetation types, as well as the role of drought in modulating these associations.

Global net climate effects of anthropogenic reactive nitrogen

Anthropogenic activities have substantially enhanced the loadings of reactive nitrogen (Nr) in the Earth system since pre-industrial times1,2, contributing to widespread eutrophication and air pollution3-6. Increased Nr can also influence global climate through a variety of effects on atmospheric and land processes but the cumulative net climate effect is yet to be unravelled. Here we show that anthropogenic Nr causes a net negative direct radiative forcing of -0.34 [-0.20, -0.50] W m-2 in the year 2019 relative to the year 1850. This net cooling effect is the result of increased aerosol loading, reduced methane lifetime and increased terrestrial carbon sequestration associated with increases in anthropogenic Nr, which are not offset by the warming effects of enhanced atmospheric nitrous oxide and ozone. Future predictions using three representative scenarios show that this cooling effect may be weakened primarily as a result of reduced aerosol loading and increased lifetime of methane, whereas in particular N2O-induced warming will probably continue to increase under all scenarios. Our results indicate that future reductions in anthropogenic Nr to achieve environmental protection goals need to be accompanied by enhanced efforts to reduce anthropogenic greenhouse gas emissions to achieve climate change mitigation in line with the Paris Agreement.

Enhancing dynamic flood risk assessment and zoning using a coupled hydrological-hydrodynamic model and spatiotemporal information weighting method

Climate change and intensified human activities are exacerbating the frequency and severity of extreme precipitation events, necessitating more precise and timely flood risk assessments. Traditional models often fail to dynamically and accurately assess flood risks due to their static nature and limited handling of spatiotemporal variations. This study confronts these challenges head-on by developing a novel coupled hydrological-hydrodynamic model integrated with a Block-wise use of the TOPMODEL (BTOP) and the Rainfall-Runoff-Inundation (RRI) model. This integrated approach enables the rapid acquisition of high-precision flood inundation simulation results across large-scale basins, addressing a significant gap in dynamic flood risk assessment and zoning. A critical original achievement of this research lies in developing and implementing a comprehensive vertical-horizontal combined weighting method that incorporates spatiotemporal information for dynamic evaluation indicators, significantly enhancing the accuracy and rationality of flood risk assessments. This innovative method successfully addresses the challenges posed by objective and subjective weighting methods, presenting a balanced and robust framework for flood risk evaluation. The findings from the Min River Basin in China, as a case study, demonstrate the effectiveness of the BTOP-RRI model in capturing the complex variations in runoff and the detailed simulations of flood processes. The model accurately identifies the timing of these peaks, offering insights into the dynamic evolution of flood risks and providing a more precise and timely assessment tool for policymakers and disaster management authorities. The flood risk assessment results demonstrate good consistency with the actual regional conditions. In particular, high-risk areas exhibit distinct characteristics along the river channel, with the distribution area significantly increasing with a sudden surge in runoff. Intense precipitation events expand areas classified as moderate and high risk, gradually shrinking as precipitation levels decrease. This study significantly advances flood risk assessment methodologies by integrating cutting-edge modeling techniques with comprehensive weighting strategies. This is essential for improving the scientific foundation and decision-making processes in regional flood control efforts.

Household Dependence on Forest Resources in the Luki Biosphere Reserve, Democratic Republic of CONGO

This study was aimed at examining the contribution of forest products to rural livelihoods and the socio-economic factors that influence household forest dependence in the Luki Biosphere Reserve. A structured questionnaire poll of 193 households randomly chosen from two enclaves in the Luki Biosphere Reserve, and focus group discussions were used to gather the data. For data analysis, a binary logistic regression model was used. The study revealed a substantial contribution of forest products to household livelihood based on household wealth strata and the gender of the household head. The contribution of forest income has been found to be higher for poor households than to other wealth categories, although their mean income from forest was low. However, the present research further revealed that household forest dependence was significantly determined by socioeconomic factors such as length of residency, age, sex, education, employment and household size. Compared to their elderly counterparts, the youth were probably more dependent on forest products. Therefore, there should be increased capacity-building efforts among the young people to enable them enlighten the local communities about the need for sustainable forest management. Meanwhile, highly educated people were observed to be less dependent on forests. The findings of this research provides empirical evidence from the Mayombe tropical forest, thus contributing to the growth of knowledge on the impact of socioeconomic factors on the household dependence on forest resources, especially in the tropical forest of the Democratic Republic of Congo where the complexity of the relationship between local communities and their environment is still being studied.

(Re)Emerging disease and conflict risk in Africa, 1997-2019

While the number of infectious zoonotic disease outbreaks has been rising, their impact on civil war and social conflict is poorly understood. This study addresses this fundamental limitation using a geolocated monthly dataset on 22 zoonotic diseases in Africa. Zoonotic disease is a key driver of new epidemics, making such pathogens a useful test case. Results suggest that over the January 1997 to December 2019 period, zoonotic disease was negatively associated with state initiation of civil conflict and positively associated with social conflict involving identity militias. Additional analyses find that the effect for identity militias is consistent with a causal interpretation. Rebel violence is not significantly associated with outbreaks. The results are robust to endogeneity concerns and additional sensitivity analyses.

Regional irrigation expansion can support climate-resilient crop production in post-invasion Ukraine

Ukraine supplies a large proportion of grain and oilseeds to the world market and faces disruptions from the Russian invasion in 2022. Here we explore the combined effects of the invasion and climate change on Ukraine's irrigation. In 2021, only 1.6% of Ukraine's cropland was irrigated. Of this portion, 73% experienced substantial declines in irrigated crop production following the invasion. We estimate that by the mid-twenty-first century, three-quarters of croplands will experience water shortages, making business-as-usual rain-fed agricultural practices inadequate in addressing the challenges posed by climate change. We explore how leveraging local surface and groundwater resources could enable sustainable irrigation expansion over 18 million hectares of croplands and form a viable climate adaptation strategy. Finally, we identify regions for implementing enhancements or expansions of irrigation systems that can foster a more resilient agricultural sector-underscoring the growing importance of irrigation in sustaining crop production in Ukraine.

Spatial patterns and environmental functions of dissolved organic matter in grassland soils of China

Soil dissolved organic matter (DOM) is crucial to atmospheric, terrestrial and aquatic environments as well as human life. Here, by characterizing DOM from 89 grassland soils throughout China, we reveal the spatial association between DOM geochemistry in the dry season vs annual ecosystem exchange and cancer cases. The humic-like and high molecular weight (3.4-25 kDa) fractions with lower biodegradability, decline from the northern to the southern regions of China, and are correlated with lower soil respiration and net ecosystem productivity at the continental scale. The <1.2 kDa and proteinaceous fractions could serve as a geographical indicator of nasopharyngeal cancer incidence and mortality, while the 3.4-25 kDa and humified fractions are potentially associated with pancreatic cancer cases (P < 0.05). Our findings highlight that exploiting the environmental functions of soil DOM and mitigating the negative impacts are necessary, and require actions tailored to local soil DOM conditions.

Carbon and oxygen isotopes in mummified wood reveal warmer and wetter winters in the Siberian Arctic 3000 years ago

Paleoclimate reconstructions from the Holocene are important for defining baseline conditions in order to interpret and contextualize the effects of modern climate change. Such records are particularly lacking for Siberia, a region that represents ~ 50% of the Arctic. In addition, the majority of proxy-based paleoclimate reconstructions for the Holocene represent mean annual conditions, and few quantify winter temperature, which is particularly important for predicting the effects of global warming in Arctic environments. Here we provide the first quantitative proxy reconstruction of precipitation and temperature for both summer and winter for 3000 years ago via novel high-resolution intra-annual carbon and oxygen isotope measurements across annual growth rings of fossil wood mummified within the permafrost of far northeastern Siberia. We found that the site experienced greater precipitation year-round (~ 10% increase in summer and ~ 30% increase in winter), cooler summer temperatures, and warmer winter temperatures, compared with today. Our findings indicate that warmer winter temperatures (+ 3.0 °C above early twentieth century values) in the Arctic 3000 years ago drove higher mean annual temperature by up to 1 °C, despite the existence of cooler summers, a similar phenomenon to what is observed within today's Arctic environments, and past intervals of extreme global warmth.

Bite Me: Bark Stripping Showed Negligible Effect on Volume Growth of Norway Spruce in Latvia

Over the past few decades, increasing populations of cervid species in the Baltic region have reduced the quality and vitality of cultivated Norway spruce (Picea abies (L.) Karst.) stands. This study evaluated the effect of bark stripping on the volume growth of spruce trees in Latvia. Data collection took place in two forest stands. In each stand, 20 Norway spruce trees were sampled, 10 with visible bark damage scars and 10 control trees. Stem discs were collected from control trees at specified heights (0 m, 0.5 m, 1 m, 1.3 m, and 2 m, and then at one-metre intervals up to the top) and from damaged trees at additional specific points relative to the damage. Each disc was sanded and scanned; tree ring widths were measured in 16 radial directions using WinDendro 2012a software. Annual volume growth reconstruction was performed for each tree. Changes in relative volume growth were analysed in interaction with scar parameters, tree type (damaged/control), and pre-damage volume using linear regression models. The significance of parameter interactions was assessed using analysis of variance (ANOVA). Pairwise comparisons of estimated marginal means (EMMs) were conducted using Tukey's HSD post hoc test. No significant effect of bark stripping on the total stem volume increment was detected. However, the length of bark stripping scars had a significant impact on relative volume growth in the lower parts of the stems. These findings underscore the importance of further research examining a broader spectrum of cervid damage intensity and the effects of repeated damage on tree survival and growth.

Global and regional prediction of coccidiosis and ascaridiosis prevalence in extensive backyard chickens in low-income and middle-income countries

Backyard chickens usually have open housing and scavenge for food, facilitating contact with infective forms of parasites present in the environment and increasing the risk of parasitic infections. Coccidiosis and ascaridiosis are two internal parasites in scavenging chickens that cause production losses to farmers. Prevalence data of these two diseases are scarce in low-income and middle-income countries (LMICs) but necessary to assess the burden of disease in backyard chickens. This study estimates the clinical prevalence of coccidiosis and ascaridiosis at the country and regional levels in all LMICs using regression imputation methods. Regression models were developed with data of known prevalence of these parasites and using primarily climatic factors as predictors. A binomial random effects model was developed for each disease to impute prevalence. The overall estimated prevalence of coccidiosis was 0.39 (95 % CI: 0.37-0.42), with a higher mean prevalence in tropical countries. The overall estimated prevalence of ascaridiosis was 0.23 (95 % CI: 0.22-0.25) with a higher mean prevalence in countries with tropical, temperate and continental climates. The findings of this study can aid to identify the burdens of coccidiosis and ascaridiosis infections across countries and regions, which can inform disease control plans and, and encourage international alliances to facilitate access to preventive measures, improving animal health and reducing production losses.

The synergy between protected area effectiveness and economic growth

Protected areas conserve biodiversity and ecosystem functions but might impede local economic growth. Understanding the global patterns and predictors of different relationships between protected area effectiveness and neighboring community economic growth can inform better implementation of the Kunming-Montreal Global Biodiversity Framework. We assessed 10,143 protected areas globally with matched samples to address the non-random location of protected areas. Our results show that protected areas resist human-induced land cover changes and do not limit nightlight increases in neighboring settlements. This result is robust, using different matching techniques, parameter settings, and selection of covariates. We identify four types of relationships between land cover changes and nightlight changes for each protected area: "synergy," "retreat," and two tradeoff relationships. About half of the protected areas (47.5%) retain their natural land cover and do so despite an increase of nightlights in the neighboring communities. This synergy relationship is the most common globally but varies between biomes and continents. Synergy is less frequent in the Amazon, Southeast Asia, and some developing areas, where most biodiversity resides and which suffer more from poverty. Smaller protected areas and those with better access to cities, moderate road density, and better baseline economic conditions have a higher probability of reaching synergy. Our results are promising, as the expansion of protected areas and increased species protection will rely more on conserving the human-modified landscape with smaller protected areas. Future interventions should address local development and biodiversity conservation together to achieve more co-benefits.

Rainfall seasonality dominates critical precipitation threshold for the Amazon forest in the LPJmL vegetation model

Understanding the Amazon Rainforest's response to shifts in precipitation is paramount with regard to its sensitivity to climate change and deforestation. Studies using Dynamic Global Vegetation Models (DGVMs) typically only explore a range of socio-economically plausible pathways. In this study, we applied the state-of-the-art DGVM LPJmL to simulate the Amazon forest's response under idealized scenarios where precipitation is linearly decreased and subsequently increased between current levels and zero. Our results indicate a nonlinear but reversible relationship between vegetation Above Ground Biomass (AGB) and Mean Annual Precipitation (MAP), suggesting a threshold at a critical MAP value, below which vegetation biomass decline accelerates with decreasing MAP. We find that approaching this critical threshold is accompanied by critical slowing down, which can hence be expected to warn of accelerating biomass decline with decreasing rainfall. The critical precipitation threshold is lowest in the northwestern Amazon, whereas the eastern and southern regions may already be below their critical MAP thresholds. Overall, we identify the seasonality of precipitation and the potential evapotranspiration (PET) as the most important parameters determining the threshold value. While vegetation fires show little effect on the critical threshold and the biomass pattern in general, the ability of trees to adapt to water stress by investing in deep roots leads to increased biomass and a lower critical threshold in some areas in the eastern and southern Amazon where seasonality and PET are high. Our findings underscore the risk of Amazon forest degradation due to changes in the water cycle, and imply that regions that are currently characterized by higher water availability may exhibit heightened vulnerability to future drying.

Mutual inhibition effects of elevated CO2 and climate change on global forest GPP

The impact of CO2 fertilization on enhancing global forest gross primary productivity (GPP) is acknowledged, but its interaction with climate factors-air temperature (Tem), precipitation (Pre), vapor pressure deficit (VPD), and radiation (Rad)-remains unclear. In this study, global forest GPP trends from 1982 to 2018 were examined using BEPS, NIRv, FLUXCOM, and revised EC-LUE datasets, with interannual trends of 5.618 (p < 0.01), 5.831 (p < 0.01), 0.227, and 6.566 g C m-2 yr-1 (p < 0.01), respectively. Elevated CO2 was identified as the primary driver of GPP trends, with the dominant area ranging from 51.11% to 90.37% across different GPP datasets. In the NIRv and revised EC-LUE datasets, the positive impact of CO2 on GPP showed a decrease of 0.222 g C m-2 yr-1, while the negative impact of Rad increased by 0.007 g C m-2 yr-1. An inhibitory relationship was found between the actual effects of elevated CO2 and climate change on GPP in most forest types. At lower latitudes, Tem primarily constrained CO2 fertilization, while at higher latitudes, VPD emerged as the key limiting factor. This was mainly attributed to the potential trade-off or competition between elevated CO2 and climate change in influencing GPP, with strategic resource allocation varying across different forest ecosystems. This study highlights the significant inhibitory effects of elevated CO2 and climate change on global forest GPP, providing insights into the dynamic responses of forest ecosystems to changing environments.

Tree-ring widths of Pinus tabulaeformis Carr reveal variability of winter half-year precipitation on the north-south transition zone in central China over the past 220 years

Long-term, high-resolution regional drought records contribute to understanding the impacts of drought on environmental and social systems in central China. Here, we develop a regional tree-ring width chronology of Pinus tabulaeformis Carr from the northern slope of Funiu Mountains on the north-south transition zone in central China. Monthly correlation analyses showed that temperature and humidity in current May and June are main limiting factors on tree growth. Despite that, the highest correlation with tree growth was found to be precipitation from previous December to current June (PreDJ, 0.718, p < 0.001), which was chosen for reconstruction. The reconstructed PreDJ revealed six drought periods and five wet periods over the past 220 years, and the recent dry spell would likely to continue. Spectral analyses indicated that the reconstructed PreDJ was closely related to the El Nino-Southern Oscillation (ENSO, 2-7a) and 35a climatic oscillation of Bruckner, and was also affected by the Quasi-Biennial Oscillation (QBO). Wavelet analyses showed that the quasi-cycle of 2-7a persisted over the past 220 years and strengthened after the 1980s, and the QBO signals appeared from the 1860s to 1970s and wear off thereafter, and 35a cycle only appeared during 1820-1920. Spatial analysis found that the reconstructed PreDJ had good spatial representation of precipitation in the central-eastern China. Therefore, the results of this study provide reliable information for understanding long-term drought impacts on environmental conditions and socioeconomic development in central China.

Path for recovery: an ecological overview of the Jambato Harlequin Toad (Bufonidae: Atelopus ignescens) in its last known locality, Angamarca Valley, Ecuador

The Jambato Harlequin toad (Atelopus ignescens), a formerly abundant species in the Andes of Ecuador, faced a dramatic population decline in the 1980s, with its last recorded sighting in 1988. The species was considered Extinct by the IUCN until 2016, when a fortuitous discovery of one Jambato by a local boy reignited hope. In this study, we present findings from an investigation conducted in the Angamarca parish, focusing on distribution, abundance, habitat preferences, ecology, disease susceptibility, and dietary habits of the species. In one year we identified 71 individuals at different stages of development in various habitats, with a significant presence in agricultural mosaic areas and locations near water sources used for crop irrigation, demonstrating the persistence of the species in a complex landscape, with considerable human intervention. The dietary analysis based on fecal samples indicated a diverse prey selection, primarily comprising arthropods such as Acari, Coleoptera, and ants. Amphibian declines have been associated with diseases and climate change; notably, our study confirmed the presence of the pathogen Batrachochytrium dendrobatidis (Bd), but, surprisingly, none of the infected Jambatos displayed visible signs of illness. When analyzing climatic patterns, we found that there are climatic differences between historical localities and Angamarca; the temporal analysis also exposes a generalized warming trend. Finally, in collaboration with the local community, we developed a series of management recommendations for terrestrial and aquatic environments occupied by the Jambato.

Pollen metabarcoding reveals the origin and multigenerational migratory pathway of an intercontinental-scale butterfly outbreak

Migratory insects may move in large numbers, even surpassing migratory vertebrates in biomass. Long-distance migratory insects complete annual cycles through multiple generations, with each generation's reproductive success linked to the resources available at different breeding grounds. Climatic anomalies in these grounds are presumed to trigger rapid population outbreaks. Here, we infer the origin and track the multigenerational path of a remarkable outbreak of painted lady (Vanessa cardui) butterflies that took place at an intercontinental scale in Europe, the Middle East, and Africa from March 2019 to November 2019. Using metabarcoding, we identified pollen transported by 264 butterflies captured in 10 countries over 7 months and modeled the distribution of the 398 plants detected. The analysis showed that swarms collected in Eastern Europe in early spring originated in Arabia and the Middle East, coinciding with a positive anomaly in vegetation growth in the region from November 2018 to April 2019. From there, the swarms advanced to Northern Europe during late spring, followed by an early reversal toward southwestern Europe in summer. The pollen-based evidence matched spatiotemporal abundance peaks revealed by citizen science, which also suggested an echo effect of the outbreak in West Africa during September-November. Our results show that population outbreaks in a part of species' migratory ranges may disseminate demographic effects across multiple generations in a wide geographic area. This study represents an unprecedented effort to track a continuous multigenerational insect migration on an intercontinental scale.

A hybrid ensemble learning merging approach for enhancing the super drought computation over Lake Victoria Basin

This study introduces a novel Hybrid Ensemble Machine-Learning (HEML) algorithm to merge long-term satellite-based reanalysis precipitation products (SRPPs), enabling the estimation of super drought events in the Lake Victoria Basin (LVB) during the period of 1984 to 2019. This study considers three widely used Machine learning (ML) models, including RF (Random Forest), GBM (Gradient Boosting Machine), and KNN (k-nearest Neighbors), for the emerging HEML approach. The three SRPPs, including CHIRPS (Climate Hazards Group Infra-Red Precipitation with Station), ERA5-Land, and PERSIANN-CDR (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Network-Climate Data Record), were used to merge for developing new precipitation estimates from HEML model. Additionally, classification and regression models were employed as base learners in developing this algorithm. The newly developed HEML datasets were compared with other ML and SRPP products for super-drought monitoring. The Standardized precipitation evapotranspiration index (SPEI) was used to estimate super drought characteristics, including Drought frequency (DF), Drought Duration (DD), and Drought Intensity (DI) from machine learning and SRPPs products in LVB and compared with RG observation. The results revealed that the HEML algorithm shows excellent performance (CC = 0.93) compared to the single ML merging method and SRPPs against observation. Furthermore, the HEML merging product adeptly captures the spatiotemporal patterns of super drought characteristics during both training (1984-2009) and testing (2010-2019) periods. This research offers crucial insights for near-real-time drought monitoring, water resource management, and informed policy decisions.

Consistent time allocation fraction to vegetation green-up versus senescence across northern ecosystems despite recent climate change

Extended growing season lengths under climatic warming suggest increased time for plant growth. However, research has focused on climatic impacts to the timing or duration of distinct phenological events. Comparatively little is known about impacts to the relative time allocation to distinct phenological events, for example, the proportion of time dedicated to leaf growth versus senescence. We use multiple satellite and ground-based observations to show that, despite recent climate change during 2001 to 2020, the ratio of time allocated to vegetation green-up over senescence has remained stable [1.27 (± 0.92)] across more than 83% of northern ecosystems. This stability is independent of changes in growing season lengths and is caused by widespread positive relationships among vegetation phenological events; longer vegetation green-up results in longer vegetation senescence. These empirical observations were also partly reproduced by 13 dynamic global vegetation models. Our work demonstrates an intrinsic biotic control to vegetation phenology that could explain the timing of vegetation senescence under climate change.

spread.gl: visualising pathogen dispersal in a high-performance browser application

Phylogeographic analyses are able to exploit the location data associated with sampled molecular sequences to reconstruct the spatio-temporal dispersal history of a pathogen. Visualisation software is commonly used to facilitate the interpretation of the accompanying estimation results, as these are not always easily interpretable. spread.gl is a powerful, open-source and feature-rich browser application that enables smooth, intuitive and user-friendly visualisation of both discrete and continuous phylogeographic inference results, enabling the animation of pathogen geographic dispersal through time. spread.gl can render and combine the visualisation of several data layers, including a geographic layer (e.g., a world map), multiple layers that contain information extracted from the input phylogeny, and different types of layers that represent environmental data. As such, users can explore which environmental data may have shaped pathogen dispersal patterns, that can subsequently be formally tested through more principled statistical analyses. We showcase the visualisation features of spread.gl on several representative pathogen dispersal examples, including the smooth animation of a phylogeny encompassing over 17,000 genomic sequences resulting from a large-scale SARS-CoV-2 analysis.

The water footprint of hydrogen production

Hydrogen (H2) is the most promising energy carrier for reducing the carbon emissions of the energy sector, but the impact of its production on water resources remains unclear. Here, we quantify the water footprint (WF) of different H2 production pathways accounting for the WF of the primary energy used in the production process, as well as feedstock and infrastructure water requirements. Results suggest that green H2 obtained from water electrolysis powered by renewable energy has the lowest WF (65 ± 2 m3/TJ for wind and 204 ± 79 m3/TJ for solar) mostly due to the low WF of renewable energy. The WF of blue H2 derived from fossil fuels is significantly higher (369 ± 30 m3/TJ for natural gas and 564 ± 82 m3/TJ for coal) due to high WF of fossil fuels as well as the water required for carbon capture and storage (CCS). H2 produced from nuclear energy and biomass have extremely high WF (741 ± 277 m3/TJ for nuclear and > 50,000 m3/TJ for biomass). Considering global and country-based energy scenarios, where the main H2 colors (green and blue) individually account for 15 % of energy consumption, we find that the use of green H2 could reduce the water demand of the energy sector while blue H2 would generally increase it, except in countries already characterized by high water consumption due to reliance on water-intensive energy sources. At the global level, we find that for every 5 % of H2 energy adoption, the energy sector could have water savings between 1 and 4 % for green H2 and increase water consumption between 1 and 5 % for blue H2. These results highlight the potential and criticalities of H2 within the water-energy nexus.

Aridity-dependent shifts in biodiversity-stability relationships but not in underlying mechanisms

Climate change will affect the way biodiversity influences the stability of plant communities. Although biodiversity, associated species asynchrony, and species stability could enhance community stability, the understanding of potential nonlinear shifts in the biodiversity-stability relationship across a wide range of aridity (measured as the aridity index, the precipitation/potential evapotranspiration ratio) gradients and the underlying mechanisms remain limited. Using an 8-year dataset from 687 sites in Mongolia, which included 5496 records of vegetation and productivity, we found that the temporal stability of plant communities decreased more rapidly in more arid areas than in less arid areas. The result suggests that future aridification across terrestrial ecosystems may adversely affect community stability. Additionally, we identified nonlinear shifts in the effects of species richness and species synchrony on temporal community stability along the aridity gradient. Species synchrony was a primary driver of community stability, which was consistently negatively affected by species richness while being positively affected by the synchrony between C3 and C4 species across the aridity gradient. These results highlight the crucial role of C4 species in stabilizing communities through differential responses to interannual climate variations between C3 and C4 species. Notably, species richness and the synchrony between C3 and C4 species independently regulated species synchrony, ultimately affecting community stability. We propose that maintaining plant communities with a high diversity of C3 and C4 species will be key to enhancing community stability across Mongolian grasslands. Moreover, species synchrony, species stability, species richness and the synchrony between C3 and C4 species across the aridity gradient consistently mediated the impacts of aridity on community stability. Hence, strategies aimed at promoting the maintenance of biological diversity and composition will help ecosystems adapt to climate change or mitigate its adverse effects on ecosystem stability.

Drought, temperature, and moisture availability: understanding the drivers of isotopic decoupling in native pine species of the Nepalese Himalaya

The Himalayas experienced long-term climate changes and recent extreme weather events that affected plant growth and the physiology of tree species at high-elevation sites. This study presents the first statistically robust δ18OTR chronologies for two native pine species, Pinus roxburghii, and Pinus wallichiana, in the lower Nepalese Himalaya. The isotope chronologies exhibited 0.88‰ differences in overall mean isotope values attributed to varying elevations (460-2000 m asl). Comparative analysis of climate response using data sets from different sources and resolutions revealed the superiority of the APHRODITE (Asian Precipitation - Highly-Resolved Observational Data Integration Towards Evaluation) data set calibrated for the South Asian Summer Monsoon (SASM)-dominated region. Both species exhibited negative correlations with monsoon precipitation and positive correlations with temperature. However, during the peak monsoon season (July-August), daily resolved climate data disentangled statistically insignificant relationships, and revealed that δ18OTR is influenced by atmospheric moisture. Both congeneric species showed a decoupling between the chronologies after 1995. However, no significant change in air moisture origin and monsoon regime between the study sites was observed, indicating a consistent dominant moisture source during different monsoon seasons. Besides, we also observed the decreased inter-series correlation of both δ18OTR chronologies after 1995, with P. wallichiana experiencing a steeper decrease than P. roxburghii. The weakening correlations between and within the chronologies coincided with a regional drought during 1993-1995 in both sites, highlighting the strong regulation of local climate on the impact of regional extreme climate events. Our findings emphasise the importance of employing climate data with optimal spatial and temporal resolution for improved δ18OTR-climate relationships at the intra-annual scale while considering the influence of site-specific local environmental conditions. Assessing climate data sets with station data is vital for accurately interpreting climate change's impact on forest response and long-term climate reconstructions.

Global pattern and determinant for interaction of seasonal influenza viruses

BACKGROUND

The prevalence of different types/subtypes varies across seasons and countries for seasonal influenza viruses, indicating underlying interactions between types/subtypes. The global interaction patterns and determinants for seasonal influenza types/subtypes need to be explored.

METHODS

Influenza epidemiological surveillance data, as well as multidimensional data that include population-related, environment-related, and virus-related factors from 55 countries worldwide were used to explore type/subtype interactions based on Spearman correlation coefficient. The machine learning method Extreme Gradient Boosting (XGBoost) and interpretable framework SHapley Additive exPlanation (SHAP) were utilized to quantify contributing factors and their effects on interactions among influenza types/subtypes. Additionally, causal relationships between types/subtypes were also explored based on Convergent Cross-mapping (CCM).

RESULTS

A consistent globally negative correlation exists between influenza A/H3N2 and A/H1N1. Meanwhile, interactions between influenza A (A/H3N2, A/H1N1) and B show significant differences across countries, primarily influenced by population-related factors. Influenza A has a stronger driving force than influenza B, and A/H3N2 has a stronger driving force than A/H1N1.

CONCLUSION

The research elucidated the globally complex and heterogeneous interaction patterns among influenza type/subtypes, identifying key factors shaping their interactions. This sheds light on better seasonal influenza prediction and model construction, informing targeted prevention strategies and ultimately reducing the global burden of seasonal influenza.

Larger nations benefit more than smaller nations from the stabilizing effects of crop diversity

Crop diversification is increasingly recognized as a strategy to stabilize national food production, yet the benefits of this approach may vary across nations due to the scale dependence of crop diversity and stability. Here we use crop production data from 131 nations from 1961 to 2020 to explore the spatial scale dependence of the crop diversity-stability relationship. Drawing on ecological theory and complementary analytical approaches, we find that as the total national harvested area increases, yield stability increases. Crop diversity stabilizes national yield stability, as does an increase in the number of farms, but these stabilizing effects are weaker in smaller countries. Our findings suggest that enhancing crop diversity at the national level may not provide a de facto universal strategy for increasing yield stability across all countries-with implications for national strategies promoting crop diversification to protect against food system shocks.

A Key Interaction Behind the Scenes: Dung Beetles in Livestock Production from Arid and Semi-Arid Rangelands

Pastoralism is a dominant agricultural activity in arid and semi-arid ecosystems. The interaction between coprophagous insects and livestock is a key but an undervalued topic in rangeland management decisions. The objective was to identify similarities and differences in the composition of coprophagous insects and nesting strategies, associated with different climatic conditions within these regions. We performed a literature review of research articles available in the Scopus database which resulted in 17 articles. We examined the taxonomic diversity of dung beetles and their nesting strategies in relation to temperature and precipitation at the study sites. Results revealed a rich and varied interaction between dung beetles and livestock in arid and semi-arid environments, with 364 species from the Scarabaeoidea superfamily documented worldwide. The greatest diversity of dung beetles was reported in hot arid and semi-arid conditions with dry winters and in cold semi-arid ones with no marked annual precipitation cycle. These insects displayed diverse nesting strategies, with endocoprid strategies predominating in colder and drier settings, and paracoprid and telecoprid strategies in warmer, more humid environments. Domestic animal species are currently key components in promoting this interaction, which indicates that the ecological processes involving coprophagous fauna are occurring in production systems, which are under the influence of human decisions. We discuss the design and planning of livestock and rangeland management in arid and semi-arid environments, emphasizing in a more formalized manner the inclusion of this kind of interaction.

A unified dataset for pre-processed climate indicators weighted by gridded economic activity

Although high-resolution gridded climate variables are provided by multiple sources, the need for country and region-specific climate data weighted by indicators of economic activity is becoming increasingly common in environmental and economic research. We process available information from different climate data sources to provide spatially aggregated data with global coverage for both countries (GADM0 resolution) and regions (GADM1 resolution) and for a variety of climate indicators (total precipitations, average temperatures, average SPEI). We weigh gridded climate data by population density, night-time light intensity, cropland, and concurrent population count - all proxies of economic activity - before aggregation. Climate variables are measured daily, monthly, and annually, covering (depending on the data source) a time window from 1900 (at the earliest) to 2023. We pipeline all the preprocessing procedures in a unified framework, and we validate our data through a systematic comparison with those employed in leading climate impact studies.

Assessing Soil Quality, Wheat Crop Yield, and Water Productivity under Condition of Deficit Irrigation

Wheat is one of the most important cereal crops in Egypt and all over the world. Its productivity is adversely affected by drought due to deficient irrigation to provide nutrients required for plant growth. In a field experiment, silicon foliar applications at concentrations of 0, 200, and 400 mg L-1 were performed at different irrigation rates ranging from 1000 to 4000 m3 ha-1 to assess water irrigation productivity and wheat crop yield in a calcareous soil under arid climate conditions. Increased irrigation rates led to a significant increase in soil nutrient dynamics, as well as in the number and weight of grains per spike, leaf area index, grain yield, straw yield, and biological yield, with the exception of the weight of 1000 grains. Spraying with sodium silicate had a significant impact on grain yield and harvest index but did not significantly impact the other traits. Furthermore, the interaction between irrigation and silicate application rates showed significance only for grain yield, the number of spikes/m2, and the harvest index. Applying three times irrigation could produce the highest nutrient retention, wheat yield, and water irrigation productivity. No significance was observed between 3000 m3 ha-1 and 4000 m3 ha-1 irrigation, indicating a saving of 25% of applied irrigation water. It can be concluded that applying irrigation at 3000 m3 ha-1 could be a supplemental irrigation strategy. High wheat grain yield can be achieved under deficit irrigation (3000 m3 ha-1) on the northwestern coast of Egypt with an arid climate by spraying crops with sodium silicate at a rate of 400 mg L-1.

Identifying drivers of non-stationary climate-growth relationships of European beech

The future performance of the widely abundant European beech (Fagus sylvatica L.) across its ecological amplitude is uncertain. Although beech is considered drought-sensitive and thus negatively affected by drought events, scientific evidence indicating increasing drought vulnerability under climate change on a cross-regional scale remains elusive. While evaluating changes in climate sensitivity of secondary growth offers a promising avenue, studies from productive, closed-canopy forests suffer from knowledge gaps, especially regarding the natural variability of climate sensitivity and how it relates to radial growth as an indicator of tree vitality. Since beech is sensitive to drought, we in this study use a drought index as a climate variable to account for the combined effects of temperature and water availability and explore how the drought sensitivity of secondary growth varies temporally in dependence on growth variability, growth trends, and climatic water availability across the species' ecological amplitude. Our results show that drought sensitivity is highly variable and non-stationary, though consistently higher at dry sites compared to moist sites. Increasing drought sensitivity can largely be explained by increasing climatic aridity, especially as it is exacerbated by climate change and trees' rank progression within forest communities, as (co-)dominant trees are more sensitive to extra-canopy climatic conditions than trees embedded in understories. However, during the driest periods of the 20th century, growth showed clear signs of being decoupled from climate. This may indicate fundamental changes in system behavior and be early-warning signals of decreasing drought tolerance. The multiple significant interaction terms in our model elucidate the complexity of European beech's drought sensitivity, which needs to be taken into consideration when assessing this species' response to climate change.

Insights from modelling sixteen years of climatic and fumonisin patterns in maize in South Africa

Mycotoxin contamination of agricultural commodities is a global public health problem that has remained elusive to various mitigation approaches, particularly in developing countries. Climate change and its impact exacerbates South Africa's vulnerability to mycotoxin contamination, and significantly threatens its's food systems, public health, and agro-economic development. Herein we analyse sixteen years (2005/2006-2020/2021) of annual national meteorological data on South Africa which reveals both systematic and erratic variability in critical climatic factors known to influence mycotoxin contamination in crops. Within the same study period, data on fumonisin (FB) monitoring show clear climate-dependent trends. The strongest positive warming trend is observed between 2018/2019 and 2019/2020 (0.51 °C/year), and a strong positive correlation is likewise established between FB contamination and temperature (r ranging from 0.6 to 0.9). Four machine learning models, viz support vector machines, eXtreme gradient boosting, random forest, and orthogonal partial least squares, are generalized on the historical data with suitable performance (RMSE as low as 0.00). All the adopted models are able to predict future FB contamination patterns with reasonable precision (R2 ranging from 0.34 to 1.00). The most important model feature for predicting average FB contamination (YA) is the historical pattern of average FB contamination in maize within the region (ΣFBs_avg). The two most significant features in modelling maximum FB contamination (YM) are minimum temperature from the CMIP6 data (Pro_tempMIN) and observed precipitation from the CRU data (O_prep). Our study provides strong evidence of the impact of climate change on FB in South Africa and reiterates the significance of machine learning modelling in predicting mycotoxin contamination in light of changing climatic conditions, which could facilitate early warnings and the adoption of relevant mitigation measures that could help in mycotoxin risk management and control.

Northward shift of Indian summer monsoon and intensifying winter westerlies cause stronger precipitation seasonality over Pamirs and its downstream basins in the 21st century

Hydroclimate will change over Pamirs and its downstream basins (PDB), including Indus River, Tarim River, Amu Darya and Syr Darya Basins, in response to the variation of Indian summer monsoon (ISM) and mid-latitude westerlies. However, the precipitation variation and its mechanism over PDB in the 21st century are yet not fully understood. Here, the best models ensemble selected from 25 CMIP6 models under SSP2-4.5 and SSP5-8.5 scenarios is applied to detect the precipitation variations over PDB in the 21st century. A remarkable dipolar pattern is found in both summer and winter precipitation over PDB, particularly in the central Indus River Basin and upper Amu and Syr Darya Basins. The central Indus River Basin (upper Amu and Syr Darya Basins) will experience an increasingly wet (dry) summer in response to northward ISM and a dry (wet) winter driven by mid-latitude westerlies. The amplifying dipolar pattern of seasonal precipitation thus increases the water resource vulnerability over PDB and emphasizes the role of Pamirs in modulating the water resources over surrounding basins, especially the Amu Darya and Syr Darya Basins in the future. The findings underscore the need for prioritizing policies by considering the impacts of precipitation seasonality on social planning.

Unpredictable soil conditions can affect the prevalence of a microbial symbiosis

The evolution of symbiotic interactions may be affected by unpredictable conditions. However, a link between prevalence of these conditions and symbiosis has not been widely demonstrated. We test for these associations using Dictyostelium discoideum social amoebae and their bacterial endosymbionts. D. discoideum commonly hosts endosymbiotic bacteria from three taxa: Paraburkholderia, Amoebophilus and Chlamydiae. Three species of facultative Paraburkholderia endosymbionts are the best studied and give hosts the ability to carry prey bacteria through the dispersal stage to new environments. Amoebophilus and Chlamydiae are obligate endosymbiont lineages with no measurable impact on host fitness. We tested whether the frequency of both single infections and coinfections of these symbionts were associated with the unpredictability of their soil environments by using symbiont presence-absence data from D. discoideum isolates from 21 locations across the eastern United States. We found that symbiosis across all infection types, symbiosis with Amoebophilus and Chlamydiae obligate endosymbionts, and symbiosis involving coinfections were not associated with any of our measures. However, unpredictable precipitation was associated with symbiosis in two species of Paraburkholderia, suggesting a link between unpredictable conditions and symbiosis.

Longitudinal assessment of extreme climate events in Kinnaur district, Himachal Pradesh, north-western Himalaya, India

It is vital to keep an eye on changes in climatic extremes because they set the stage for current and potential future climate, which usually have a reasonable adverse impact on ecosystems and society. The present study examines the variability and trends in precipitation and temperature across seasons in the Kinnaur district, offering valuable insights into the complex dynamics of the Himalayan climate. Using Climatic Research Unit gridded Time Series (CRU TS) datasets from 1951 to 2021, the study analyzes the data to produce 28 climate indices based on India Meteorological Department (IMD) convention indices and Expert Team on Climate Change Detection and Indices (ETCCDI). Although there may be considerable variation in climate indices in terms of absolute values within different products, there is consensus in both long-term trends and inter-annual variability. Analysis shows that even within a small area, there is variability in the magnitude and direction of historic temperature trends. Initially, the data were subjected to rigorous quality control procedures, which involved identifying anomalies. Statistical analysis like trend analysis, employing Mann-Kendall test and Sen's slope estimator, reveal significant (p < 0.05) increase in consecutive dry days (CDD) at 0.03 days/year and decrease in consecutive wet days (CWD) at 0.02 days/year. Notably, the frequency of heavy precipitation occurrences showed an increasing trend. Changes in precipitation in the Western Himalaya are driven by a complex interplay of orographic effects, monsoonal dynamics, atmospheric circulation patterns, climate change, and localized factors such as topography, atmospheric circulation patterns, moisture sources, land-sea temperature contrasts, and anthropogenic influences. Moreover, in case of temperature indices, there is significant increasing trend observed. Temperature indices indicate a significant annual increase in warm nights (TN90p) at 0.06%/year and warm days (TX90p) at 0.11%/year. Extreme temperature events have been trending upward, with monthly daily maximum temperature (TXx) increasing by 1.5 °C yearly. This study enhances our comprehension of the global warming phenomenon and underscores the importance of acknowledging alterations in the water cycle and their repercussions on hydrologic resources, agriculture, and livelihoods in the cold desert of the northwestern Indian Himalaya.

Underground trees inhabit varied environmental extremes across the Afrotropics

BACKGROUND AND AIMS

Geoxyles, a distinctive feature of Afrotropical savannas and grasslands, survive recurrent disturbances by resprouting subshrub branches from large below-ground woody structures. Underground trees are a type of geoxyle that independently evolved within woody genera of at least 40 plant families in Africa. The environmental limits and determinants of underground tree biogeography are poorly understood, with the relative influence of frost and fire debated in particular. We aim to quantify variability in the niche of underground tree species relative to their taller, woody tree/shrub congeners.

METHODS

Using occurrence records of four Afrotropical genera, Parinari (Chrysobalanaceae), Ozoroa (Anacardiaceae), Syzygium (Myrtaceae) and Lannea (Anacardiaceae), and environmental data of nine climate and disturbance variables, the biogeography and niche of underground trees are compared with their open and closed ecosystem congeners.

KEY RESULTS

Along multiple environmental gradients and in a multidimensional environmental space, underground trees inhabit significantly distinct and extreme environments relative to open and closed ecosystem congeners. Niche overlap is low among underground trees and their congeners, and also among underground trees of the four genera. Of the study taxa, Parinari underground trees inhabit hotter, drier and more seasonal environments where herbivory pressure is greatest. Ozoroa underground trees occupy relatively more fire-prone environments, while Syzygium underground trees sustain the highest frost frequency and occur in relatively wetter conditions with seasonal waterlogging. Lannea underground trees are associated with the lowest temperatures, highest precipitation, and varying exposure to disturbance.

CONCLUSIONS

While underground trees exhibit repeated convergent evolution, varied environments shape the ecology and biogeography of this iconic plant functional group. The multiplicity of extreme environments related to fire, frost, herbivory and waterlogging that different underground tree taxa occupy, and the distinctiveness of these environments, should be recognized in the management of African grassy ecosystems.

A Warm Welcome to the Alps-The Northward Expansion of Trithemis annulata (Odonata, Libellulidae) in Italy

Climate warming has already influenced the distribution, community composition, and phenology of European Odonata. Trithemis annulata had been confined to the southern regions of Italy for over 150 years. In only four decades, it has expanded its range and has recently been observed inhabiting several alpine valleys. A dataset of 2557 geographical distribution data points spanning the years 1825-2023 was compiled using various resources, with the aim to analyse the chrono-story of the expansion of T. annulata. A further aim was to investigate the climatic conditions that best explain its current and future distribution. Over a period of 43 years, the species steadily extended its northern range margin at an approximate rate of 12 km/year. Once it reached the Po Plain, the expansion accelerated to an average speed of 34 km/year. However, its northward shift lagged behind the warming climate as we estimated an average speed of 28 km/year. In the future, the area suitable for T. annulata is expected to significantly increase in Italy. Surprisingly, we did not observe any consistent upward shift. Trithemis annulata has considerably expanded its distribution due to human-induced climate warming. The northernmost populations now inhabit Alpine valleys, potential gateways to central Europe.

Impacts of heat exposure in utero on long-term health and social outcomes: a systematic review

BACKGROUND

Climate change, particularly global warming, is amongst the greatest threats to human health. While short-term effects of heat exposure in pregnancy, such as preterm birth, are well documented, long-term effects have received less attention. This review aims to systematically assess evidence on the long-term impacts on the foetus of heat exposure in utero.

METHODS

A search was conducted in August 2019 and updated in April 2023 in MEDLINE(PubMed). We included studies on the relationship of environmental heat exposure during pregnancy and any long-term outcomes. Risk of bias was assessed using tools developed by the Joanna-Briggs Institute, and the evidence was appraised using the GRADE approach. Synthesis without Meta-Analysis (SWiM) guidelines were used.

RESULTS

Eighteen thousand six hundred twenty one records were screened, with 29 studies included across six outcome groups. Studies were mostly conducted in high-income countries (n = 16/25), in cooler climates. All studies were observational, with 17 cohort, 5 case-control and 8 cross-sectional studies. The timeline of the data is from 1913 to 2019, and individuals ranged in age from neonates to adults, and the elderly. Increasing heat exposure during pregnancy was associated with decreased earnings and lower educational attainment (n = 4/6), as well as worsened cardiovascular (n = 3/6), respiratory (n = 3/3), psychiatric (n = 7/12) and anthropometric (n = 2/2) outcomes, possibly culminating in increased overall mortality (n = 2/3). The effect on female infants was greater than on males in 8 of 9 studies differentiating by sex. The quality of evidence was low in respiratory and longevity outcome groups to very low in all others.

CONCLUSIONS

Increasing heat exposure was associated with a multitude of detrimental outcomes across diverse body systems. The biological pathways involved are yet to be elucidated, but could include epigenetic and developmental perturbations, through interactions with the placenta and inflammation. This highlights the need for further research into the long-term effects of heat exposure, biological pathways, and possible adaptation strategies in studies, particularly in neglected regions. Heat exposure in-utero has the potential to compound existing health and social inequalities. Poor study design of the included studies constrains the conclusions of this review, with heterogenous exposure measures and outcomes rendering comparisons across contexts/studies difficult.

TRIAL REGISTRATION

PROSPERO CRD 42019140136.