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ABSTRACT Aim Location Time Period Methods Major Taxa Studies Results Main Conclusions Given that microbial communities normally comprise generalist and specialist species, there have been limited efforts to estimate the contribution of these sub‐communities to bacterial biogeography regarding ecological assembly processes and nestedness structure. To resolve this gap, we studied the spatial distribution of bacterioplankton communities and their generalist and specialist sub‐communities, as well as the underlying assembly processes.Six lakes span three climate zones in northern China.September 2021.By separately analysing the generalist and specialist sub‐communities from the whole communities, we investigated the relationships between sub‐communities and the entire communities in terms of distance‐decay pattern, nestedness, and assembly processes. As such, we assessed the contribution of generalist and specialist sub‐communities to the biogeographic patterns of the whole communities.Bacterial community.Generalist sub‐communities were more diverse but less abundant than specialist sub‐communities. In line with the whole communities, both types of sub‐communities exhibited distance‐decay relationships at the regional scale, with the slope of specialists being steeper than that of generalists. Additionally, generalist sub‐communities and whole communities also exhibited similar nestedness patterns, in which assemblages from saline water were the subset of those from freshwater. In terms of assembly processes, generalist sub‐communities and whole communities were strongly regulated by homogeneous selection, whereas specialist sub‐communities were mainly shaped by dispersal limitation. More importantly, there was a transition from stochastic to deterministic assembly processes for generalist sub‐communities and whole communities and generalist sub‐communities with increasing total dissolved solids.Relative to the specialists, the assembly processes and nestedness pattern were more altered if the generalists were absent, which implies the higher contribution of generalist sub‐communities on the biogeography of whole communities at the regional scale. [ABSTRACT FROM AUTHOR]

This study introduces a rapid simulation method for assessing seismic damage to building curtain walls at a regional scale. Although the results are approximate, this approach enables quick evaluations, making it an important instrument for emergency responses during disaster situations. This method’s independence from numerical models is a noteworthy advantage. Unlike conventional approaches, it eliminates the need for structural analysis models when evaluating the seismic capacities of curtain walls regionally. Creating reliable structural analysis models is both time-consuming and labor-intensive, primarily due to the detailed design information they require. In contrast, the presented method leverages the wind load capacities for which curtain walls are designed. It is based on the core premise that most curtain walls, primarily designed for wind resistance, possess wind load capacities that could serve as substitutes for their seismic capacities, even if they are not explicitly designed for such seismic loads. To assess the method’s effectiveness, it was applied to seismic damage assessments across regions experiencing varying wind intensities: weak, moderate, and strong. The results suggest the likelihood of curtain walls sustaining seismic damage in regions with weak wind could be five times higher than in regions with strong wind. This underscores the importance of seismic design considerations for curtain walls. Moreover, the findings closely match the actual seismic damage assessment data from a region with a moderate to strong wind intensity. [ABSTRACT FROM AUTHOR]

Heathlands are extensive systems often dominated by slow‐growing and long‐lived woody plants. These systems require longer‐term studies to capture if and how they are changing over time. In 2020, we resurveyed species richness and cover of vascular plant communities in 139 heathlands along the coastline of northern Fennoscandia, first surveyed during 1965–1975. The first survey included six heathland types, each with dominance – a cover of 25% or more – of the dwarf shrubs Calluna vulgaris, Kalmia procumbens, Betula nana, Vaccinium myrtillus and Empetrum nigrum. The two latter heathland types made up 29% and 48%, respectively, of all heathlands. In addition to the dominant dwarf shrubs giving their names to the heathland types, a few other species qualified as dominant. In the resurvey, all the heathland types had E. nigrum as the single dominant species, except for the heathland formerly dominated by B. nana. Most other species had low cover both at the time of the original survey and the resurvey. Also, the heathland types were species poor at the time of the original survey, with an average of eight vascular plant species per 4 m2 and were found equally species poor in the resurvey. Species richness differed between heathland types only at the time of the original survey, and the ratio of species exchange between the two surveys was negatively related to the original cover of E. nigrum. Here we provide a half‐century perspective on vegetation change, during which several heathland types in northern Fennoscandia have changed to Empetrum heathlands, reducing the diversity of heathland types across the Boreal to Arctic landscape. As a native plant, E. nigrum cannot be considered invasive, but its allelopathic capacity has likely already modified these heathland ecosystems and will continue to do so, reducing ecosystem multifunctionality across the region. [ABSTRACT FROM AUTHOR]

In order to address the impact of nuclear accident on the atmospheric environment, an analysis method for the atmospheric diffusion characteristics of radionuclides at different scales was established, which was based on the regional scale weather prediction model weather research forecasting model ( WRF). Taking multiple nuclear power plants in the eastern region as the research object, the atmospheric diffusion distribution characteristics of radionuclides released from nuclear accident in the eastern region and in the nuclear power plant surrounding region were studied. The WRF model was used, which was driven by final reanalysis data (FNL) reanalysis meteorological data, combined with the Gaussian atmospheric diffusion model. The results show that the maximum atmospheric diffusion factor at the regional scale mainly distributes in the western region of the calculation area, and it shows a decreasing trend with increasing distance. The difference of the maximum atmospheric diffusion factor at distances of 500 m and 5 000 m is about one order of magnitude. The maximum atmospheric diffusion factor of nuclear power plant surrounding region scale is one order of magnitude lower than that of the regional scale. The difference of the maximum atmospheric diffusion factor at distances of 500 m and 5 000 m is about one order of magnitude for other nuclear power plants,except Qinshan Nuclear Power Plant. There are significant differences of the direction of the maximum atmospheric diffusion factor among different nuclear power plants due to the influence of meteorological conditions of the plant site. The atmospheric diffusion capacity in eastern coastal region is stronger than that in inland region, which is conducive to the atmospheric transport of radioactive radionuclides. [ABSTRACT FROM AUTHOR]

Accurate, timely, and fine-resolution crop phenology is essential for determining the optimal timing of agronomic management practices supporting precision agriculture and food security. Synthetic Aperture Radar (SAR) methods, unaffected by cloud occlusion, have been widely applied in monitoring maize phenology. Nonetheless, their reliance on manual threshold settings, which depend on the user's expertise, limits their applicability. Furthermore, the neglect of SAR's potential for monitoring other phenological periods (e.g., seven-leaves date (V7), jointing date (JD), tassel date (TD), and milky date (MID)) hinders their robustness, particularly for regional-scale applications. To address these issues, this study used an adaptive dynamic threshold to evaluate the ability of the Sentinel-1 cross-polarization ratio (CR) in detecting the three-leaves date (V3), V7, JD, TD, MID, and maturity date (MD) of maize. We analyzed the effect of incidence angle, precipitation, and wind speed on Sentinel-1 features to identify the optimal feature for time series fitting. Then, we employed linear regression to determine the optimal threshold and developed an adaptive dynamic threshold for phenology detection. This approach effectively mitigated the speckle noise of Sentinel-1 and minimized artificial interference caused by customary conventional thresholds. Finally, we mapped phenology across 8.3 million ha in Heilongjiang Province. The results indicated that the approach has a higher ability to detect JD (RMSE = 11.10 d), MID (RMSE = 10.31 d), and MD (RMSE = 9.41 d) than that of V3 (RMSE = 32.07 d), V7 (RMSE = 56.37 d), and TD (RMSE = 43.33 d) in Sentinel-1. Compared with Sentinel-2, the average RMSE of JD, MID, and MD decreased by 4.14%, 35.28%, and 26.48%. Moreover, when compared to different thresholds, the adaptive dynamic threshold can quickly determine the optimal threshold for detecting each phenological stage. CR is least affected by incident angle, precipitation, and wind speed, effectively suppressing noise to reflect phenological development better. This approach supports the rapid and feasible mapping of maize phenology across broad spatial regions with a few samples. [ABSTRACT FROM AUTHOR]

This work is based on an analysis of the spatial trends and drivers of soil C, N, and P contents and their stocks in relation to latitude, longitude, and altitude. For this purpose, the coniferous forests of Qinghai spruce (Picea crassifolia (Pc)) and Qilian juniper (Juniperus przewalskii (Jp)) within the Qilian Mountains in northwest China were selected as the objects of research. It was found that at the regional scale, the C and N contents in soil from the Pc forests were 1.34 and 1.17 folds higher than those of the Jp forests, respectively, whereas the P content was 0.92 fold lower than that of the Jp forests. Interestingly, the stock of soil C and N in the two forests was consistent, indicating an equivalent role of both in maintaining the regional C and N stocks. Secondly, the soil C and N stocks of Jp were the highest at a low altitude (< 2800 m), which indicated that the Jp forest trees retained high amounts of C and N at an altitude < 2800 m. In addition, the stocks of soil C and N correlated negatively with the latitude and positively with the longitude (P < 0.05). A partial redundancy analysis and random forests regression models showed that the stocks of soil C, N, and P were primarily controlled by the soil properties, particularly the bulk density and nutrient contents. Overall, these results provide insights into the effects of soil and terrain factors on soil C, N, and P stock, thereby providing a foundation for targeted forest conservation and rehabilitation in the Qilian Mountains in the future. [ABSTRACT FROM AUTHOR]

Background: Domingo de Ramos, or Palm Sunday, is a traditional Christian religious event where devotees use ramos, which are bouquets currently elaborated from palm leaves and other natural elements. In various countries, it is assumed this use of biodiversity leads to the depletion of the species involved. However, other important aspects must be considered, including the role of the people who produce and sell these ramos, the associated symbolism that has been overlooked, as well as commercial aspects that have barely been documented. This ethnobotanical study evaluates the regional-scale cultural, biological and socioeconomic aspects associated with Domingo de Ramos in central Mexico from an emic perspective. Methods: Ethnographic and commercial information was obtained through interviews with ramos sellers in 28 municipalities in the state of Hidalgo, Mexico. We specifically sought sociodemographic data regarding the interviewees, as well as information pertaining to the ramos themselves and the palms. These aspects were explored with all of the sellers. The free list method was used to describe the uses and key elements associated with the ramos. Results: Although the ramos are used for religious purposes, they have eight different uses in the daily life of the sellers, the main one being "protection." They serve to protect families, crops and animals, as well as against several diseases. Likewise, they are considered valuable for diminishing strong storms. This belief in the protection conferred by the ramos preserves pre-Hispanic concepts and is combined with their use in blessing corresponding to Western beliefs. Ramos are made from 35 introduced and native plant species and comprise a base (made of palm, wheat or sotol), a "reliquia" (palm, rosemary, chamomile and laurel) and natural or artificial flowers. The ramos sellers are mostly adult women of indigenous origin and heads of family. Conclusions: This study of Domingo de Ramos, carried out at a regional scale, highlights a syncretism that is reflected in both the symbolic importance of ramos palm and in the species used, as well as socioeconomic aspects that had not previously been identified in the study area and reflect the occurrence of complex relationships in non-timber forest products that remain little addressed. [ABSTRACT FROM AUTHOR]

Background: Domingo de Ramos, or Palm Sunday, is a traditional Christian religious event where devotees use ramos, which are bouquets currently elaborated from palm leaves and other natural elements. In various countries, it is assumed this use of biodiversity leads to the depletion of the species involved. However, other important aspects must be considered, including the role of the people who produce and sell these ramos, the associated symbolism that has been overlooked, as well as commercial aspects that have barely been documented. This ethnobotanical study evaluates the regional-scale cultural, biological and socioeconomic aspects associated with Domingo de Ramos in central Mexico from an emic perspective. Methods: Ethnographic and commercial information was obtained through interviews with ramos sellers in 28 municipalities in the state of Hidalgo, Mexico. We specifically sought sociodemographic data regarding the interviewees, as well as information pertaining to the ramos themselves and the palms. These aspects were explored with all of the sellers. The free list method was used to describe the uses and key elements associated with the ramos. Results: Although the ramos are used for religious purposes, they have eight different uses in the daily life of the sellers, the main one being "protection." They serve to protect families, crops and animals, as well as against several diseases. Likewise, they are considered valuable for diminishing strong storms. This belief in the protection conferred by the ramos preserves pre-Hispanic concepts and is combined with their use in blessing corresponding to Western beliefs. Ramos are made from 35 introduced and native plant species and comprise a base (made of palm, wheat or sotol), a "reliquia" (palm, rosemary, chamomile and laurel) and natural or artificial flowers. The ramos sellers are mostly adult women of indigenous origin and heads of family. Conclusions: This study of Domingo de Ramos, carried out at a regional scale, highlights a syncretism that is reflected in both the symbolic importance of ramos palm and in the species used, as well as socioeconomic aspects that had not previously been identified in the study area and reflect the occurrence of complex relationships in non-timber forest products that remain little addressed. [ABSTRACT FROM AUTHOR]

Background and Aims The hart's tongue fern (HTF) complex is a monophyletic group composed of five geographically segregated members with divergent abundance patterns across its broad geographic range. We postulated hierarchical systems of environmental controls in which climatic and land-use change drive abundance patterns at the global scale, while various ecological conditions function as finer scale determinants that further increase geographic disparities at regional to local scales. Methods After quantifying the abundance patterns of the HTF complex, we estimated their correlations with global climate and land-use dynamics. Regional determinants were assessed using boosted regression tree models with 18 potential ecological variables. Moreover, we investigated long-term population trends in the USA to understand the interplay of climate change and anthropogenic activities on a temporal scale. Key Results Latitudinal climate shifts drove latitudinal abundance gradients, and regionally different levels of land-use change resulted in global geographic disparities in population abundance. At a regional scale, population isolation, which accounts for rescue effects, played an important role, particularly in Europe and East Asia where several hot spots occurred. Furthermore, the variables most strongly influencing abundance patterns greatly differed by region: precipitation seasonality in Europe; spatial heterogeneity of temperature and precipitation in East Asia; and magnitudes of past climate change, temperature seasonality and edaphic conditions in North America. In the USA, protected populations showed increasing trends compared with unprotected populations at the same latitude, highlighting the critical role of habitat protection in conservation measures. Conclusions Geographic disparities in the abundance patterns of the HTF complex were determined by hierarchical systems of environmental controls, wherein climatic and land-use dynamics act globally but are modulated by various regional and local determinants operating at increasingly finer scales. We highlighted that fern conservation must be tailored to particular geographic contexts and environmental conditions by incorporating a better understanding of the dynamics acting at different spatiotemporal scales. [ABSTRACT FROM AUTHOR]

While it is well accepted that climate change and growing water needs affect long-term sustainable water resourcesmanagement, performing accurate simulations of water cycle and energy balance dynamics at regional scale remains a challenging task. Traditional Soil-Vegetation-Atmosphere-Transfer (SVAT) models are used for numerical surface water and energy simulations. These models, by conception, do not account for the groundwater lower boundary that permits a full hydrosystem representation. Conversely, while addressing important features such as subsurface heterogeneity and river-aquifer exchanges, groundwater models often integrate overly simplified upper boundary conditions ignoring soil heating and the impacts of vegetation processes on radiation fluxes and root-zone uptakes. In this paper, one of the first attempts to jointly model water and energy fluxes with a special focus on both surface and groundwater at the regional scale is proposed on the Seine hydrosystem (78,650 km²), which overlays one of the main multi-aquifer systems of Europe. This study couples the SVAT model ORCHIDEE and the process-based hydrological-hydrogeological model CaWaQS, which describes water fluxes, via a one-way coupling approach from ORCHIDEE toward CaWaQS based on the blueprint published by de Marsily et al. [1978]. An original transport library based on the resolution of the diffusion/advection transport equation was developed in order to simulate heat transfer in both 1D-river networks and pseudo-3D aquifer systems. In addition, an analytical solution is used to simulate heat transport through aquitards and streambeds. Simulated ORCHIDEE surface water and energy fluxes feed fast surface runoff and slow recharge respectively and then is used as CaWaQS forcings to compute river discharges, hydraulic heads and temperature dynamics through space and time, within each of the hydrosystem compartments. The tool makes it possible to establish a fully consistent water and energy budget over a period of 17 years. It also simulates temperature evolution in each aquifer and evaluates that river thermal regulation mostly relies by order of importance on short wave radiations (109.3W·m-2), groundwater fluxes (48.1W·m-2) and surface runoff (22.7W·m-2). [ABSTRACT FROM AUTHOR]

SOC storage (SOCS) plays a vital role in global climate change. Understanding the spatial pattern and features of soil organic carbon (SOC) and its influencing factors is important for increasing SOC fixation. However, few studies exist on the organic carbon reserves of farmland on a regional scale. This study revealed the SOCD and SOCS values and distribution using Hubei Province as a sampling region. The results demonstrated that the spatial distributions of farmland system carbon storage and density were uneven, and the spatial heterogeneity was related to geography, cultivated area, and soil type. The SOCD ranged from 0.559 to 10.613 kg/m2, with an average of 3.3710 ± 0.0337 kg/m2, and the soil carbon reserve of the farmland system was ~17.81 Tg. The SOCD varied with topography and soil type: in mountainous cultivated land, it was generally higher than that in hilly land and in the plains. However, the plain cultivated areas contained the highest carbon reserves. Within the farmland system, paddy soil, the dominant soil type, exhibited higher SOCD and larger SOC storage capacity. Soil types with the same physicochemical properties exhibited different organic carbon storage capacity in different geomorphic and regional environments. Specifically, paddy soil was found to have higher SOCD and SOCS than the other soil types, and its soil carbon storage capacity was high; the SOC reserves of wheat-rice tillage were the largest among the main tillage methods. Boosting the soil carbon sink requires fundamental improvement in soil properties by improving soil texture, using conservation tillage to increase soil organic matter, and reducing unnecessary human interference. [ABSTRACT FROM AUTHOR]

The Orbiting Carbon Observatory 2/3 (OCO-2/3) employs a full-physics inversion algorithm and estimates the column-averaged dry air mole fraction of carbon dioxide (XCO 2). This research focuses on the spatiotemporal coverage and associated uncertainties of OCO-2/3's XCO 2 measurements within the Chinese region. We undertook an extensive statistical examination of the daily, weekly, 16-day, and monthly spatiotemporal coverage of XCO 2 across China, employing data from both OCO-2 and OCO-3 and their amalgamated datasets. Additionally, we used a posterior error analysis method to rigorously evaluate the uncertainties induced by various input parameters in the XCO 2 inversion model across different regions in China. Our findings reveal that OCO-2's spatial coverage spans 2.3–53.8% in China at a spatial resolution of 1° × 1°, and OCO-3's spatial coverage spans 3.3 and 47.4% across these time scales in China. Notably, the combined coverage rates of both satellites are significantly higher, ranging from 5.4 to 72.6%. Our analysis also reveals a gradual decrease in XCO 2 coverage and inversion rates from north to south and west to east across China. A significant portion of the uncertainties in OCO-2/3 XCO 2 measurements, over 90%, were attributed to primary error sources such as instrument, aerosol, and CO 2 prior profile. Aerosol-induced errors show regional variations, with higher levels observed in Southeast China. Compared to TCCON data, the accuracy of XCO 2 measurements in the two Chinese sites was lower than the global average. Our research identifies the spatiotemporal distribution and uncertainty decomposition of carbon satellites at a regional scale in China, providing an essential reference for future research. [Display omitted] • OCO-2&3 boosted China's XCO 2 coverage by 5.4%, 29.3%, 50.8%, and 72.6% for daily, weekly, 16-day, and monthly scales. • OCO-2/3 XCO 2 coverage and efficiency decline regionally, decreasing from north to south and west to east. • Key OCO-2/3 error sources: instrument, aerosol, and CO 2 prior profile contribute to over 90% of XCO 2 errors. • Aerosol errors, 20% of XCO 2 uncertainties, are higher in Southeast China, with distinct regional variations. [ABSTRACT FROM AUTHOR]

The vectorization of historical maps is an important scientific issue for understanding the dynamics of change recorded by territories. Historical maps are potentially an excellent source of data for characterizing river changes at large scales. The use of vectorized data is essential for such characterization, as well as for highlighting changes in the planform alignment of such reaches over time. At a regional network scale of several thousand kilometers of river, such work requires the vectorization of several hundred or even thousands of maps. This work proposes an automated vectorization procedure for the hydrographic network detailed in the cartographic resources of the IGN (the French National Mapping Agency). The ultimate goal is to use these historical maps to track the planform evolution of the elementary landscape units (water, bare banks, and riparian vegetation) that constitute river corridors at the basin network scale. The Historical Maps Vectorization Toolbox was developed to automatically vectorize river corridor objects (sediment banks, water surfaces, and vegetation polygons) with a high level of accuracy. The toolbox works with a 2-step process: first it classifies the colors detected on the map, then it reconstructs the objects of the fluvial corridor. We also demonstrate a practical use of the toolbox through measuring changes in the surface area of river networks of several hundred kilometers. [ABSTRACT FROM AUTHOR]

Sense of place provides a strategy to identify qualities of landscape change in rural areas undergoing urban development, yet a scale to assess such qualities has not been developed. Research on place meanings tends to draw from either an interpretivist or positivist approach but does not integrate them. This research integrates the two approaches with a mixed-methods design that resulted in the first scale of regional place meanings for two counties undergoing landscape change on the urban-rural fringe. We conducted interviews and focus groups with stakeholders in Jasper County, IA and Will County, IL, followed by a household survey to assess the psychometric properties of our scale. Eight regional place meanings were identified to characterize the reasons why residents developed connections with places. This paper responds to previous calls for research to merge different philosophical paradigms and it directs attention within the place scholarship to the study of rural communities. [ABSTRACT FROM AUTHOR]

Despite decades of investigation, there are few ecological studies on the Amazonian fish fauna that have looked both at the main factors shaping the fish assemblages at a regional scale and used environmental, spatial and historical approaches simultaneously. The current study aimed to measure the relative influence of environmental aspects, spatial distance and historical processes on fish genera assemblages in the upper Amazon basin (Peru and Ecuador). Climate, slope and elevation were used as environmental variables; watercourse was used to represent the spatial distance between sites and phylogenetic relationships were used as a proxy for historical processes. A partial Redundancy Analysis (pRDA) was used to compute the influence of each group of factors (environment, space and historical processes) on the fish genera assemblage. Our analysis indicated historical processes had the greatest influence on fish genera assemblages, followed by spatial distance and environment. Such patterns are most likely due to the extinction processes caused by environmental filters generated by the Andean orogeny and possible speciation in each sub-basin. The results suggest that the use of phylogeny, in addition to environment and space, provides a useful tool with which to assess the drivers responsible for fish assemblages at a regional scale. [ABSTRACT FROM AUTHOR]

• Neglecting SW-GW feedback in groundwater flow modelling is highly likely to result in the simulation of overly deep (disconnected) water tables in shallow regional aquifer systems. • The consideration of two-way feedback is of larger importance when simulating low-flow periods compared to high-flow periods. • The inclusion of SW-GW feedback may reduce the potential of water table elevation observations to constrain hydraulic conductivity for model calibration. Groundwater flow models are increasingly considered for the regional scale simulation of hydraulic heads and water table elevation. In the most complete configuration, models explicitly simulate two-way interactions between surface water (SW) and groundwater (GW) to reproduce and forecast both SW and GW water levels. In most regional scale groundwater models, however, SW-GW interactions are represented by simplified boundary conditions that only allow one-way interaction from SW to GW, neglecting most of the dynamic exchange fluxes between SW and GW. To evaluate the potential consequences of such simplifications on the simulation of regional GW levels, we compare two models on a 36,900 km2 regional aquifer system in Southern Quebec. One model explicitly simulates both SW and GW flow with two-way SW-GW feedback and the other model only simulates GW flow with a surface boundary flux to represent a one-way interaction with the land surface. Both models are developed with the same numerical code to ensure that the only differences are the representation of SW water flow and SW-GW feedback. The one-way model simulates overall deeper water tables because it removes all exfiltrated groundwater from the system once it exits the subsurface, therefore not allowing exfiltrating groundwater to re-infiltrate. This effect is most pronounced in areas where the water table is close to the surface and for low-flow periods. The inclusion of two-way feedback also reduces the sensitivity of simulated GW levels to the magnitude of the hydraulic conductivity. This result highlights the need for additional data on other system states to improve the calibration of regional scale models that explicitly simulate two-way SW-GW interactions. [ABSTRACT FROM AUTHOR]

• A process-based water quality model was constrained with two datasets. • One dataset was intensively sampled, one was sparsely sampled. Both had many sites. • Sparse sites were chosen for water quality data up to 80th percentile of flow. • The results showed the model converged on similar solutions with both datasets. • Sparse sampling may be adequate for process model calibration in Great Lakes area. Model parameter calibration is an important step in process-based watershed water quality modelling. Calibration is commonly performed using readily available water quality data from long-term monitoring programs that collect samples periodically at a relatively low frequency (i.e. monthly). Higher frequency synoptic and targeted event data is becoming available from more intensive monitoring programs, yet there remains little consensus on whether relatively lower frequency data are sufficient to constrain process-based watershed water quality models. To investigate the effects of using water quality data from differing sampling regimes for calibration, we use an implementation of HYPE (HYdrological Predictions for the Environment), a process-based watershed water quality model, in Southern Ontario, Canada. HYPE was calibrated with two stream water quality datasets, one associated with the long-term Ontario Provincial (Stream) Water Quality Monitoring Network and characterized by routine approximately monthly sampling frequency, and one associated with the Multi-Watershed Nutrient Study and characterized by semi-regular synoptic sampling during baseflow and at increased frequency (∼4 to 8 h) during event flow. Performances varied widely between sites, with validation ranges of daily predictions having Nash-Sutcliffe Efficiencies (NSE) from > −1 to 0.48 for flow and > −1 to 0.98 for total Phosphorus. Medians for daily data during validation ranged from 0.15 to 0.24 for flow and from 0.19 to 0.36 for total phosphorus. We found that model performance and simulated total phosphorus loads were similar for the two calibration datasets, potentially suggesting that the dataset with approximately monthly water quality sampling was adequate to constrain the HYPE model. We attribute this to a combination of similar levels of statistical variability in the calibration datasets and prior knowledge in the HYPE model structure. Furthermore, while model performance was similar when HYPE was calibrated with datasets of differing sampling strategies, there was a large range in model performance within each modelling domain. Results suggest that this range in performance could be due in part to poor representation of cold-weather processes in the HYPE model, as sites with higher mean annual temperature and fewer freezing days had better model performance. [ABSTRACT FROM AUTHOR]

Rockfalls are among the natural hazards that endanger infrastructure, cause major economic disruptions, and threaten human lives. These phenomena result from long-term geological processes such as tectonic rock deformation or weathering, but the actual rockfall itself occurs suddenly, usually without warning. The triggering mechanisms are complex and difficult to trace. In this study, we investigated the triggering mechanisms of more than 2100 small rockfalls that occurred in 2021 in Slovenia, Europe, along the 51,000 km long national road network. We analyzed their spatial and temporal characteristics, as well as the triggering mechanisms of their occurrence, based on different weather scenarios. Multiple data mining methods were used to investigate triggering conditions, and scenario analyses were used to understand the triggering mechanisms. Most small rockfalls in 2021 were recorded in winter and spring at a density of 1 rockfall per 10 km2. The results show that winter weather conditions have the greatest potential for triggering small rockfalls in Slovenia, both in terms of spatial extent and frequency of triggering weather conditions. The analysis showed that summer storms are an important but indeterminant factor for the occurrence of small rockfalls. Among the scenarios tested, the winter scenario, which includes a combination of antecedent precipitation, snowmelt, and freeze‒thaw cycles a few days before the event, was able to predict 72% of the events in the colder season. [ABSTRACT FROM AUTHOR]

Aiming at the problem that it is difficult to quantitatively describe the vulnerability of water and soil environment of artificial oasis in arid areas, taking Jingtaichuan Electric Power Irrigation District in Gansu Province as the research area, through data collection and analysis, the soil salinity and land use types that directly participate in driving the regional water and soil environment differentiation are selected., vegetation coverage, soil conductivity, surface irrigation, groundwater salinity, groundwater depth, altitude, slope, average annual precipitation, average annual evaporation, average annual temperature 12 indicators, based on cloud theory to improve the analytic hierarchy process The weight of each index is determined, and ArcGIS software is used as the technical platform to superimpose the spatial distribution results of each index according to the corresponding weight, so as to realize the visual expression of the spatial differentiation characteristics of soil and water environment vulnerability in the study area. The results show that the vulnerability of soil and water environment in the study area is basically maintained at grades I to III, and the overall spatial distribution pattern is low in the west and high in the east. Severely vulnerable and extremely vulnerable areas are concentrated in the closed hydrogeological unit in the eastern part of the irrigation area; soil salinity, Vegetation coverage, land use type, and surface irrigation are the main factors that affect the vulnerability of soil and water environment at the regional scale. [ABSTRACT FROM AUTHOR]

The large area estimation of forest canopy closure (FCC) using remotely sensed data is of high interest in monitoring forest changes and forest health, as well as in assessing forest ecological services. The accurate estimation of FCC over the regional or global scale is challenging due to the difficulty of sample acquisition and the slow processing efficiency of large amounts of remote sensing data. To address this issue, we developed a novel bounding envelope methodology based on vegetation indices (BEVIs) for determining vegetation and bare soil endmembers using the normalized differences vegetation index (NDVI), modified bare soil index (MBSI), and bare soil index (BSI) derived from Landsat 8 OLI and Sentinel-2 image within the Google Earth Engine (GEE) platform, then combined the NDVI with the dimidiate pixel model (DPM), one of the most commonly used spectral-based unmixing methods, to map the FCC distribution over an area of more than 90,000 km2. The key processing was the determination of the threshold parameter in BEVIs that characterizes the spectral boundary of vegetation and soil endmembers. The results demonstrated that when the threshold equals 0.1, the extraction accuracy of vegetation and bare soil endmembers is the highest with the threshold range given as (0, 0.3), and the estimated spatial distribution of FCC using both Landsat 8 and Sentinel-2 images were consistent, that is, the area with high canopy density was mainly distributed in the western mountainous region of Chifeng city. The verification was carried out using independent field plots. The proposed approach yielded reliable results when the Landsat 8 data were used (R2 = 0.6, RMSE = 0.13, and 1-rRMSE = 80%), and the accuracy was further improved using Sentinel-2 images with higher spatial resolution (R2 = 0.81, RMSE = 0.09, and 1-rRMSE = 86%). The findings demonstrate that the proposed method is portable among sensors with similar spectral wavebands, and can assist in mapping FCC at a regional scale while using multispectral satellite imagery. [ABSTRACT FROM AUTHOR]

Farming systems under contrasting management practices can contribute differently to the delivery of bundles of ecosystem services (ES) in agricultural landscapes. Low intensity farming systems, such as High Nature Value farmlands, are expected to deliver a wider range of ES, whereas landscapes under more intensive management are expected to deliver mainly provisioning services. Understanding the management practices associated with desirable outcomes in terms of biodiversity and ES in agricultural landscapes is needed. Our research aimed to understand the links between the delivery of ES bundles associated with agricultural landscapes, and their socio-ecological drivers, using a region in northern Portugal as a case study. Based on publicly available data on ecosystems services and drivers, we analyzed ES associations, delineated ES bundles, and investigated their relationship with socioecological drivers. Overall, our results suggested spatial trade-offs between landscapes delivering provisioning services of high economic value, and landscapes delivering a more balanced set of multiple ES. Bundle analysis highlighted an association between higher landscape multifunctionality and higher values of landscape complexity, higher number of farmers, and farm sizes. Our results reflected the complexity of social and ecological factors operating at the landscape level, pinpointed landscapes with higher multifunctionality and disclosed the conditions underlying their occurrence. The results also highlighted the importance of low-intensity farming systems, namely those supporting High Nature Value farmlands, for the delivery of a wider range of ES at the landscape scale. [ABSTRACT FROM AUTHOR]

Animal agriculture is a major consumer and generator of both macro- and micronutrients. Intensification and regional concentration of animal production, due to economic and logistical advantages, have altered nutrient fluxes in agriculture systems, causing increased stock of nutrients in soils and, consequently, their emission to air and transport to surface water and groundwater. Established nutrient and manure planning frameworks, while effective in addressing nutrient point sources and using manure to enhance fertility and soil quality, have not been wholly successful in addressing farmand region-scale challenges with nutrient concentrations. This review article addresses nutrient management issues associated with modern animal agriculture by advancing the use of nutrient budgets and balances. This is accomplished by establishing core concepts for nutrient budgets and balances as they apply to animal agriculture. Relevant spatial scales for these budgets are reviewed, including field, whole-farm, and watershed scales, along with proposed methodologies and data sources for each. This study also identifies existing region- and commodity-specific metrics (when available) for use as thresholds for corrective action toward more balanced nutrient budgets. Finally, recommendations for the community of practitioners, researchers, and educators are provided to address nutrient imbalance in animal agriculture systems. At farm and region scale, nutrient balance investments will be needed to strengthen accounting methodologies, develop appropriate data sources for measurements, identify thresholds for action, and apply the methods in appropriate settings and decisions. Data availability and uncertainty are recognized as key limitations facing wider adoption of these concepts, particularly considering data ownership and privacy concerns. The lack of transparent datasets that capture current animal production practices and their impact on manure composition and nutrient cycling is a gap facing these methodologies. The lack of engagement by practitioners and producers in the development phase of such tools greatly affects their adoption and utility. The need for continued engagement in establishing accepted methodologies, training, data collection, and education are crucial to establish farm- and region-scale methods and measure their value to nutrient planning over time. [ABSTRACT FROM AUTHOR]

To extract regional winter wheat planting area using higher-resolution satellite imagery still faces many challenges due to large data size and long processing time in traditional remote sensing classification. Google Earth Engine (GEE), a cloud computing analysis platform based on global geospatial analysis, provides a new opportunity for rapid analysis of remote sensing data. In this study, high-quality Landsat-8 imagery was used to extract the winter wheat planting area from the Huang-Huai-Hai Plain in China. The random forest algorithm was used to identify and map the winter wheat sown in 2019 and harvested in 2020, and Sentinel-2 imagery was used to verify the results. The spectral indices, texture, and terrain features of the image were derived, and their contribution to the classification accuracy of winter wheat was evaluated by scoring. Then the top nine features were selected to form an optimal feature subset. Comparing the set of thirty-four features and the optimized feature subset as the input variables of the random forest classifier, the results show that the accuracy difference between the two feature classification schemes is small, but the classification effect of all feature sets is slightly better than the optimal feature subset. The overall classification accuracy of sample plots verification was 86%-95%, the Kappa coefficient was between 0.7 and 0.85, and the percentage error of the total area was 5.42%. The research demonstrates a reliable method for mapping a wide range of winter wheat planting area, and provides a good prospect for exploring the precise mapping of other crops, which is of great significance to crop monitoring and agricultural development. [ABSTRACT FROM AUTHOR]

The outstanding diversity of Amazonian forests is predicted to be the result of several processes. While tree lineages have dispersed repeatedly across the Amazon, interactions between plants and insects may be the principal mechanism structuring the communities at local scales.Using metabolomic and phylogenetic approaches, we investigated the patterns of historical assembly of plant communities across the Amazon based on the Neotropical genus of trees Inga (Leguminosae) at four, widely separated sites.Our results show a low degree of phylogenetic structure and a mixing of chemotypes across the whole Amazon basin, suggesting that although biogeography may play a role, the metacommunity for any local community in the Amazon is the entire basin. Yet, local communities are assembled by ecological processes, with the suite of Inga at a given site more divergent in chemical defences than expected by chanceSynthesis. To our knowledge, this is the first study to present metabolomic data for nearly 100 species in a diverse Neotropical plant clade across the whole Amazonia. Our results demonstrate a role for plant–herbivore interactions in shaping the clade's community assembly at a local scale, and suggest that the high alpha diversity in Amazonian tree communities must be due in part to the interactions of diverse tree lineages with their natural enemies providing a high number of niche dimensions. [ABSTRACT FROM AUTHOR]

Aim: Ectomycorrhizal (ECM) fungal community structures can vary across sites at a regional scale (>1,000 km), affected by abiotic and biotic environments, dispersal abilities of the fungi, or ecological drift, even among forests of the same host tree species. The spatial patterns of such variation may differ among associated host species and their growth environments, but our knowledge about this remains limited. In the present study, we aimed to investigate whether the ECM fungal community structures (i.e. species richness and species composition) at the regional scale and their driving factors vary across hosts. Location: Japan. Taxon: ECM fungi associated with Fagus crenata and Castanopsis sieboldii. Methods: Using DNA metabarcoding of fine roots, the ECM fungal communities of 15 Fagus crenata forests across their distribution range were characterised. The resultant community structure of ECM fungi, as well as the relative effects of edaphic, climatic and spatial factors on community composition were compared with those of 12 Castanopsis sieboldii forests investigated in a previous study. Results: ECM fungal community composition differed between the two Fagaceae hosts. The spatial pattern of ECM fungal community composition also differed between hosts. Specifically, the spatial variation in community composition across sites was smaller in F. crenata forests than in C. sieboldii forests. The spatial pattern of ECM fungal communities of F. crenata forests was explained by climatic and edaphic factors, while that of C. sieboldii forests was explained by spatial and edaphic factors. Main conclusions: On a regional scale in Japan, the spatial pattern of ECM fungal communities and its driving factors varied between two Fagaceae host species. Our results provide an example that the difference in associated host leads to the difference in environmental response among ECM fungal communities. [ABSTRACT FROM AUTHOR]

To fight the power consumption conflicts at the regional scale, rooftop solar photovoltaics (RTSPV) in rural areas is considered as a critical way. In this study, we constructed a sophisticated framework for evaluating the regional RTSPV power generation potential of rural areas. Focusing on Jiangsu Province, the rural RTSPV power generation potential was evaluated. Then, the generation potential was compared with electricity demand to describe the spatial heterogeneity of the supply and demand situation, and proposed the pathways to alleviate the regional consumption conflicts. The results showed that the total RTSPV power generation potential of rural areas in Jiangsu Province is 202.91 TWh, which can meet the electricity demand of rural areas in this province. From the perspective of supply and demand, the conflicts between rural RTSPV power generation and electricity demand will be aggravated, especially in areas of rapid economic development. The rural RTSPV power generation of Suzhou, Wuxi, and Changzhou is far low the actual demand for electricity. While for the city with significant disparities between urban and rural areas, the development of rural RTSPV can effectively alleviate the power consumption conflicts. In particular, the rural RTSPV power generation in Xuzhou can meet the demand of total electricity. [ABSTRACT FROM AUTHOR]

• Process-based model was extended to link with plastic debris model in regional scale. • Model simulated seasonal variations of riverine plastic transport in Asian region. • Settling and resuspension affect plastic mobilisation and intra-annual variability. • Impact of waste plastic trade on change in riverine plastic transport was evaluated. • Results helped to quantify trade-off of waste plastic between export and import. Environmental contamination by plastics has been receiving considerable attention from scientists, policy makers and the public, and waste plastic trade has become a major social issue in recent years. In this study, the authors applied eco-hydrology model coupled with plastic debris model in Asian regions by including effect of waste plastic trade in order to clarify this research gap. Result showed settling and resuspension of plastic particles have great impact on mobilisation of plastic and its high intra-annual variability, and that the plastic transport becomes drastically higher during the flood periods accounting for most of the annual flux. In particular, the model simulated the size distribution of plastics in the water and riverbed sediment of the global major rivers and showed that the coarser particles are more distributed in the riverbed than those in the water. Further, the authors evaluated impact of waste plastic trade on change in riverine plastic transport by newly including effect of plastic trade on Mismanaged plastic waste (MPW) in the extension of previous studies. They newly modified to calculate municipal plastic waste by including these effects of plastic trade and disposal, and revised MPW assuming that the import of plastics is treated as the same as the export of plastics as the first approximation, which is the innovation of this study. The modified MPW became smaller than the original one in the exporting countries and vice versa in the importing countries. Further, this analysis clarified waste plastic trade has promoted decrease of riverine plastic transport in Japanese rivers, its slight increase in Yangtze, Yellow, and Ganges Rivers, and almost its constant in Mekong, Indus, Irrawaddy, and Brahmaputra Rivers. Recently, there is a growing progress in compiling existing research results and setting policy making in various countries under the umbrella of an intergovernmental negotiating committee (INC) on plastic pollution. The present results help to quantify plastic trade-off about impact of export and import of waste plastic on plastic dynamics in regional scale and to support the achievement of sustainable development goals (SGDs). [Display omitted] [ABSTRACT FROM AUTHOR]

Aim: To test the hypothesis that spatial variations in climate and land use explain the distribution and diversity of reptiles' ecological traits in a biodiversity hotspot of the Mediterranean basin. Location: French Mediterranean region. Taxon: Reptiles (25 species). Methods: We defined 288 species assemblages from 27,858 opportunistic occurrence records within 10 × 10 km square grid cells. Using a RLQ analysis, we investigated the distribution of nine ecological traits describing reptiles' reproductive, dietary and behavioural strategies along environmental gradients formed by 10 climatic, topographic and land‐use descriptors. After homogenizing survey effort through rarefaction, we used generalized additive models to assess variations in species richness and several measures of functional diversity and composition along these gradients. Results: Although ecological traits were not structured by environmental gradients at a species level, species richness and all measures of functional diversity varied nonlinearly with climate, elevation and secondarily land use. Species richness and body size peaked at intermediate altitudes, indicating a climatic transition zone between Mediterranean and medio‐European herpetofaunas. Conversely, functional diversity increased from Mediterranean plains, dominated by urbanization and agriculture, to higher elevations. These changes were associated with shifts towards less productive, more diurnal and more forest‐related species. Main conclusions: Species‐scale patterns are insufficient to assess regional variations in ecological traits in space. Our results support the hypothesis that climatic limitations in species' distributions, rather than environmental filtering, explain the taxonomic and ecological diversity of reptiles at a regional scale. Although secondary to climate, land abandonment has a strong structuring effect which may contribute to homogenize the composition of reptile assemblages. [ABSTRACT FROM AUTHOR]

The aim of this paper is to achieve a quantitative assessment of rockfall protection forest efficiency at regional scale, considering site specific forest, morphological and lithological parameters. At first, a semi-automatic GIS-based method, integrated with a multi-scenario 3D-rockfall model realized by using the simulation code HY-STONE, was used to map protection forests of Regione Lombardia (central Italian Alps). For each different forest type, a rockfall protective efficiency was assessed by using empirical (energy line angle) and modelling (HY-STONE) approaches. The empirical approach shows an increase of the energy line angle value from about 36° for the bare slopes to over 40° in forested slopes, with a value ranging from 37° to 44° for different forests types. The modelling approach is based on a new efficiency index EEI ranging from 0 (minimum efficiency, equal to no forest condition) to 1 (maximum efficiency): the efficiency of different forest types ranges from 0.08 to 0.98 by using average values of the controlling parameters. To modulate the efficiency in each single forest at regional scale, a set of parametric simulations was performed to evaluate the effects of controlling parameters. The parametric simulations show that block volume, slope gradient, DBH (diameter at breast height) and forest density are the most important parameters at controlling the efficiency. These parameters were used within a multiple linear regression function to associate a protection efficiency to each specific protection forest in the regional map. This allows to discriminate quantitatively the individual forests according to their actual efficiency. Most of the protection forest area (46%) shows an efficiency greater than 0.50 and only the 24% of the total covered area shows a value lower than 0.25. [ABSTRACT FROM AUTHOR]

Fluvial corridor quality assessment requires that historical data be collected at a regional scale. In this article, our goal is to assess potential map resources to explore riverscape changes at a regional network scale and to define key issues in using an automated vectorization protocol to characterize such changes on such a large scale. We consider IGN's Nouvelle Carte de France a potentially good resource for our objective of two-date (oldest + actual vector database) comparisons on 1:20,000–1:25,000 scale maps, notably when applied at a regional scale. The French IGN corpus is a good example of topographic maps that were produced in the twentieth century in Europe with fairly homogeneous data over a whole national territory. Moreover, the digitization and georeferencing processes applied by IGN are very accurate. The evolution of conventional features is not as significant for the hydrographic theme and should not be a problem for automatic vectorization. The potential temporal coverage is from 1922 to 1993, but the complexity of the sheet divisions, partial revisions, and the heterogeneity of coverage over time prevent multidate analysis. [ABSTRACT FROM AUTHOR]

Aim: The protection of phylogenetic diversity has become a priority in conservation biology, but its achievement requires a detailed understanding of (a) hotspots of phylogenetic diversity on a management‐relevant scale and (b) the land use and climate factors determining local phylogenetic diversity. In this study, we identified spatial patterns of taxonomic and phylogenetic diversity and their environmental drivers. Location: Bavaria, Germany. Methods: To map the cross‐taxon phylogenetic diversity, we combined species distribution data obtained from country‐wide monitoring programmes and phylogenetic trees of birds, bats, dragonflies, grasshoppers and butterflies and calculated the phylogenetic diversity standardized by species richness. Generalized additive models were used to test the effects of land use and climate on phylogenetic diversity. We identified hotspots of phylogenetic diversity and assessed the extent to which established protected areas in Bavaria cover these hotspots. Results: High coverage by urban areas, arable land and water bodies negatively affected the phylogenetic diversity of most species groups. The phylogenetic diversity of birds increased with increasing meadow cover. Climate did not influence the phylogenetic diversity of the studied groups. We identified 10 regional hotspots that contained the highest standardized phylogenetic diversity across the examined species groups. There was a strong mismatch between hotspots of phylogenetic diversity among the species groups. Protected areas (national parks, natural reserves and areas of the Flora‐Fauna‐Habitat Directive) overlapped only to ~9.6% with these hotspots of standardized phylogenetic diversity. Main conclusions: Cross‐taxon approaches are required to identify hotspots of phylogenetic diversity at a management‐relevant scale. At regional scales, land use was more important than climate in determining phylogenetic diversity. Our study highlights the importance of involving land users into strategies for protecting phylogenetic diversity. [ABSTRACT FROM AUTHOR]

Groundwater level fluctuations are caused by spatial and temporal superposition of processes within and outside the aquifer system. Most of the subsurface processes are usually observed on a small scale. Upscaling to the regional scale, as required for future climate change scenarios, is difficult due to data scarcity and increasing complexity. In contrast to the limited availability of system characteristics, high-resolution data records of groundwater hydrographs are more generally available. Exploiting the information contained in these records should thus be a priority for analysis of the chronical lack of data describing groundwater system characteristics. This study analyses the applicability of 63 indices derived from daily hydrographs to quantify different dynamics of groundwater levels in unconfined gravel aquifers from three groundwater regions (Bavaria, Germany). Based on the results of two different skill tests, the study aids index selection for different dynamic components of groundwater hydrographs. [ABSTRACT FROM AUTHOR]

BACKGROUND Multi‐elements have been widely used to identify the geographical origins of various agricultural products. The objective of this study was to investigate the feasibility of identifying the geographical origins of peanut kernels at different regional scales by using the multi‐element fingerprinting technique. The concentrations of 20 elements [boron (B), magnesium (Mg), phosphorus (P), potassium (K), calcium (Ca), etc.] were determined in 135 peanut samples from Jilin Province, Jiangsu Province, and Shandong Province of China. Data obtained were processed by one‐way analysis of variance (ANOVA), principal components analysis (PCA), k nearest neighbors (k‐NN), linear discriminant analysis (LDA), and support vector machine (SVM). RESULTS: Peanut kernels from different regions had their own element fingerprints. The k‐NN, LDA, and SVM were all suitable to predict peanut kernels according to their grown provinces with the total correct classification rates of 91.2%, 91.1%, and 91.1%, respectively. While SVM was the best to identify different grown cities of peanut kernels with the prediction accuracy of 91.3%, compared to 72.2% and 78.3% for k‐NN and LDA, respectively. CONCLUSION: It was an effective method to identify producing areas of peanut kernels at different regional scales using multi‐element fingerprinting combined with SVM to enhance regional capabilities for quality assurance and control. © 2020 Society of Chemical Industry [ABSTRACT FROM AUTHOR]

Results of the comparison of organic carbon stocks in the automorphic and semihydromorphic forest soils are discussed. The database includes information on 289 soil profiles in the forest zone of European Russia. On the average, the total organic carbon pool (including forest litter) in semihydromorphic soils is three times higher than that in automorphic soils. The difference decreases with an increase in the thickness of the considered soil layer from 3.2 times for the layer of 0–30 cm to 2.6 times for the layer of 0–100 cm. The greatest difference in carbon stocks is noted for the organic horizons; in semihydromorphic soils, the carbon storage in them averages 73 ± 8.2 t C/ha; in automorphic soils, it is seven times smaller. The neglect of the contribution of semihydromorphic soils results in underestimation of the total soil organic carbon stock of the region. The degree of underestimation depends on the soil cover pattern of particular areas and on the thickness of the considered soil layer. Calculations made for Karelia show that the underestimation of organic carbon stocks in various landscapes ranges from 10 to 40%. For the total area of this republic, it is estimated at 22, 19, and 13% for the soil layers of 0–30, 0–50, and 0–100 cm, respectively. A comparative analysis of known pedotransfer functions for calculating soil bulk density shows that the best results (RMSE = 0.15; R2 = 0.36) for mineral horizons of forest soils in European Russia are provided by the pedotransfer function suggested by O.V. Chestnykh and D.G. Zamolodchikov. [ABSTRACT FROM AUTHOR]

In the present study, we assessed the assemblages of terrestrial Heteroptera along a 500-km latitudinal and 500-km longitudinal gradient in the north of Argentine Patagonia and investigated the potential effects of the environment, vegetation factors and spatial structure on the community composition of terrestrial Heteroptera at regional scale. To identify the terrestrial Heteroptera assemblages and evaluate their association with different factors, we used multivariate analyses. A total of 840 samplings were carried out in 21 sites of three phytogeographic provinces (Patagonian steppe, Subantarctic province and Monte) along two sampling years. We captured a total of 2007 specimens, 1890 of which were identified to species and morphospecies level, and 57 of which were immature-stage specimens that could not be identified due to their unknown morphology and biology. We identified two distinct terrestrial Heteroptera assemblages: a) one from sites belonging to the Patagonian steppe and Subantarctic province and b) the other from sites belonging to the Patagonian steppe and Monte. The variation in the terrestrial Heteroptera assemblages explained mainly by Isothermality was significant and greater than that explained by the vegetation and the spatial structure. The results showed that, in northern Argentine Patagonia, the different Heteroptera assemblages are more associated with geographic areas with different environmental conditions than with areas with different vegetation types. The results also suggest that the variation in Heteroptera species composition at regional scale is driven by environmental variables related to thermal amplitude and precipitation. [ABSTRACT FROM AUTHOR]

This study inter-compares the spatiotemporal features of precipitation extremes at global and regional scales within six daily precipitation datasets, i.e., gauge-based (Global Precipitation Climatology Center dataset, GPCC), satellite-retrieval (Precipitation Estimation From Remotely Sensed Information Using Artificial Neural Networks-Climate Data Record, PERSIANN-CDR), three reanalysis datasets (ERA-Interim, ERAI; the National Center for Atmospheric Research Reanalysis 2, NCEP2; and the WATCH-Forcing-Data-ERA-Interim, WFDEI), and products merged from the three type datasets (the Multi-Source Weighted-Ensemble Precipitation, MSWEP). All datasets reproduce similar spatial patterns of both annual and seasonal precipitation extremes over the period from 1979 to 2017. Compared to the reference dataset gauge-based GPCC, the reanalysis WFDEI outperforms among six products with spatial correlation coefficients of 0.89 and 0.80 for the annual extreme indices (i.e., annual total amount of 95th precipitation and maximum 1-day precipitation), respectively. The satellite-based product PERSIANN-CDR performs better than reanalyses and merged datasets in capturing the temporal variability of the intensity and amount of precipitation extremes with similar changing tendencies and magnitudes of about 45 mm day−1 and 230 mm at the global scale, respectively. The reanalyses and merged products underestimate the intensity of precipitation extremes. The selected six datasets behave differently in various regions. For the percentile-based frequency of precipitation extremes, NCEP2 performs well in regions of the Southeast Asian (SEA) and Amazon (AMZ), while WFDEI better matches GPCC over East North America (ENA) and North Australia (NAU) in both spatial patterns and temporal changes with correlation coefficients of 0.84 and 0.90, respectively. For the intensity features of annual precipitation extremes, NCEP2 performs better than other four datasets over regions of SEA, AMZ and West Africa (WAF). ERAI and WFDEI are consistent with GPCC in ENA and NAU with correlations coefficients of the intensity between ERAI (WFDEI) and GPCC are 0.82 (0.77) and 0.78 (0.64) for ENA and NAU, respectively. For the intensity of seasonal precipitation extremes, GPCC shows the highest estimates in regions of SEA, AMZ, ENA and WAF. ERAI and WFDEI perform better in reproducing the spatial patterns of seasonal precipitation extremes in all regions. NCEP2 (ERAI and WFDEI) show(s) consistent temporal variability of seasonal precipitation extremes with GPCC in regions of AMZ and WAF (ENA and NAU). Overall, there are large discrepancies in the absolute values of daily precipitation among datasets, and performances of non-gauged-based precipitation datasets in capturing the spatiotemporal variability of precipitation extremes are dependent on seasons, regions, and time periods. [ABSTRACT FROM AUTHOR]

Climate change and human activities have increased the risk of soil erosion, resulting in widespread soil degradation in many regions worldwide. In this study, our purpose was to estimate the spatial and temporal changes in the integrated fertility indexes (IFI) of Northeast China from the 1990s to the 2010s from a regional perspective. The soil erosion modulus, calculated using the Revised Universal Soil Loss Equation, was combined with soil nutrient data for four nutrients in two time stages, and the response of soil fertility to soil erosion was analyzed under nine land-use patterns. The results indicated that soil fertility in Northeast China had decreased by 4.46% from the 1990s to the 2010s, with the IFI of cultivated land showing the smallest decline at 1.69%, followed by grassland at 4.81%, and forest land at 6.21%, in that order. The IFI of changed land-use decreased more than that of unchanged land-use. The △IFI (IFI in the 2010s minus IFI in the 1990s) was negatively correlated with the soil erosion modulus, particularly when the average soil erosion modulus exceeded 2 t/(ha/yr). Furthermore, △IFI was mostly negative, indicating obvious soil degradation. The contribution rate of nutrient loss in the 1990s averaged over 70%, which was significantly higher than that in the 2010s, indicating that non-point source pollution control and soil erosion interception measures implemented by most city governments after 2010 had been effective. In most cases, the contribution rates of the total potassium (TK) and soil organic carbon (SOC) in the 1990s were significantly higher than those of the other indicators, with the highest contribution rate of SOC loss being observed for cultivated land and the highest contribution rate of TK loss being observed for forest land and grasslands. Forest land is conducive to maintaining soil fertility, and when other types of land are converted into forest land, the contribution rate of nutrient loss decreases. [ABSTRACT FROM AUTHOR]

Solar-induced chlorophyll fluorescence (SIF), as a direct probe of vegetation photosynthesis, has recently been an effective indicator for crop yield estimation in late-season. Spatio-temporal prediction of SIF (STP-SIF) from mid- to late-season could be a promising solution to forecast crop yields in mid-season. However, STP-SIF has not been well explored in assessing its applicability in crop yield forecasting. In the study, we first explored the potential driving mechanism and designed time-series data-driven deep learning approaches for the STP-SIF issue. We compared the feasibility of four styles of explanatory variables, six network structures, and the corresponding eight approaches in SIF prediction in the main cotton-planting area in Northern Xinjiang, taking the two tasks of one and two months before harvest as examples. The STP-SIF products of the five approaches, namely Spe_CNN-LSTM (a hybrid network combining convolutional neural network and long short-term memory considering spectra), Spe_CNN3D (a three-dimensional CNN considering spectra), SpaSpeSIF_CNN3D (a three-dimensional CNN considering spectra and SIF), SpaSpeSIF_HCNN (a hybrid network combining CNN2D and CNN3D considering spectra and SIF), and SIF_CNN-LSTM (a CNN-LSTM network considering SIF), showed a similar spatial pattern to the referenced SIF, indicating that these proposed approaches could be better for STP-SIF. Discussion of the spatial scale effect of the STP-SIF issue preliminary showed that our proposed methods had little spatial scale dependence and hence could be suitable for STP-SIF in different spatial extents at diverse resolutions. Further, we performed the experiments for the regional-scale cotton yield forecast one to two months before harvest based on the STP-SIF products of August and September. The best cotton yield prediction accuracies, with R2 of 0.70 and 0.66 for one and two months before harvest, were obtained respectively by the combination of the known SIF and NDWI (Normalized Difference Water Index) and the predicted SIF by SIF_CNN-LSTM. This study offers a baseline for the STP-SIF issue and reveals the feasibility of the STP-SIF products for accurate crop yield forecast. • Time-series data-driven deep learning approaches were proposed for the STP-SIF issue. • STP-SIF products provide acceptable prediction accuracy for cotton yield forecasting. • Little spatial scale dependence of the STP-SIF methods was preliminary demonstrated. [ABSTRACT FROM AUTHOR]

The triangle/trapezoid framework model (TFM) is a widely used approach for mapping regional evapotranspiration (ET) based on thermal infrared remote sensing imagery. However, the homogeneity assumption for meteorological forcing and surface properties involved in TFM contradicts the characteristics of heterogeneous regions, leading to high uncertainty at regional scale, especially under energy-limited or strong advection conditions. Therefore, this study examined the linear relationship between soil moisture availability (Λ SM), evapotranspiration efficiency (Λ ET) and radiation surface temperature (T rad), and developed an Independent Framework-based dual-source ET Model (IFEM) for heterogeneous regions. By fixing two key meteorological forcing variables, air temperature (T a) and vapor pressure deficit (VPD), and three surface characteristic parameters, aerodynamic resistance (r a), albedo (α) and the ratio of soil heat flux to net radiation (Γ), the IFEM constructs a uniform fractional vegetation cover (f c)- T rad space. In this uniform f c -T rad space, isolines of Λ SM and Λ ET are aligned with those of T rad , and an independent trapezoid framework is constructed for each pixel of RS images. It avoids the systematic bias caused by the distorted trapezoid space involved in traditional TFMs. The proposed model was applied in a hydrologically semi-enclosed irrigation area, the Hetao Irrigation District, with Landsat and MODIS datasets from 2016 to 2020 to evaluate its performance at the field and region scales. Firstly, the IFEM was capable of retrieving latent heat with a mean absolute error (MAE) of 34.43 W m−2 and a mean absolute percentage error (MAPE) of 8.68%, compared with the measurements from flux towers. Secondly, the IFEM reasonably separated the soil (MAPE = 21.33%) and canopy (MAPE = 14.33%) components from ET, compared with the soil evaporation observed by micro-lysimeters and the plant transpiration calculated by sap velocity upscaling technology. Thirdly, the IFEM showed high accuracy in estimating annual total ET with a percentage error range within ±3.0%, compared against the regional water balance calculations. Overall, the IFEM demonstrated high robustness and accuracy for field-scale and regional-scale applications, validating its potential as a reliable method for mapping regional ET in heterogeneous regions. • The IFEM is developed for remote sensing-based duan-source ET estimation in heterogeneous regions. • The IFEM constructs a uniform f c - T rad space. • Where an independent trapezoid framework is constructed for each pixel. • Based on which, the evaporation efficiency could be more accurately estimated. • The LE could be more reasonably partitioned into soil and canopy components. [ABSTRACT FROM AUTHOR]

Phosphorus is a critical element determining trophic status and Chlorophyll a (Chl a) level in natural lakes and reservoirs, and total phosphorus (TP) concentrations can be predicted from data on phosphorus loading, hydraulic flushing rate and sedimentation. Due to their interactions with phosphorus, iron (hydr) oxides in suspended particles, originally derived from watershed soil, can strongly influence the phosphorus sedimentation and phosphorus bioavailability in water columns. Thus, the TP-precipitation relationship and the response of Chl a to TP are likely associated with watersheds soil iron. To test this assumption, we built hierarchical linear models for summer observation of natural lakes and reservoirs across a large geographic gradient. The intercepts and slopes of TP-precipitation relationships are higher in natural lakes than those in reservoirs, and these model coefficients exhibit latitudinal variations that are explained by the natural soil iron gradient. Soil iron, operating at a regional level, significantly mediates the effect of precipitation on TP concentration in both natural lakes and reservoirs, and drives the latitudinal variation in the Chl a -TP relationships for reservoirs. Our results imply that the increase in extreme precipitation events anticipated under future climate conditions may substantially mitigate eutrophication in tropical and subtropical reservoirs, but may worsen conditions in temperate lakes. Image 1 • Hierarchical models were used to analyze our cross-lake/reservoir data. • Soil iron modifies the impact of precipitation on TP concentration in lakes. • Soil iron drives the regional pattern of Chl a -TP relationship for reservoirs. • Iron promotes precipitation to mitigate eutrophication of (sub)tropical reservoirs. [ABSTRACT FROM AUTHOR]

Abstract Changes in land-use, agricultural management and climate affect the turnover and storage of organic carbon in soils (SOC) as well as the nitrogen mobilization from soil organic matter (SOM), with potential side effects on nitrogen availability and leaching. When addressing the requests for increased carbon storage in soil as well as for the reduction of nitrogen losses, integrated approaches on regional scales are required that take into account the actual changes in agricultural management and climate. This study investigated the arable land (7345 km2) of Saxony (Germany) with regard to the following: (1) the trends of SOC storage and organic matter-related nitrogen fluxes, including their subregional and annual dynamics, (2) changes in the carbon input to arable soils and the turnover of organic matter, and (3) the contribution of different drivers (climate, crop production and fertilization, tillage system) to the simulated SOM changes for the period 1998–2014 on a 500 m grid. The model CANDY carbon balance (CCB) was specifically adapted for large-scale simulations of SOM turnover to link spatial data on soils and climate with regional statistics on agricultural management. This new 'regional mode' of CCB has been validated using data from 391 plots across different European locations. The initial SOC levels for Saxony assumed steady state conditions at the beginning of the simulation period and have been validated using data from 667 monitoring sites. The results showed an increase in the SOC stocks of the arable soils of Saxony of 785 × 103 t C (1.24‰ annually) during the simulation period. At the same time, the model simulated an average increase in organic nitrogen stored in SOM of approximately 7.5 kg N ha−1 a−1, with considerable differences between individual years and subregions. Both the increase in carbon inputs to soil (+8%) and the reduction of carbon turnover rates (−10%) had positive effects on SOC storage. While the increased use of conservation tillage was the most important driver for the overall increase in SOM storage in Saxony, climate variability and crop production and fertilization had the largest effect on its annual dynamics. Highlights • Soil organic carbon (SOC) & nitrogen dynamics in Saxony were simulated on a 500 m grid. • The CCB model was specifically adapted & validated for large-scale simulations of SOM. • C input to arable soils increased while C turnover conditions decreased (1998–2014). • SOC stocks increased by 1.2‰ per year, largely driven by conservation tillage. • Climate variability caused a high annual dynamic in organic matter related nitrogen. [ABSTRACT FROM AUTHOR]

Highlights • ES bundle framework quantifies landscape scale ES tradeoffs or synergies changes. • Most of the ecosystem services were improved as a result of restoration programme. • The synergies among ecosystem services were weakened while gaps were more evident. • Baseflow is a sensitive indicator as the response to the vegetation restoration. • Bundles can capture the changed interactions of ecosystem services. Abstract Ecosystem service (ES) bundles can facilitate comprehensive understanding of the spatial configurations and interactions of multiple ESs across large-scale landscapes. They are critical for informing policy and improving ecosystem management. The spatial dimension of ES bundles has been addressed in recent research but little work has considered the temporal changes of ES bundles. This paper uses a case study in the Loess Plateau, the core area of vegetation restoration in China, to explore changes in ES spatial distributions, bundle types and multiple ES interactions in a period of rapid vegetation restoration between 2000 and 2015. Measurable proxies, biophysical indicators and the InVEST model were used to quantify 10 ESs. We found that (1) most of the ESs were improved, especially provisioning services and carbon sequestration. (2) There is a steady tradeoff between provisioning services and most regulating services, while the impacts of vegetation restoration on agricultural production were small. (3) The synergies among ESs were weakened, implying the presence of subtle functional ES interdependencies. (4) Changes in the bundling patterns between 2000 and 2015 revealed heightened gaps among ESs due to the upsurge of carbon sequestration and deterioration of the baseflow regulation. This research provides a new perspective for understanding the interactions between multiple ESs with regional vegetation restoration activities. Ecological restoration programmes play an important role in enhancing ESs, but they may also lead to expanded gaps between ESs. Baseflow regulation could be included as a key indicator to support a comprehensive understanding of the impacts of restoration interventions. The ES bundle framework is able to capture changes over time of the ES interactions across a large-scale landscape and facilitates informed ES management. [ABSTRACT FROM AUTHOR]

Abstract Environmental stressors and population growth have significantly affected terraced rice ecosystems, such as in the Sapa district in northern Vietnam. The question arises how natural and socio-economic components determine the amount of rice yields. This study combines a hybrid neural-fuzzy inference system (HyFIS) with GIS-based methods to generate two models that can map suitability areas for rice cultivation at a regional scale and predict actual rice yields at a plot scale. Semi-structured interviews, the "Integrated Valuation of Ecosystem Services and Tradeoffs" tool and different statistical models were used to investigate the impacts of eight environmental variables and three socio-economic variables on rice production. Subsequently, two HyFIS models were trained with an accuracy higher than 88%. Because the predictive power values of the two proposed HyFIS models were higher than those of benchmark models, they are considered as useful tools to assess and optimize land use and related rice productivity. Highlights • Hybrid models integrating neural network, fuzzy logic and geographical information system approaches were developed to find areas suitable for rice cultivation (a so-called S-HyFIS model) and to predict rice yields (a so-called I-HyFIS model). • Impacts of environmental characteristics and additional human inputs on rice production were quantified. • The S-HyFIS model can extrapolate results from plot to regional scales in order to generate a map representing crop suitability areas for rice cultivation. • The potential of conversion from different land uses/covers to arable lands and vice versa were analyzed in the Sapa district, Lao Cai province, Vietnam. [ABSTRACT FROM AUTHOR]

Abstract Vegetation restoration often has a significant effect on the supply of an ecosystem service (ES). Assessment of this effect is crucial for informed decision-making in sustainable ecosystem management. In this respect, this study analyses three regulating, two provisioning, and a single cultural ES over a 30-year period (1985 to 2015, with 15 years pre-restoration and 15 years post-restoration) in the Loess Plateau, China, using data from a combination of modelling and statistical yearbooks. On applying a suite of standard statistical tools, results indicate: (1) regional scale restoration promotes the increase of vegetation cover as the coverage increased faster between 2000 and 2015 than between 1985 and 2000; (2) vegetation restoration changes the temporal trend of regulating ESs, and enhances the supply of provisioning and cultural ESs; (3) the 40 municipalities of the Loess Plateau can be divided into four ES categories where areas with poor ES delivery account for about 30% of the Loess Plateau; (4) vegetation restoration changes the interaction among ESs, resulting in synergistic relationships between provisioning and regulating ESs; (5) precipitation has a significant impact on regulating ESs, while population density is critical for provisioning and cultural ESs. This study demonstrates that ESs, their interactions and their groupings can change across both time and space following the implementation of a vegetation restoration programme, which makes understanding ES dynamics complicated. Recommendations are provided for improved and coherent ecosystem management. Graphical abstract Unlabelled Image Highlights • Study assessed the impact of vegetation restoration on six ecosystem services. • 30% of the Loess Plateau was weak in ecosystem service delivery. • Vegetation restoration changed interaction and grouping among ecosystem services. • Social-natural factors were found to drive ecosystem service variation. [ABSTRACT FROM AUTHOR]

The process of soil salinization in the artificial oasis in the arid area is a complex process involving multiple factors, multi-level driving and multi-process coupling. To reveal the spatial-temporal distribution of water and salt in arid pumping-irrigation areas, the first phase irrigation area of Jingtaichuan Electrical Pumping Irrigation District in Gansu Province, located at the edge of Tengger desert, was selected as the typical research area. A total of five indicators including surface salt, soil salinity, groundwater salinity, surface irrigation water, and groundwater depth were selected in 1994, 2001, 2008, and 2015. We determined the weights of each indicator factor by extension analytic hierarchy process. With the help of monitoring classification and spatial analysis technology in ArcGIS software, spatial distribution raster maps of each indicator factor were obtained, and each raster map is standardized, the space is nested and superimposed according to the weight of each index factor, so as to get the spatial-temporal distribution of water and salt in the regional scale. The results showed that: 1) The weight of each factor affecting the spatial-temporal differentiation process of water and salt on a regional scale was ranked as follows: groundwater depth (0.3190), > groundwater salinity (0.2710), > soil salinity (0.1971), > surface salinity (0.1748), and > surface irrigation (0.0381).Groundwater depth and groundwater salinity were the main driving factors affecting the spatial-temporal differentiation of water and salt at regional scales. 2) The saline land in the study area were mainly distributed in the eastern closed hydro-geological units. Overall, the area of mild saline land was the largest, accounting for 7.22%-11.12%, followed by moderate saline land, accounting for 3.19%-5.72%, the area of heavy saline land was the smallest, accounting for 3.03%-4.91% during 1994-2015. The saline land in the study area was still in the process of development, and showed an accelerating growth trend. Among them, the development speed was mild saline land area > the moderate saline land > the heavy saline land. 3) The spatial and temporal distribution of water and salt in the study area was related to the overall topography. The distribution of total equivalent value of water and salt was low in the west and high in the east, increasing from southwest to northeast in arc diffusion development trend, affected by natural geomorphology and topographic conditions. With the passage of time, the total can be divided into two stages: stable development period (1994-2008) and rapid development period (2008-2015).Affected by the continuous expansion of the regions with higher total water and salt content in the east to the west, the security of cultivated land resources in the west was potentially threatened, and the overall development trend of water and salt in the study area was not conducive to the sustainable development of agricultural production in the irrigated areas.Based on the analysis of single driving factors, this study proposes an important means for coupling and superimposing multiple driving factors, which provides a new visualization for the comprehensive development of the spatial-temporal differentiation of water and salt in the study area. It can provide useful reference for studying the development trend of spatial-temporal differentiation process of water and salt in regional scale. [ABSTRACT FROM AUTHOR]

Abstract The WOFOST cropping systems model has been applied operationally over the last 25 years as part of the MARS crop yield forecasting system. In this paper we provide an updated description of the model and reflect on the lessons learned over the last 25 years. The latter includes issues like system performance, model sensitivity, spatial model setup, parameterization and calibration approaches as well as software implementation and version management. Particularly for spatial model calibrations we provide experience and guidelines on how to execute calibrations and how to evaluate WOFOST model simulation results, particularly under conditions of limited field data availability. As an open source model WOFOST has been a success with at least 10 different implementations of the same concept. An overview is provided for those implementations which are managed by MARS or Wageningen groups. However, the proliferation of WOFOST implementations has also led to questions on the reproducibility of results from different implementations as is demonstrated with an example from MARS. In order to certify that the different WOFOST implementations and versions available can reproduce basic sets of inputs and outputs we make available a large set of test cases as appendix to this publication. Finally, new methodological extensions have been added to WOFOST in simulating the impact of nutrients limitations, extreme events and climate variability. Also, a difference is made in the operational and scientific versions of WOFOST with different licensing models and possible revenue generation. Capitalizing both on academic development as well as model testing in real-world situations will help to enable new applications of the WOFOST model in precision agriculture and smart farming. Highlights • An updated description of the WOFOST model is provided • Guidelines for (spatial) calibration of WOFOST are provided • Current implementations of the model are described and issues with model proliferation are raised • New development and model extensions are described • A set of reference results is published that can be used to certify any WOFOST implementation. [ABSTRACT FROM AUTHOR]