Variety Of Spatial Scales Research Articles

Development of a new method framework to estimate the nonlinear and interaction relationship between environmental factors and soil heavy metals

The intricate and multifaceted nature of soil system profoundly influences the highly complex and often nonlinear changes that soil heavy metals (HM) undergo. Spatial heterogeneity, location and scale variability, and the interaction and superposition among environmental drivers challenged researchers to determine the sophisticated nature of soil HMs changes at the regional scale. This study aims to develop a new method framework and selects Ningbo as the case study to apportion the environmental factors responsible for soil HMs pollution that include Cd, Cr, Pb, Hg, As, Cu, Zn and Ni, focusing on nonlinearity and interaction. We harnessed the Random Forest model to apportion the environmental drivers of soil HM change. The directionality and shape of the nonlinear relationship between HMs and their individual contributors were derived by Partial Dependence Plots. The interactions of multiple drivers were quantitatively assessed by the Conditional Inference Tree. Our results demonstrated that soil HMs in the study area varied spatially. Soil HMs pollution was mitigated by natural factors and anthropogenic factors. The main influencing factors were pH, soil parent material type, enterprise activities, and agricultural application. The effects of some factors on soil HMs showed a monotonic linear trend, but some have apparent threshold effects. The direction of influence on soil HMs will shift when pH and phosphate fertilizer reach a specific value. The addition of enterprises in the area would rarely have an impact on the HMs pollution once it reached around 2 per km2 because of the industrial agglomeration. Soil HM concentrations were mainly from multi-pollutants and were governed by a combination of environmental factors. Our study provided managers and policymakers with site-specific and definite guidelines for preventing and controlling soil HM pollution.

Evaluation of Long Time-Series Soil Moisture Products Using Extended Triple Collocation and In Situ Measurements in China

Currently, satellite-based soil moisture (SM) products and land surface model assimilation techniques are widely utilized. However, the presence of systematic errors in the observation process, algorithmic discrepancies between products, and variations in spatial and temporal scales result in diverse accuracy characteristics and applicability. This study evaluates three prominent SM products in China, namely, the Essential Climate Variable Soil Moisture (ECV), the European Centre for Medium-Range Weather Forecasts’ Fifth-Generation Land Surface Reanalysis Data (ERA5-Land), and the Global Land Surface Data Assimilation System (GLDAS). The evaluation was conducted using extended triple collocation (ETC) analysis and in situ validation methods at a monthly scale from 2000 to 2020. The ETC analysis results show that among the three products, GLDAS exhibits the highest correlation coefficient (CC) and the lowest standard deviation of error (ESD), indicating its superior performance in China. ECV and ERA5-Land follow, with slightly lower performance. In the in situ validation results, ERA5-Land displays the highest correlation, capturing the temporal trend of the ground SM well. Comparatively, in terms of overall accuracy, ECV performs the best, with a slightly smaller mean error (ME) and root mean square error (RMSE) than GLDAS, and ERA5-Land has the lowest accuracy. The discrepancy between the in situ validation results and ETC analysis can be attributed to the limited number of sites and their representativeness errors. Notably, ERA5-Land exhibits a highly consistent trend of interannual fluctuations between ESD and precipitation. Furthermore, a strong association is observed between the ME and RMSE of ECV and GLDAS and precipitation. These findings serve as valuable references for future SM studies in China.

Spatial Distribution, Source Analysis, and Health Risk Assessment of Metal Elements in Karst Water in Southeastern Chongqing

Dispersed karst water is an important water supply source, or even the only water supply source, for some districts and counties in Chongqing City. It is particularly necessary to understand the distribution characteristics of metal elements in karst water and the health risks exposed. In this study, the scattered karst water in the southeastern part of Chongqing was taken as the main research object, and the concentrations of Al, Cu, Pb, Zn, Cr, Cd, Ni, Mn, As, and Hg in 42 groups of karst spring water samples were determined. The spatial distribution of metal elements with a high detection rate was revealed using the ordinary kriging interpolation method, and the spatial distribution characteristics, sources, and health risks of metal elements were analyzed using multivariate statistical methods and health risk models. The results showed that the quality of dispersed karst water in southeastern Chongqing was generally good, and the spatial scale variability in the occurrence of metal elements in karst water was strong, especially for Ni and As. The sources of Cu, Pb, As, Zn, and Cr were mainly affected by the regional geological background; Al and Mn were mainly affected by human industrial, agricultural, and mining activities; and Ni was affected by both the natural background and human activities. The total health risk of exposure through the drinking route was higher than that of the skin infiltration route, which was the main exposure route of the human body. The total health risk of children exposed through the drinking route was higher than that of adults, and the total health risk of adults exposed through the skin infiltration route was higher than that of children. It is worth noting that Cr was the determinant of total health risk. From the perspective of drinking water safety, local residents need to pay certain attention to water quality when drinking distributed karst groundwater, in order to reduce the health risk of the population.

Relationships between summertime surface albedo and melt pond fraction in the central Arctic Ocean: The aggregate scale of albedo obtained on the MOSAiC floe

As part of the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC), the HELiX uncrewed aircraft system (UAS) was deployed over the sea ice in the central Arctic Ocean during summer 2020. Albedo measurements were obtained with stabilized pyranometers, and melt pond fraction was calculated from orthomosaic imagery from a surface-imaging multispectral camera. This study analyzed HELiX flight data to provide insights on the temporal and spatial evolution of albedo and melt pond fraction of the MOSAiC floe during the melt season as it drifted south through Fram Strait. The surface albedo distributions showed peak values changing from high albedo (0.55–0.6) to lower values (0.3) as the season advanced. Inspired by methods developed for satellite data, an algorithm was established to retrieve melt pond fraction from the orthomosaic images. We demonstrate that the near-surface observations of melt pond fraction were highly dependent on sample area, offering insight into the influence of subgrid scale features and spatial heterogeneity in satellite observations. Vertical observations conducted with the HELiX were used to quantify the influence of melt pond scales on observed surface albedo as a function of sensor footprint. These scaling results were used to link surface-based measurements collected during MOSAiC to broader-scale satellite data to investigate the influence of surface features on observed albedo. Albedo values blend underlying features within the sensor footprint, as determined by the melt pond size and concentration. This study framed the downscaling (upscaling) problem related to the airborne (surface) observations of surface albedo across a variety of spatial scales.

Higher daily temperature range at depth is linked with higher thermotolerance in antipatharians from the canary islands

Sensitivity to ocean warming is generally expected to be lower in populations from more heterogeneous thermal environments, owing to greater phenotypic plasticity and/or genotype selection. While resilience of benthic populations from thermally fluctuating environments has been investigated at a variety of spatial scales, this has received limited attention across depths and has remained unresolved for Antipatharian corals, key habitat-forming species across a wide bathymetric range in all of the world oceans. In this study, we aimed at addressing the thermal sensitivity of Antipatharian corals across depths characterized by different levels of temperature fluctuations. We used an acute ramping experimental approach to compare the thermal sensitivity of colonies of (1) the branched Antipatharian Antipathella wollastoni (Gray, 1857) from two distinct depths (25 and 40 m) in Gran Canaria (Canary Islands, Spain); and of (2) unbranched mesophotic (80 m) Stichopathes species, from Lanzarote (Canary Islands, Spain; S. gracilis (Gray, 1857)), and Stichopathes sp. clade C from Mo’orea, French Polynesia. Results showed that the daily temperature range in Gran Canaria was larger at mesophotic depths (3.9 °C vs. 2.8 °C at 40 and 25 m, respectively) and this coincided with lower thermal sensitivity in mesophotic colonies of A. wollastoni. Second, S. gracilis from Lanzarote showed a lower thermal sensitivity than the previously studied Stichopathes sp. clade C from Mo’orea (French Polynesia) inhabiting a less variable habitat. These results are in line with the climate variability hypothesis, which states that populations under more variable thermal conditions have a lower sensitivity to warming than those from more stable environments, as they have adapted/acclimated to these higher levels of temperature fluctuations.

APPLICATION OF SEMI-VARIOGRAM ANALYSIS IN MEASURING SPATIAL VARIABILITY AND DISTRIBUTION OF SELECTED SOIL PROPERTIES IN NORTHEAST AKWA IBOM STATE, NIGERIA

Application of semi-variogram analysis in measuring spatial variability and distribution of selected soil properties in Northeast Akwa Ibom State, was carried out.The aim was to assess spatial variability and distribution of selected soil properties in the study area for effective site-specific soil management and precision agriculture using semi-variogram analysis. A digital elevation model (DEM) of the study area was acquired from United State Geological Survey (USGS) at 30m resolution. Slope gradient map that is capable of capturing the short-scale spatial variability of soil properties in the study area was generated from the DEM to guide field sampling. Modified conditioned Latin hypercube sampling technique was used in selecting observation points. Soil samples were collected from each observation point at 0-30 cm and 30-60 cm depths using soil auger. A total of 152 soil samples were collected for laboratory analysis. Analysed data of depth interval of 0-30cm and 30-60 cm were integrated to form depth interval of 0-60 cm. The data were subjected to normality test to ascertain the normal distribution of the data. Selected soil properties were subjected to semi-variogram analysis. The study revealed that slope gradient was able to captured short scale spatial variation in some soil properties understudy. Soil texture of the flat/nearly flat was sand in both surface and subsurface soil and sand in the surface soil and loamy sand in the subsurface soil in gently sloping and sloping. Soil pH was slightly acid in in flat/nearly flat and gently sloping and strongly acid in the sloping area in both surface and subsurface soil. Organic carbon was very high in the flat/nearly flat and gently sloping and high in sloping topography in both surface and subsurface soil. Total N was low in the sloping area and moderately low in gently sloping and nearly flat /flat. Base saturation was very high in the sloping topography and high in the gently sloping and nearly flat /flat. The results of semi-variogram analysis showed that all the selected soil properties exhibited spatial dependence within some distances. The range was 136.2 m for sand, 76.4m for silt, 1.6 m for clay, 1.7m for soil pH, 9.4m for organic carbon, 7.1m for total N, 9.2m for available P and 7.8 m for exchangeable K in the study area. Beyond this range, there is no longer relationship between sample points and sample values are not related to one another. The strength of the spatial dependence of sand, silt, soil pH, organic carbon, total N and available P was moderate; exchangeable K was strong while clay was weak. The semi- variance (sill) was 57.4 for sand, 23.8 for silt, 7.15 for clay, 0.21 for soil pH, 1.18 for organic carbon, 0.002 for total N, 85.1 for available P, and 0.03 for exchangeable K. The nugget variance or nugget effect was 25.9 for sand, 10.2 for silt, 5.9 for clay, 0.06 for soil pH, 0.60 for organic carbon, 0.001 for total N, 33.4 for available P and 0.003 for exchangeable K. The best fitted models were Exponential for sand and silt; Gaussian for available P and Spherical for clay, pH, organic carbon, total N and exchangeable K.

Spatial and temporal variability of greenhouse gas ebullition from temperate freshwater fish ponds

Fish ponds with their typically high carbon and nutrient inputs are relevant sources of greenhouse gases. However, not much is known about gas bubble emissions (ebullition) and their high spatiotemporal variability. This is the first study which quantified diffusive and ebullitive greenhouse gas emissions from temperate fish ponds. To improve greenhouse gas estimates, we investigated the diurnal and spatial variability of diffusive and ebullitive fluxes in 12 extensively to semi-intensively managed fish ponds near Bautzen, Germany. Emissions differed greatly between the different ponds but methane was consistently the predominant greenhouse gas. The feeding sites were hotspots with one order of magnitude higher ebullition rates compared to other parts of the ponds. At these hotspots, ebullitive fluxes of up to 38 L/m2d were measured with a mean bubble methane content of 79%, corresponding to a methane flux of 1.24 mol/m2d. Methane accounted for 90% of the global warming potential in one fish pond but carbon dioxide emissions of up to 242 mmol/m2d at the feeding sites were also significant. Nitrous oxide fluxes, in contrast, were low with 5 ± 9 μmol/m2d. Greenhouse gas ebullition decreased exponentially along a transect from the feeding site into the pond and showed some diurnal fluctuations. While diffusion was higher during night, ebullition rates increased in the morning, presumably caused by higher benthivorous fish activity. Our results highlight the potential of temperate fish ponds as significant greenhouse gas sources and ebullition as a significant pathway. For robust quantification, both small scale spatial and temporal variability as well as the hotspot of the feeding area must be considered.

YOLO-BYTE: An efficient multi-object tracking algorithm for automatic monitoring of dairy cows

Dairy cows tracking is an essential means to obtain their behavioral information, real-time position, activity data, and health status. A multi-object tracking method (YOLO-BYTE) is proposed to address the problem of missed detection and false detection caused by complex environments in cow individual detection and tracking. The method improves upon the YOLO v7 Backbone network feature extraction module by adding a Self-Attention and Convolution mixed module (ACmix) to account for the uneven spatial distribution and target scale variation of the cows. Additionally, in order to reduce the number of model parameters, an improved lightweight Spatial Pyramid Pooling Cross Stage Partial Connections (SPPCSPC-L) module is adopted to reduce model complexity. At the same time, the state parameters in the Kalman filter are improved by directly predicting the width and height information of the tracking boxes, so as to improve the ByteTrack algorithm to make tracking boxes matching the cows more precisely and accurately. Experimental conducted on the dairy cow object detection and multi-object tracking dataset show that the proposed YOLO-BYTE model achieves a Precision (P) of 97.3% in the dairy cow target detection dataset, with an improved Recall (R) and Average Precision (AP) by 1.1% compared to the original algorithm, and an 18% reduction in model parameters. Moreover, the proposed method demonstrated significant improvements in High Order Tracking Accuracy (HOTA), Multi-Object Tracking Accuracy (MOTA), and Identification F1 (IDF1) by 4.4%, 6.1%, and 3.8%, respectively, compared to the original model, with a decrease of 37.5% in Identity Switch (IDS). The tracker runs in a real-time manner with an average analysis speed of 47 fps. Hence, it is demonstrated that the proposed approach is capable of effective multi-object tracking of dairy cows in natural scenes and provides technical support for non-contact dairy cow automatic monitoring.

Contrasting spatial distribution of pioneer versus non‐pioneer saplings in a Taiwanese forest: A multiple scale approach

AbstractDispersal limitation and environmental filtering were recognized as the main dispersal‐based and niche‐based processes responsible for community assembly. These interactions usually leave more spatial signatures in sapling communities and create detectable spatial patterns in different functional types of species. We investigated saplings of pioneer and non‐pioneer species, which facilitated an understanding of species co‐existence and biodiversity recovery. Based upon mapped tree data in the subtropical evergreen broad‐leaved forest dynamics plot in Taiwan, we endeavored to: (1) determine the different spatial scales contributing to distribution patterns of pioneer and non‐pioneer saplings; (2) understand how dispersal limitation affects distribution of pioneer and non‐pioneer saplings; and (3) evaluate the degree to which the different environmental factors explain variation in species composition in pioneer and non‐pioneer saplings. We used the principal coordinates of neighbor matrices (PCNM) method, and variation partitioning to disentangle the contributions of these processes. Fine‐scale spatial patterns were more important for pioneer than for non‐pioneer saplings. Dispersal limitation was the main process influencing the spatial distribution of the non‐pioneer saplings. Environmental filtering was also an important process regulating the spatial distribution of saplings for both functional types, especially for pioneer saplings. Disturbance effects contributed to fine‐scale spatial variation in pioneer saplings, whereas topographic and soil effects contributed to broad and medium scale spatial variation in non‐pioneer saplings. It was evident that different spatial patterns of saplings of different functional types served to facilitate tree regeneration and maintain species co‐existence in this subtropical broad‐leaved forest.

Global and Regional Discrepancies between Early-Twentieth-Century Coastal Air and Sea Surface Temperature Detected by a Coupled Energy-Balance Analysis

Abstract A major uncertainty in reconstructing historical sea surface temperature (SST) before the 1990s involves correcting for systematic offsets associated with bucket and engine-room intake temperature measurements. A recent study used a linear scaling of coastal station-based air temperatures (SATs) to infer nearby SSTs, but the physics in the coupling between SATs and SSTs generally gives rise to more complex regional air–sea temperature differences. In this study, an energy-balance model (EBM) of air–sea thermal coupling is adapted for predicting near-coast SSTs from coastal SATs. The model is shown to be more skillful than linear-scaling approaches through cross-validation analyses using instrumental records after the 1960s and CMIP6 simulations between 1880 and 2020. Improved skill primarily comes from capturing features reflecting air–sea heat fluxes dominating temperature variability at high latitudes, including damping high-frequency wintertime SAT variability and reproducing the phase lag between SSTs and SATs. Inferred near-coast SSTs allow for intercalibrating coastal SAT and SST measurements at a variety of spatial scales. The 1900–40 mean offset between the latest SST estimates available from the Met Office (HadSST4) and SAT-inferred SSTs range between −1.6°C (95% confidence interval: [−1.7°, −1.4°C]) and 1.2°C ([0.8°, 1.6°C]) across 10° × 10° grids. When further averaged along the global coastline, HadSST4 is significantly colder than SAT-inferred SSTs by 0.20°C ([0.07°, 0.35°C]) over 1900–40. These results indicate that historical SATs and SSTs involve substantial inconsistencies at both regional and global scales. Major outstanding questions involve the distribution of errors between our intercalibration model and instrumental records of SAT and SST as well as the degree to which coastal intercalibrations are informative of global trends. Significance Statement To evaluate the consistency of instrumental surface temperature estimates before the 1990s, we develop a coupled energy-balance model to intercalibrate measurements of sea surface temperature (SST) and station-based air temperature (SAT) near global coasts. Our model captures geographically varying physical regimes of air–sea coupling and outperforms existing methods in inferring regional SSTs from SAT measurements. When applied to historical temperature records, the model indicates significant discrepancies between inferred and observed SSTs at both global and regional scales before the 1960s. Our findings suggest remaining data issues in historical temperature archives and opportunities for further improvements.

Safeguarding pollinators requires specific habitat prescriptions and substantially more land area than suggested by current policy

Habitat loss and fragmentation are major drivers of global pollinator declines, yet even after recent unprecedented periods of anthropogenic land-use intensification the amount of habitat needed to support insect pollinators remains unknown. Here we use comprehensive pan trap bee survey datasets from Ontario, Canada, to determine which habitat types are needed and at what spatial scales to support wild bee communities. Safeguarding wild bee communities in a Canadian landscape requires 11.6–16.7% land-cover from a diverse range of habitats (~ 2.6–3.7 times current policy guidelines) to provide targeted habitat prescriptions for different functional guilds over a variety of spatial scales, irrespective of whether conservation aims are enhancing bee species richness or abundance. Sensitive and declining habitats, like tallgrass woodlands and wetlands, were important predictors of bee biodiversity. Conservation strategies that under-estimate the extent of habitat, spatial scale and specific habitat needs of functional guilds are unlikely to protect bee communities and the essential pollination services they provide to both crops and wild plants.

Evaluation of the near-surface wind field over the Adriatic region: local wind characteristics in the convection-permitting model ensemble

We present the first evaluation of the wind field from the ensemble of kilometer-scale simulations from the CORDEX-Flagship Pilot Study on convection, with focus on the Adriatic region. Kilometer-scale climate models, also known as convection-permitting models (CPMs), produce a good representation of small-scale topographic features and consequently a more detailed depiction of dynamical and thermal circulations. These enable a reliable view of climate characteristics of the wind field, especially in coastal regions and over complex terrain, such as the Adriatic region. We investigate the (potential) added value introduced by CPMs compared to classical “cumulus-parametrized” regional climate models (RCMs), reanalysis and station observations. For this purpose, wind components at 10 m level are used at 3-hourly frequency. All simulations cover a 10-year period, extending from 2000 to 2009. In terms of the standard statistical parameters such as correlation coefficient and temporal standard deviation, CPMs are very dependent on their parent RCM performance. However, the orographic forcing emphasizes the potential added value and CPMs contain some fine spatial scale variability (i.e., stronger extremes by 25% and more accurate wind direction) that is absent in coarser RCMs and reanalysis. The potential added value is higher in the cold season compared to the warm season due to the proportion of severe wind events. CPMs reproduce well the typical wind regimes along the Adriatic coast, namely Bora and Sirocco. The benefit of using CPMs is especially pronounced in simulating Bora maximum wind speeds in northern Adriatic and Sirocco frequencies in southern Adriatic. Based on our overall analysis, we conclude that CPMs provide added value compared to coarser models, especially in the complex coastal terrain.

Weighted risk assessment of critical source areas for soil phosphorus losses through surface runoff mechanisms

In intensive livestock areas, soils commonly contain elevated nutrients above the agronomic optimum which increases the risk of nutrient losses and contributing to poor ecological status waterbodies. Large within-field variability in soil nutrient content exists, and at-risk phosphorus (P) hotspots are rarely quantified due to sub-optimal soil sampling regimes. This study aims to address this issue by developing and evaluating an improved classification of P transfer risk at a sub-field scale through a weighted risk assessment model that combines gridded soil sampling data with modelled in-field surface runoff pathways. Within-field soil P variability was quantified at six field-scale sites in Northern Ireland using two different sampling techniques; traditional bulked field soil sampling (i.e. bulk analysis of W pattern sampling) and gridded sampling (at 35 m resolution) alongside interpolation. Results show that traditional bulked sampling failed to account for the sub-field scale spatial variability in soil P content. This may contribute to the poor chemical and ecological status of surface waters by frequently under-predicting soil nutrient content, and failing to identify potential contributing sources of soil P losses. In contrast, higher intensity gridded sampling and interpolation revealed wide in-field spatial variability in soil P content, facilitating the identification of contributing sources of P losses to poor water quality and aiding in the characterisation of risk for nutrient losses to waterways. Hydrological modelling of in-field runoff pathways indicated several P sources potentially contributing to runoff-based P losses. Our weighted risk assessment model was successful in identifying P hotspots and transfer potential to water courses, illustrating that a similar approach could be applied anywhere in the world where excess P poses a problem for water quality. Model validation took place using instream water quality sampling data, which showed that higher risk weighting model results correlated to poorer water quality conditions. This methodology could be a useful management tool to help countries meet their national water quality targets.

Bottom evolution patterns driven by hydrodynamic forcing in the Southwest Atlantic Inner Continental Shelf, off Río de la Plata and Patos Lagoon

Sediment transport and depositional processes in the Southwest Atlantic Inner Shelf are strongly influenced by the contribution from Río de la Plata and Patos Lagoon fluvial systems. Understanding the behavior of erosive and depositional processes and bed evolution in the region is of utmost importance to address the impacts of anthropogenic activities, climate change and for navigation security. Therefore, this work aims to improve the understanding of such processes, and their temporal and spatial scales of variability. We employed the SISYPHE morphodynamic model coupled with the TELEMAC-3D hydrodynamic model to simulate the resulting depositional and erosional fluxes and the bottom evolution during a period of 8 years (2005–2012). Results indicate that during this period, depositional fluxes mostly exceeded erosional fluxes in the south of the Patos Lagoon mouth, resulting in predominantly positive bottom evolution. On the other hand, erosional fluxes exceeded depositional fluxes to the north of the Patos Lagoon mouth, resulting in predominantly negative bottom evolution. Widespread positive values of bottom evolution are observed along the northern and southern coasts off the Río de la Plata mouth, indicating a general dominance of sediment deposition over erosion. A wavelet analysis showed that fluvial discharge influences the variability of depositional process on an interannual time scale, whereas the synoptic variability is influenced by wind action. Moreover, positive ENSO periods (El Niño) are related to increased depositional fluxes, and decreased depositional fluxes during the negative phase (La Niña), with pronounced effects off Río de la Plata.

Spatial and temporal controls on the solute behavior of rivers in arid watersheds: The Okavango River, NW Botswana

Solute cycling models for rivers in arid watersheds must identify solute sources and their spatial and temporal connectivity to rivers to assess the processes that control the solute behavior in these rivers. In this study, we collected hourly time series of total dissolved ions (TDI) concentrations, water levels, water temperatures and air temperatures at select stations distributed longitudinally in a river in an arid watershed. Our objectives were to: (1) document the spatial and temporal variations in solute concentrations and (2) determine the processes controlling the spatial and temporal variations in solute concentrations. We conducted this investigation over a two-year period at four stations along the Okavango River flowing through the Okavango Delta (Delta) in the middle Kalahari Desert, Botswana. At the spatial scale, we observed progressive downriver enrichment in TDI concentrations associated with evapotranspiration of river water because of the 5 months river transit across the hot Delta. At a temporal scale, the TDI concentrations increased seasonally from evapoconcentration and sub-seasonally from solute transfer from the watershed to the river. We analyzed sub-seasonal TDI concentration perturbations using the slope (β) of the relationship between TDI concentrations and normalized water level (C-NWL) relationships. We find that at low discharge during flow recession and at the beginning of rising discharge from flooding, the solute enrichment anomalies with β > 0 are related to hydrologic connectivity between the river and solute stores in the river floodplains, hundreds of thousands of salt islands and isolated evapoconcentrated wetland pools. Our findings indicate that hydrologically-driven river connectivity to solute stores in the local watershed and evapotranspiration jointly control the solute behavior at variable spatial and temporal scales in rivers in arid watersheds. We anticipate that our findings will inform solute transport and solute cycling models for rivers in arid watersheds.

Study on the Evaluation and Assessment of Ecosystem Service Spatial Differentiation at Different Scales in Mountainous Areas around the Beijing-Tianjin-Hebei Region, China.

Ecosystem services are closely related to human wellbeing-which refers to the basic material conditions required to maintain high standards of quality of life, of health, and of safety and security, as well as good social relationships, and freedom of choice and action-and have a high potential value. The adequate valuation of ecosystem service values (ESV) is now an urgent need for the implementation of policy measures such as ecosystem asset management, ecological compensation and paid use of ecosystem services. Based on the method of ecosystem value equivalent factor per unit area, in this paper we investigated the variability of total ESV spatial distribution and regional differences in the value of 11 ecosystem service types provided by ecosystems in the mountainous areas of the Beijing-Tianjin-Hebei (BTH) region at different spatial scales and discussed the relationship between ESV and land use land cover (LULC). The results show that the total ESVs in 2015 and 2020 in the mountainous areas of BTH region were 5671 × 108 CNY and 6381 × 108 CNY, respectively. The change trend of each ecosystem service value from 2015 to 2020 was dominated by an increase of water supply service, and the maintenance of soil and nutrient cycle services in the mountainous area of BTH and the Yanshan Mountain (YSM). The change patterns of the value of ecosystem service categories in the Taihang Moutain (THM) and Bashang region (BSR) are dominated by an increase in the value of maintained soil and water supply services and a decrease in the value of regulating services. The calculation of ESV can be made more accurate by considering climate and vegetation conditions at the region, ecosystem, county or township scales rather than at grid scale, as, for calculating the interannual variation of total ESV, the spatial scale variability is large. The assessment of ESVs is important from the point of view of planning the use of the environment, of spatial planning, and of nature conservation. The ecosystem service of woodland and water bodies are more prominent compared with other land-use types and construction land and bare land provide the lowest value of service. There is some similarity between the value changes of ecosystem service categories and the distribution of LULC types. This study strengthens the understanding of the spatial scales of different ESV in mountain areas, which is beneficial to ecosystem management policies.

Patterns and controls of foliar nutrient stoichiometry and flexibility across United States forests.

Plant element stoichiometry and stoichiometric flexibility strongly regulate ecosystem responses to global change. Here, we tested three potential mechanistic drivers (climate, soil nutrients, and plant taxonomy) of both using paired foliar and soil nutrient data from terrestrial forested National Ecological Observatory Network sites across the USA. We found that broad patterns of foliar nitrogen (N) and foliar phosphorus (P) are explained by different mechanisms. Plant taxonomy was an important control over all foliar nutrient stoichiometries and concentrations, especially foliar N, which was dominantly related to taxonomy and did not vary across climate or soil gradients. Despite a lack of site-level correlations between N and environment variables, foliar N exhibited intraspecific flexibility, with numerous species-specific correlations between foliar N and various environmental factors, demonstrating the variable spatial and temporal scales on which foliar chemistry and stoichiometric flexibility can manifest. In addition to plant taxonomy, foliar P and N:P ratios were also linked to soil nutrient status (extractable P) and climate, especially actual evapotranspiration rates. Our findings highlight the myriad factors that influence foliar chemistry and show that broad patterns cannot be explained by a single consistent mechanism. Furthermore, differing controls over foliar N versus P suggests that each may be sensitive to global change drivers on distinct spatial and temporal scales, potentially resulting in altered ecosystem N:P ratios that have implications for processes ranging from productivity to carbon sequestration.

SPATIAL VARIABILITY STATUS OF SELECTED SOIL PROPERTIES IN NORTH-EAST AKWA IBOM STATE, NIGERIA

Spatial variability status of selected soil properties in North-east Akwa Ibom State, Nigeria was assessed. The aim was to establish baseline information on the spatial variability status of selected soil properties in North-east Akwa Ibom State for site -specific and sustainable soil management. A terrain attribute (plan curvature) that is capable of capturing the short-scale spatial variability of soil properties in the field was used to guide field sampling. Plan curvature map was generated from digital elevation model (DEM) of the study area acquired from United State Geological Survey (USGS) at 30m resolution. The plan curvature map was classified into straight, convex and concave surfaces. Modified conditioned Latin hypercube sampling method was used in selecting observation points. Each observation point was purposefully selected to fall within the three classes of the plan curvature map to give a good coverage of both feature space (terrain attributes) and geographical space (study area). Soil samples were collected from each observation point at depths of 0-30 cm and 30-60 cm using soil auger. A total number of 152 soil samples were collected in the study area for laboratory analysis. Data generated were subjected to analysis of variance (ANOVA) and means were separated using least significant difference (LSD) at 5% level of significance. The depth interval of 0-30cm and 30-60 cm were integrated to form depth interval of 0-60 cm and data with skewed distribution were log transformed for semivariogram analysis. Soil properties were then subjected to semi-variogram analysis. The results showed that plan curvature was able to capture short scale spatial variation in some soil properties under study. Soil texture was sand in the surface and subsurface soils of both convex and concave slope while in straight slope, the soil texture was sand in the surface and loamy sand in the subsurface. Soil pH was strongly acidic in both straight and concave slope and slightly acidic in convex slope in both surface and subsurface soil. Organic carbon was high in concave and convex slope and very high in straight topography in both surface and subsurface soils. Total N was low in the convex and concave slope but moderately low in straight terrain. The available P of straight slope was higher than that of concave and convex slope.From the semi-variogram analysis, all the selected soil properties exhibited spatial dependence within some distances. The strength of the spatial dependence varied from moderate for sand, silt, soil pH, organic carbon, total N and available P to weak for clay and strong for exchangeable K. The best fitted models were Exponential for sand and silt; Gaussian for available P and Spherical for clay, pH, organic carbon, total N and exchangeable K.The range of autocorrelation was 136.2 m for sand, 76.4m for silt, 1.6 m for clay, 1.69 m for soil pH, 9.4 m for organic C, 7.1m for total N, 39.2 m for available P and 7.8 m for exchangeable K. This shows that beyond these ranges, the selected soil properties should be managed differently

An assessment of the scope and comprehensiveness of well-being economy indicator sets: The cases of Iceland, Scotland and New Zealand

Over the last three years, national indicator sets and international coalitions for advancement of the well-being economy's ambitions have begun to be developed. This study applies a capital asset, well-being goals and domains, and Sustainable Development Goals (SDGs) framework to evaluate the scope and comprehensiveness of the indicator sets of Iceland, Scotland and New Zealand. Both national objectives and SDG indicator priorities, determined through each nation's stakeholder consultation process, have greatly shaped the indicator selection process, albeit leading to a narrow concentration in some areas. There is currently more focus on natural capital preservation and environmental performance in the cases of Iceland and New Zealand, whereas Scotland integrates analysis on contributions to human well-being via ecosystem services. Additionally, resources that appear critical to these economies and processes that undermine the productive capacities of the resource base are not represented by indicators. Spatial scale variations are evident too. Domestic phenomena are the focus of Iceland and New Zealand's indicators sets, whilst Scotland's is more internationalist. Despite these inconsistencies, it is evident that the national indicator sets are inclusive and reflective of socio-cultural priorities, including the needs of certain Indigenous peoples, often monitoring criteria that go beyond the limits of the SDGs.

Large-scale spatial variability in urban tolerance of birds.

Quantifying intraspecific and interspecific trait variability is critical to our understanding of biogeography, ecology and conservation. But quantifying such variability and understanding the importance of intraspecific and interspecific variability remain challenging. This is especially true of large geographic scales as this is where the differences between intraspecific and interspecific variability are likely to be greatest. Our goal is to address this research gap using broad-scale citizen science data to quantify intraspecific variability and compare it with interspecific variability, using the example of bird responses to urbanization across the continental United States. Using more than 100 million observations, we quantified urban tolerance for 338 species within randomly sampled spatial regions and then calculated the standard deviation of each species' urban tolerance. We found that species' spatial variability in urban tolerance (i.e. standard deviation) was largely explained by the variability of urban cover throughout a species' range (R2 =0.70). Variability in urban tolerance was greater in species that were more tolerant of urban cover (i.e. the average urban tolerance throughout their range), suggesting that generalist life histories are better suited to adapt to novel anthropogenic environments. Overall, species differences explained most of the variability in urban tolerance across spatial regions. Together, our results indicate that (1) intraspecific variability is largely predicted by local environmental variability in urban cover at a large spatial scale and (2) interspecific variability is greater than intraspecific variability, supporting the common use of mean values (i.e. collapsing observations across a species' range) when assessing species-environment relationships. Further studies, across different taxa, traits and species-environment relationships are needed to test the role of intraspecific variability, but nevertheless, we recommend that when possible, ecologists should avoid using discrete categories to classify species in how they respond to the environment.