Patterns Of Spatial Variation Research Articles

Spatial Variations of Village-Level Environmental Variables from Satellite Big Data and Implications for Public Health–Related Sustainable Development Goals

The United Nations Sustainable Development Goals (SDGs) include 17 interlinked goals designed to be a blueprint for the world’s nations to achieve a better and more sustainable future, and the specific SDG 3 is a public health–related goal to ensure healthy living and promote well-being for all population groups. To facilitate SDG planning, implementation, and progress monitoring, many SDG indicators have been developed. Based on the United Nations General Assembly resolutions, SDG indicators need to be disaggregated by geographic locations and thematic environmental and socioeconomic characteristics for achieving the most accurate planning and progress assessment. High-resolution data such as those captured at the village level can provide comparatively more precise insights into the different socioeconomic and environmental factors relevant to SDGs, therefore enabling more effective sustainable development decision-making. Using India as our study area and the child malnutrition indicators stunting, underweight, and wasting as examples of public health–related SDG indicators, we have demonstrated a process to effectively derive environmental variables at the village level from satellite big datasets on a cloud platform for SDG research and applications. Spatial analysis of environmental variables regarding vegetation, climate, and terrain have shown spatial grouping patterns across the entire study area, with each village group having different statistics. Correlation analysis between these environmental variables and stunting, underweight, and wasting indicators show a meaningful relationship between these indicators and vegetation index, land surface temperature, rainfall, elevation, and slope. Identifying the spatial variation patterns of environmental variables at the village level and their correlations with child malnutrition indicators can be an invaluable tool to facilitate a clearer understanding of the causes of child malnutrition and to improve area-specific SDG 3 implementation planning. This analysis can also provide meaningful support in assessing and monitoring SDG implementation progress at the village level by spatially predicting SDG indicators using available socioeconomic and environmental independent variables. The methodology used in this study has the potential to be applied to other similar regions, especially low-to-middle income countries where a high number of children are severely affected by malnutrition, as well as to other environmentally related SDGs, such as Goal 1 (No Poverty) and Goal 2 (Zero Hunger).

Climatic Factors Determine the Distribution Patterns of Leaf Nutrient Traits at Large Scales.

Leaf nutrient content and its stoichiometric relationships (N/P ratio) are essential for photosynthesis and plant growth and development. Previous studies on leaf nutrient-related functional traits have mainly focused on the species level and regional scale, but fewer studies have investigated the distribution patterns of the leaf N and P contents (LN, LP) and N/P ratios (N/P) in communities and their controlling factors at a large scale; therefore, we used LN, LP, and N/P data at 69 sites from 818 forests in China. The results showed significant differences (p < 0.05) in the LN, LP, and N/P at different life forms (tree, shrub, and herb). Neither LN, LP, nor N/P ratios showed significant patterns of latitudinal variation. With the increase in temperature and rainfall, the LN, LP, and leaf nutrient contents increased significantly (p < 0.001). Across life forms, LN at different life forms varied significantly and was positively correlated with soil P content (p < 0.001). The explanatory degree of climatic factors in shaping the spatial variation patterns of LN and N/P was higher than that of the soil nutrient factors, and the spatial variation patterns of the leaf nutrient traits of different life forms were shaped by the synergistic effects of climatic factors and soil nutrient factors.

Citizen scientist monitoring accurately reveals nutrient pollution dynamics in Lake Tanganyika coastal waters

Several studies in Lake Tanganyika have effectively employed traditional methods to explore changes in water quality in open waters; however, coastal monitoring has been restricted and sporadic, relying on costly sample and analytical methods that require skilled technical staff. This study aims in validating citizen science water quality collected data (nitrate, phosphate and turbidity) with those collected and measured by professional scientists in the laboratory. A second objective of the study is to use citizen scientist data to identify the patterns of seasonal and spatial variations in nutrient conditions and forecast potential changes based on expected changes in population and climate (to 2050). The results showed that the concentrations of nitrate and phosphate measured by citizen scientists nearly matched those established by professional scientists, with overall accuracy of 91% and 74%, respectively. For total suspended solids measured by professional and turbidity measured by citizen scientists, results show that, using 14 NTU as a cut-off, citizen scientist measurements of Secchi tube depth to identify lake TSS below 7.0 mg/L showed an accuracy of 88%. In both laboratory and citizen scientist-based studies, all measured water quality variables were significantly higher during the wet season compared to the dry season. Climate factors were discovered to have a major impact on the likelihood of exceeding water quality restrictions in the next decades (2050), which could deteriorate lake conditions. Upscaling citizen science to more communities on the lake and other African Great Lakes would raise environmental awareness, inform management and mitigation activities, and aid long-term decision-making.

Temporal Changes in Land Use, Vegetation, and Productivity in Southwest China

In recent decades, vegetation coverage and land use/land cover (LULC) have constantly changed, especially in southwest China. Therefore, it is necessary to conduct in-depth research into the temporal–spatial variation patterns of vegetation greening, LULC, and gross primary productivity (GPP). Here, we used remote sensing to analyze the spatial and temporal variation in the normalized difference vegetation index (NDVI) and GPP in the growing season under different LULCs in southwest China. Results showed: (1) From 2000–2019, the forest area in southwest China had increased by 2.1%, while the area of cropland and grassland had decreased by 3.2% and 5.5%, respectively. Furthermore, there are significant differences in spatial variation patterns. (2) NDVI and GPP in the growing season showed a general increasing trend (p &lt; 0.01); vegetation coverage is dominated by high coverage to highest coverage and medium coverage to high coverage transfer. (3) Under different LULCs, the migration directions of NDVI and GPP were different. The center of gravity migration of highest and medium coverage shifted to the southeast by 1.69° and to the northwest by 1.81°, respectively. The results showed the ecosystem evolution and will help to guide the maintenance measure of ecosystem balance and sustainable development.

Spatial-temporal differentiation and dynamic spatial convergence of inclusive low-carbon development: evidence from China.

Promoting green and low-carbon development has become a global consensus. However, few studies have explored the scientific connotation and influencing factors of inclusive low-carbon development (ILCD). Based on the perspective of inclusive growth and sustainable development, this paper constructs an economic growth-social inclusion-low carbon development (ESC) analytical framework and uses the improved entropy weight method to estimate the ILCD level of 30 provinces in China from 2006 to 2020. Kernel density estimation, Moran's I index, and Dagum Gini coefficient decomposition are used to characterize the spatial and temporal variation patterns, and the variation coefficient and the dynamic spatial Durbin model are used to explore the dynamic spatial convergence characteristics. The results show that (1) ILCD in China is increasing steadily overall, but there is a significant spatial non-equilibrium characteristic of high in the east and low in the west. (2) The overall difference in ILCD shows a trend of fluctuation and narrowing, and the imbalance between regions is the primary source of the overall difference. (3) ILCD has significant path dependence and dynamic spatial convergence characteristics in the whole country and the three regions, and the spatial spillover effect tends to be good neighborliness. The rate of convergence shows a trend of national (4.77%) > western (2.33%) > eastern (1.97%) > central (0.96%), and the spatial convergence of the club is gradually becoming prominent. (4) The factors including economic development, technological innovation, urbanization level and human capital significantly affect ILCD, which also has regional heterogeneous. Therefore, it is necessary to break down administrative and market barriers, strengthen cross-regional cooperation and resource interconnectivity, and bring into play policy synergy to provide decision-making reference for achieving inclusive low-carbon development.

Spatial patterns of evolutionary diversity in Cactaceae show low ecological representation within protected areas

Mapping biodiversity patterns across taxa and environments is crucial to address the evolutionary and ecological dimensions of species distribution, suggesting areas of particular importance for conservation purposes. Within Cactaceae, spatial diversity patterns are poorly explored, as are the abiotic factors that may predict these patterns. We gathered geographic and genetic data from 921 cactus species by exploring both the occurrence and genetic databases, which are tightly associated with drylands, to evaluate diversity patterns, such as phylogenetic diversity and endemism, paleo-, neo-, and superendemism, and the environmental predictor variables of such patterns in a global analysis. Hotspot areas of cacti diversity are scattered along the Neotropical and Nearctic regions, mainly in the desertic portion of Mesoamerica, Caribbean Island, and the dry diagonal of South America. The geomorphological features of these regions may create a complexity of areas that work as locally buffered zones over time, which triggers local events of diversification and speciation. Desert and dryland/dry forest areas comprise paleo- and superendemism and may act as both museums and cradles of species, displaying great importance for conservation. Past climates, topography, soil features, and solar irradiance seem to be the main predictors of distinct endemism types. The hotspot areas that encompass a major part of the endemism cells are outside or poorly covered by formal protection units. The current legally protected areas are not able to conserve the evolutionary diversity of cacti. Given the rapid anthropogenic disturbance, efforts must be reinforced to monitor biodiversity and the environment and to define/plan current and new protected areas.

Spatial patterns of macrobenthos taxonomic and functional diversity throughout the ecotones from river to lake: A case study in Northern China

Macrobenthos taxonomic and functional diversity are key indicators of ecosystem health. River–lake ecotones are key macrobenthos habitats. However, we don’t fully understand macrobenthos biodiversity patterns in these ecotones. We studied water environment, sediment heavy metal contents, and macrobenthos community, which we sampled simultaneously from 29 sampling sites along the Fu River–Baiyangdian Lake gradient in Northern China with five field surveys from 2018 to 2019. Six trait classes resolved into 25 categories were allocated to macrobenthos through a binary coding system. We used the RLQ framework (R, environmental variables; L, species of taxa; Q, traits) and fourth-corner analyses to evaluate the relationship between environmental variables and macrobenthos traits. Finally, we carried out variance partitioning to assess the contributions of environmental variables to variation of macrobenthos diversities. As the results, TN and TP contents in the river and lake mouths were lower than those in the adjacent river and lake, indicating that the river–lake ecotones played a role in purifying the water and buffering pollution. High taxonomic diversity of macrobenthos in the lake mouth and the presence of unique taxa in the two ecotones revealed edge effects, but the macrobenthos abundance and biomass were extremely low compared with those in the adjacent river and lake. We found no significant correlation between the taxonomic and functional diversity indices in the river and lake mouths. Water depth, water transparency, TN, and TP were the main water environmental drivers of macrobenthos taxonomic and functional diversity, explaining up to 45.5% and 56.2% of the variation, respectively. Sediment Cd, Cr, Cu, Pb, and Zn contents explained 15.1% and 32.8%, respectively, of macrobenthos taxonomic and functional diversity. Our results suggest that functional diversity approaches based on biological traits can complement taxonomic approaches in river–lake ecotones. Furthermore, improving water depth, transparency, eutrophication, and heavy metal pollution will improve macrobenthos diversity in these ecotones and maintain ecosystem health.

Spatial patterns of benthic biofilm diversity among streams draining proglacial floodplains

Glacier shrinkage opens new proglacial terrain with pronounced environmental gradients along longitudinal and lateral chronosequences. Despite the environmental harshness of the streams that drain glacier forelands, their benthic biofilms can harbor astonishing biodiversity spanning all domains of life. Here, we studied the spatial dynamics of prokaryotic and eukaryotic photoautotroph diversity within braided glacier-fed streams and tributaries draining lateral terraces predominantly fed by groundwater and snowmelt across three proglacial floodplains in the Swiss Alps. Along the lateral chronosequence, we found that benthic biofilms in tributaries develop higher biomass than those in glacier-fed streams, and that their respective diversity and community composition differed markedly. We also found spatial turnover of bacterial communities in the glacier-fed streams along the longitudinal chronosequence. These patterns along the two chronosequences seem unexpected given the close spatial proximity and connectivity of the various streams, suggesting environmental filtering as an underlying mechanism. Furthermore, our results suggest that photoautotrophic communities shape bacterial communities across the various streams, which is understandable given that algae are the major source of organic matter in proglacial streams. Overall, our findings shed new light on benthic biofilms in proglacial streams now changing at rapid pace owing to climate-induced glacier shrinkage.

Elevational biodiversity gradients in the Neotropics: Perspectives from freshwater caddisflies (Insecta: Trichoptera).

Aquatic insects in the order Trichoptera are extremely diverse in number of species and their trophic roles. However, their distribution and diversity patterns are poorly known in the Neotropics, including the species restricted to tropical mountain ecosystems. Recent studies in tropical mountains have shown high levels of endemism of aquatic insects and changes in the composition of communities over short distances. Still, the incidence of environmental filters that explain such patterns has not been addressed quantitatively. Given the relevance of understanding Trichoptera spatial diversity patterns to prioritize conservation areas for freshwaters, as well as to obtain baseline information to predict changes in aquatic communities facing global environmental changes, we assessed the species distribution and assemblages of caddisflies along an elevational gradient from 600 to 3,600 m a.s.l. on the equatorial Andes. In this area, we had long-term continuous climate data with hourly resolution. We collected adult caddisflies in seven localities along this gradient using light traps. We sampled each locality for two hours after sunset for three consecutive days. All specimens collected were identified to species or morphospecies. Our results showed an increase in species and genera numbers with decreasing altitude, albeit no significant. Minimum air temperature is the main environmental variable explaining Trichoptera community assemblages. β‐diversity (taxon turnover among sites), as opposed to species richness, increased with altitude and showed a bimodal distribution along the elevation gradient for both genera and species assemblages, which resulted in a significant shift in community composition of species and genera at 2,000 m a.s.l. Our null-models confirm the observed patterns of B-diversity are non-random and suggest a strong environmental filtering of tropical caddisflies community assemblies and turnover. Geographic distance coupled with changes in environmental conditions along the elevation gradient explained a high percentage of community variance, as documented for other taxa (e.g., vascular plants), suggesting the importance of securing habitat connectivity along the altitudinal gradient to protect aquatic insect diversity effectively.

Use of geographical information systems (GIS) in assessing ecological profile, fish community structure and production of a large reservoir of Himachal Pradesh.

The present study demonstrates the spatial analysis and mapping of fish and different measures of environmental parameters and fish diversity of Pong reservoir, Himachal Pradesh, using Kriging spatial interpolation methods for geographical information system mapping. Seasonal data on environmental parameters, potential fish habitat and fish diversity was collected from lentic (dam), lentic (reservoir), transitional and lotic zone of the reservoir.. Important environmental parameters like water temperature, dissolved oxygen, electrical conductivity, water depth and transparency showed variations across the different zones of the reservoir. The sediment of the reservoir was sandy clay loam in nature as per texture analysis. Fish species richness, Shannon index and evenness index showed a similarity of the lotic and lentic (reservoir) zones of the reservoir. Six potential fish breeding grounds were identified in the reservoir indicating high conservation significance. The analysis of data showed a declining trend in fish production from 456.9 tonnes during the decade 1976-1987 to 347.91 tonnes during 2009-2020. The factors like anthropogenic climate change, predation of a stocked fish juvenile by water birds, undersized fish stocking and unscientific management are the probable reasons for the decreasing fish production. The spatial variation pattern of the water spread area, environmental parameters, fish catch and potential fish breeding grounds depicted in the GIS platform can be used as an important information base by the policy makers for fisheries management. The stocking of large size fish as a stocking material and adequate protection of the potential fish breeding grounds are the key advisories for the sustainable enhancement of fisheries as well as conservation.

Distinguishing Direct Human-Driven Effects on the Global Terrestrial Water Cycle.

Population growth is increasing the pressure on water resource availability. For useful assessment and planning for societal water availability impacts, it is imperative to disentangle the direct influences of human activities in the landscape from external climate‐driven influences on water flows and their variation and change. In this study we used the water balance model, a gridded global hydrological model, to quantify and distinguish human‐driven change components, modified by interventions such as dams, reservoirs, and water withdrawals for irrigation, industry, and households, from climate‐driven change components on four key water balance variables in the terrestrial hydrological system (evapotranspiration, runoff, soil moisture, storage change). We also analyzed emergent effect patterns in and across different parts of the world, facilitating exploration of spatial variability and regional patterns on multiple spatial scales, from pixel to global, including previously uninvestigated parts of the world. Our results show that human activities drive changes in all hydrological variables, with different magnitudes and directions depending on geographical location. The differences between model scenarios with and without human activities were largest in regions with the highest population densities. In such regions, which also have relatively large numbers of dams for irrigation, water largely tends to be removed from storage and go to feed increased runoff and evapotranspiration fluxes. Our analysis considers a more complete set of hydrological variables than previous studies and can guide further research and management planning for future hydrological and water availability trends, including in relatively data‐poor parts of the world.

Lineage dynamics in growing biofilms: Spatial patterns of standing vs. de novo diversity.

Microbial biofilms show high phenotypic and genetic diversity, yet the mechanisms underlying diversity generation and maintenance remain unclear. Here, we investigate how spatial patterns of growth activity within a biofilm lead to spatial patterns of genetic diversity. Using individual-based computer simulations, we show that the active layer of growing cells at the biofilm interface controls the distribution of lineages within the biofilm, and therefore the patterns of standing and de novo diversity. Comparing biofilms of equal size, those with a thick active layer retain more standing diversity, while de novo diversity is more evenly distributed within the biofilm. In contrast, equal-sized biofilms with a thin active layer retain less standing diversity, and their de novo diversity is concentrated at the top of the biofilm, and in fewer lineages. In the context of antimicrobial resistance, biofilms with a thin active layer may be more prone to generate lineages with multiple resistance mutations, and to seed new resistant biofilms via sloughing of resistant cells from the upper layers. Our study reveals fundamental “baseline” mechanisms underlying the patterning of diversity within biofilms.

Persistent Spatial Patterns of Listeria monocytogenes and Salmonella enterica Concentrations in Surface Waters: Empirical Orthogonal Function Analysis of Data from Maryland

High spatiotemporal variability of pathogen concentrations in surface waters complicates the design and interpretation of microbial water quality monitoring. Empirical orthogonal function (EOF) analysis can provide spatial patterns (EOFs) of variability in deviations of concentrations in specific locations from the average concentration across the study area. These patterns can be interpreted to assess the effect of environmental factors on pathogen levels in the water. The first and the second EOFs for Listeria monocytogenes explained 84.4% and 9.7% of the total variance of deviations from average, respectively. That percentage was 50.8% and 45.0% for Salmonella enterica. The precipitation also had a strong explanatory capability (79%) of the first EOF. The first EOFs of Listeria and precipitation were similar at pond sites but were opposite to the precipitation at the stream sites. The first EOF of S. enterica and precipitation demonstrated opposite trends, whereas the second S. enterica EOF pattern had similar signs with the precipitation EOF at pond sites, indicating a relationship between rainfall and Salmonella at these sites. Overall, the rainfall data could inform on persistent spatial patterns in concentrations of the two pathogens at the pond sites in farm settings but not at stream sites located in forested areas.

Gender Representation in Orthopaedic Surgery: A Geospatial Analysis From 2015 to 2022.

IntroductionThe gender disparity in orthopaedic surgery is well-established. According to our analysis, only 7.4% of practicing orthopaedic surgeons in the US are female in 2022. While there are several theories attempting to explain this gender gap, our eight years of data show that limited female representation is a self-perpetuating cycle as areas without female representation almost never improve in that regard. It appears that existing female mentorship is critical to the growth of a female orthopaedic presence in an area. In the present work, we aim to describe how gender diversity in orthopaedic surgery differs across the country, how this diversity is changing over time, and how surgeon gender diversity may be affected by the sociodemographic characteristics making up the counties where orthopaedic surgery is practiced.MethodsA retrospective study was conducted using publicly available National Provider Identifier (NPI) data from 2015 to 2022. Orthopaedic surgeons and their genders were identified using the Provider Type and Gender data elements associated with an individual NPI. Rural-urban and metro characters were defined using the USDA Economic Research Reserve’s rural-urban continuum codes. Python was used for database building and data cleaning. GeoDa, a statistical map-based graphing software, was used to plot and assess demographic, geographic, and socioeconomic trends. Trends in gender diversity from 2015 to 2019 were analyzed for each individual year as well as the time period as an aggregate. Cluster analysis was performed to assess complex spatial patterns of variables that could not be condensed linearly or logarithmically. Moran’s I was used to measure the similarity of a Federal Information Processing System (FIPS) area code to its neighbors. Within the clustering analysis, spatial clusters were broken down into four groups of spatial outliers (High-High, High-Low, Low-High, and Low-Low) referencing a given area’s relationship with its neighbors. Factorial ANOVA between each of the four cluster types was performed using the variables provided in the article to identify significant demographic variables within the cluster analysis.ResultsThere are relative hotspots of gender diversity in the Northwest, Northeast, and Southwest with relative coldspots in the Midwest and Southern US. In counties that are considered gender diversity hotspots, the total population of orthopaedic surgeons increases by 0.94 each year while the population of female orthopaedic surgeons increases by 0.2, suggesting that in areas with high gender diversity, 4.7 male orthopaedic surgeons are joining practices for every 1.0 female. In areas with low gender diversity, the population of orthopaedic surgeons increases by 0.11 surgeons each year while the slope for an increase in female orthopaedic surgeons is 0.Conclusions Orthopaedic surgery lags behind other male-dominated surgical specialties in gender parity. Our analysis demonstrates that certain areas of the country including the Northwest, Northeast, and Arizona have improved gender diversity compared to the rest of the country. We also see that the rate of increase of female orthopaedic surgeons in the past seven years is highest in areas with more preexisting female orthopaedic surgeons, suggesting the importance of a “trailblazer” phenomenon in recruiting female surgeons.

Population genetics of a recent range expansion and subsequent loss of migration in monarch butterflies

Range expansions—whether permanent or transient—strongly influence the distribution of genetic variation in space. Monarch butterflies are best known for long‐distance seasonal migration within North America but are also established as nonmigratory populations around the world, including on Pacific Islands. Previous research has highlighted stepwise expansion across the Pacific, though questions remain about expansion timing and the population genetic consequences of migration loss. Here, we present reduced‐representation sequencing data for 275 monarchs from North America (n = 85), 12 Pacific Islands (n = 136) and three locations in Australia (n = 54), with the goal of understanding (i) how the monarch's Pacific expansion has shaped patterns of population genetic variation and (ii) how loss of migration has influenced spatial patterns of differentiation. We find support for previously described stepwise dispersal across the Pacific and document an additional expansion from Hawaii into the Mariana Islands. Nonmigratory monarchs within the Mariana Islands show strong patterns of differentiation, despite their proximity; by contrast, migratory North American samples form a single genetically panmictic population across the continent. Estimates of Pacific establishment timing are highly uncertain (~100–1,000,000 years ago) but overlap with historical records that indicate a recent expansion. Our data support (i) a recent expansion across the Pacific whose timing overlaps with available historical records of establishment and (ii) a strong role for seasonal migration in determining patterns of spatial genetic variation. Our results are noteworthy because they demonstrate how the evolution of partial migration can drive population differentiation over contemporary timescales.

RAD-sequencing improves the genetic characterization of a threatened tree peony (Paeonia ludlowii) endemic to China: Implications for conservation

Compared with traditional genetic markers, genomic approaches have proved valuable to the conservation of endangered species. Paeonia ludlowii having rarely and pure yellow flowers, is one of the world's most famous tree peonies. However, only several wild populations remain in the Yarlung Zangbo Valley (Nyingchi and Shannan regions, Xizang) in China due to increasing anthropogenic impact on the natural habitats. We used genome-wide single nucleotide polymorphisms to elucidate the spatial pattern of genetic variation, population structure and demographic history of P. ludlowii from the fragmented region comprising the entire range of this species, aiming to provide a basis for conserving the genetic resources of this species. Unlike genetic uniformity among populations revealed in previous studies, we found low but varied levels of intra-population genetic diversity, in which lower genetic diversity was detected in the population in Shannan region compared to those in Nyingzhi region. These spatial patterns may be likely associated with different population sizes caused by micro-environment differences in these two regions. Additionally, low genetic differentiation among populations (Fst = 0.0037) were detected at the species level. This line of evidence, combined with the result of significant genetic differentiation between the two closest populations and lack of isolation by distance, suggested that shared ancestry among now remnant populations rather than contemporary genetic connectivity resulted in subtle population structure. Demographic inference suggested that P. ludlowii probably experienced a temporal history of sharp population decline during the period of Last Glacial Maximum, and a subsequent bottleneck event resulting from prehistoric human activities on the Qinghai-Tibet Plateau. All these events, together with current habitat fragment and excavation might contribute to the endangered status of P. ludlowii. Our study improved the genetic characterization of the endangered tree peony (P. ludlowii) in China, and these genetic inferences should be considered when making different in situ and ex situ conservation actions for P. ludlowii in this evolutionary hotspot region.

The Scope for Using Proximal Soil Sensing by the Farmers of India

Knowledge about spatial distribution patterns of soil attributes is very much needed for site-specific soil nutrient management (SSSNM) under precision agriculture. High spatial heterogeneity exists in the agricultural soils of India due to various reasons. The present practice of assessing the spatial variability of the vast cultivated landscape of India by using traditional soil sampling and analysis is costly and time consuming. Hence, proximal soil sensing (PSS) is an attractive option to assess the plot-scale spatial variability pattern (SVP) of soil attributes for SSSNM. A PSS system, either in a fixed position or mounted on a vehicle (on-the-go), can be used to obtain measurements by having direct contact with soil. PSS measurements provide low-cost and high-density data pertaining to the SVPs of soil attributes. These data can be used to generate digital elevation and soil attribute variability maps at the field scale in a crop production environment. Based on the generated variability maps, locally available and economically feasible agricultural inputs can be applied using variable rate application strategies for sustainable cropping and enhanced farm profit. This overview presents the potential of adopting PSS in India and other developing countries. The scope, challenges, and probable solutions are also proposed. There is ample scope for adoption of PSS in India in view of diverse soil types, climatic conditions, cropping patterns, crop management practices, and ultimately, the ever-increasing demand for higher agricultural production. However, the successful adoption of the PSS technique in India will be dependent on the proper design and adoption of strategies which require adequate planning and analysis. There are several studies that have highlighted the usefulness of soil sensing technologies in Indian soils. There are also certain challenges and limitations associated with PSS in India, which could be addressed. The available proximal soil sensing technologies will be of great help in improving the understanding of soil heterogeneity for adopting SSSNM in order to optimize crop production in India and other developing countries.

Estimation of probabilistic seismic sliding displacement and pseudo-static coefficients (k15) for seismic stability assessment of slopes in the southern Lower Mainland, British Columbia

Seismic stability of slopes across the Lower Mainland, British Columbia, is investigated based on a probabilistic solution of the Newmark sliding block analogy. The various seismicity sources in the region and the latest updates in sliding displacement prediction models are utilized to determine the probabilistic values for the sliding displacement of slopes at 10 sites across the southern Lower Mainland. The probabilistic displacement (Dprob) values of the considered 10 sites are used to assess the spatial variation of Dprob and the pseudo-static seismic coefficient for Dprob = 15 cm (k15) across the Lower Mainland. Based on spatial variation patterns observed at 7 training sites, regression analysis is employed to develop regional interpolation models to estimate Dprob and k15 values. The accuracy of the regression models to regionally interpolate Dprob and k15 values is confirmed considering model residuals. Calculated probabilistic values at 3 additional test sites confirm that the proposed models estimate Dprob and k15 values with minimal error in Dprob (< 5 cm). The application of the developed Dprob and k15 regional interpolation models is presented with an illustrative example from Coquitlam in the northeastern Lower Mainland.

The central Alps comprise a major dispersal barrier between western and eastern populations of two butterfly species

AbstractAimGenetic connectivity and diversity are key components of species' resilience to environmental change. However, the specific factors shaping species' resilience are poorly understood. We here aim to strengthen our understanding of resilience in two butterfly species, by identifying regions of high genetic diversity and barriers to dispersal.LocationEuropean Alps.TaxonCopper butterflies (Lycaena spp.).MethodsWe sampled 21 Lycaena hippothoe and 14 L. virgaureae populations with 18 individuals each in the European Alps. Using 14 and 9 microsatellite markers, respectively, we analysed genetic diversity and population structure (using arlequin, genalex, structure and snmf). We analysed spatial patterns of gene flow and genetic diversity (using an estimated effective migration surface), population demographic history and effective population size (diyabc), habitat suitability (maxent), and isolation by distance, and with resistance (genalex, circuitscape).ResultsWe found higher genetic diversity and a more pronounced genetic structure in L. hippothoe than in L. virgaureae. Both species displayed a major genetic barrier in the central Alps. Western and eastern populations showed the highest genetic diversity in L. hippothoe, but central ones in L. virgaureae. Populations of both species were structured by geodetic distance, and minimum and maximum altitude.Main ConclusionsThe population genetic structure of both Copper butterflies seemed to be strongly affected by population history, demography and geographic features. Valleys and high mountain ridges seem to comprise major dispersal barriers. The high genetic diversity and pronounced population structure found in L. hippothoe seems to be related to a low dispersal ability and closed populations with high local abundances as opposed to L. virgaureae. We suggest that different conservation strategies are needed for these closely related species, focussing on connecting suitable habitats in L. hippothoe and increasing local population sizes in L. virgaureae.

Distinct Amphibian Elevational and Seasonal Phylogenetic Structures Are Determined by Microhabitat Variables in Temperate Montane Streams.

Simple SummaryPhylogenetic structure can be used to understand various ecological patterns. The main objective of the present study was to understand the elevational and seasonal amphibian phylogenetic structures in temperate montane streams. This study was conducted in 13 streams located in lowland and highland sites of Tianping mountain, China, in April, June, August, and October 2017, separately. We found that the elevational spatial patterns were not significantly different, but the seasonal temporal patterns differed significantly for amphibian phylogenetic structures, associated with the variation of microhabitat variables.Phylogenetic structure is a key facet of biodiversity, reflecting the evolutionary history of species, and thus can be used to understand various ecological patterns. Although amphibian phylogenetic structures have been tested across space and time separately, simultaneous quantifications are still needed. In the present study, amphibians in streams of Tianping mountain, China, were selected as the model to investigate their elevational spatial and seasonal temporal patterns of phylogenetic diversity. Specifically, 13 streams located in lowland and highland sites were sampled for amphibians and measured for microhabitat variables in April, June, August, and October 2017, separately. Four phylogenetic structural indices, including Faith’s PD, standardized effect size (SES) of Faith’s PD, mean pairwise phylogenetic distance index (MPD), and SES.MPD, were calculated. Our results revealed that amphibian phylogenetic patterns were not significantly different between lowland and highland sites, but differed significantly between four seasons, associated with distinct community assembly rules (phylogenetically overdispersed vs. phylogenetically clustered). Importantly, these patterns were strongly determined by microhabitat variables such as rock cover, water temperature, and water depth. Our results provide fundamental knowledge to better protect amphibian diversity. Both elevational and seasonal variations are important to understanding the general patterns of amphibian community assembly rules.