Patterns Of Spatial Variation Research Articles

Spatial patterns and driving factors of plant diversity along the urban–rural gradient in the context of urbanization in Zhengzhou, China

Plant diversity is the basis for human survival and development, directly affecting the function and stability of urban ecosystems. Its distribution pattern and causes have been a central issue in ecological and landscape gardening research. Rapid urbanization in Zhengzhou City has led to the fragmentation of urban green spaces and damage to ecosystems, seriously affecting urban biodiversity conservation. Understanding the distribution pattern of plant diversity in the region and its relationship with environmental factors is crucial for maintaining and enhancing urban plant diversity. Plant data from 178 sample plots in the built-up area of Zhengzhou City were collected and combined with environmental factors, and the characteristics of plant diversity, richness patterns, and their main environmental explanations in Zhengzhou City were explored. Results showed that there were 596 plant species belonging to 357 genera and 110 families in the study area. There were five dominant families and four dominant genera. Four distinct spatial patterns of plant diversity were identified along the urban–rural gradient. Urbanization factors such as GDP per capita, house prices, and imperviousness within 500 m from the patch significantly influenced plant diversity. There was an imbalance between the spatial pattern of plant diversity and application of urban landscape greening in Zhengzhou City. Future studies should focus on the application of native plants, curb plant homogenization, and reduce anthropogenic interference, which are conducive to protecting and enhancing urban plant diversity. These results can provide a basis for understanding the distribution pattern and influence mechanism of urbanization factors on plant diversity and serve as a reference for policymakers and planners of plant diversity conservation in Zhengzhou City.

Tree species diversity impacts on ecosystem services of temperate forests

Tree species diversity is crucial for forest ecosystem services as it relates to ecosystem functions. However, it remains unclear how spatially continuous tree species diversity affects multiple ecosystem services in temperate forests that undergo various management practices. We mapped the spatial pattern of tree species diversity represented by the Shannon diversity index, H’ in the temperate forests of Northeast China using 1,028 in situ observations and 846 Sentinel-2 images. We further analysed the relationships between tree species diversity and ecosystem services including carbon storage, water yield, and soil retention, while controlling for the covarying effects of multiple forest attributes including tree height, leaf area index (LAI), and stand age. Our results showed distinct spatial variations in tree species diversity across different forest management practices, with natural forests exhibiting a higher diversity compared to managed natural forests and planted forests. Tree species diversity was found to be positively associated with improved ecosystem services, particularly water yield and soil retention, while the effects plateaued above diversity of 1.0 (Shannon index values). We also showed that LAI was the most important factor influencing carbon storage, while tree species diversity and stand age were crucial for water yield and soil retention. These results highlight the importance of maintaining diverse tree species to improve ecosystem services in temperate forests, providing a robust framework for effectively monitoring and managing forest ecosystems with regards to sustainable forest functioning.

Simulation modelling demonstrates differential performance of connectivity methods in their ability to predict genetic diversity in complex landscapes

ContextThere have been few evaluations of how well different connectivity modelling methods are able to predict the spatial genetic structure and genetic diversity of populations residing in complex landscapes. Given the wide application of connectivity modelling tools in applied conservation planning, it is crucial to broadly evaluate how these models perform across resistance, movement, and population structure conditions in predicting genetic diversity patterns. Such evaluations are critical to provide rigorous, biologically based guidance for conservation and management applications. ObjectivesOur goal was to investigate how the predictions of three connectivity models were related to spatial patterns of genetic diversity complex landscapes, considering factors such as population structure, resistance, genetic drift, genetic disequilibrium, and organism movement abilities. MethodsWe evaluated the performance of several connectivity methods across seven a priori landscape resistance surfaces to provide a broad assessment of their performance. We used CDPOP, an individual-based, spatially explicit population and genetic simulation model, to simulate genetic diversity across these resistance surfaces. This provided a pool of genetic diversity patterns that were the response factor in our simulation experiment. We then simulated landscape connectivity with several popular connectivity methods, including resistant kernels, Circuitscape, and Pathwalker, and evaluated how well they were able to predict spatial patterns of genetic diversity. ResultsResistant kernel outperformed other connectivity methods in predicting landscape patterns of genetic diversity. The strongest relationships occurred when the population process has created spatial structure but has not yet led to significant genetic diversity loss due to drift. The time lag disequilibrium was relatively short. Long simulation times resulted in severe reduction in prediction ability due to drift. ConclusionsResistant kernel predictions were much more strongly related to spatial patterns of genetic diversity than were predictions produced by Circuitscape and Pathwalker, across a large combination of population structures. Strong relationships exist between functional connectivity and genetic diversity, with clearer and stronger associations seen in spatial patterns of allelic richness compared to heterozygosity or spatial effective population size. Our results confirm the strong relationship between genetic diversity and population connectivity, and suggest that computationally efficient incidence function algorithms, such as resistant kernel methods, are well suited to predicting functional connectivity.

Spatial patterns and effects of invasive plants on soil microbial activity and diversity along river corridors

Abstract Background and aims Invasive species represent a threat to the conservation of biological systems. Riparian ecosystems are vulnerable to plant invasions, as waterflow facilitates the dispersal of plant propagules, while invasive species may subsequently impact soil, including soil microbial communities. Downstream connectivity among disparate riverine segments is expected to cause spatial continuity of abiotic and biotic components of riparian ecosystems. Methods We studied diversity of microbial communities in three headwater streams in Central Europe. Plant diversity, soil properties and soil microbiota were assessed on 20 sample plots per river. Soil microbial activity and community-level physiological profiling were used to study the soil microbial community. Results While the α-diversity of plants and soil microbiota was similar among rivers, plant communities were substantially more differentiated than microbial communities. Richness in alien and invasive plants significantly differed among rivers, which was reflected in different spatial patterns of microbial activity and diversity. A high level of spatial continuity was observed in the Kysuca river with straightened riverbed and artificial surfaces in the adjacent areas. The cover of invasive plants affects the composition of microbial functional groups of riverbed soils. Conclusion The expectation of spatial continuity of riverbed soil properties including those of soil microbiota caused by connectivity between different river segments was only partially fulfilled. Spatial continuity strongly depends on the environmental setting and stream characteristics of a particular river. The presence of invasive herbs affected the functional composition of soil microbiota but had no effect on microbial activity and diversity.

Analysis of the Interrelation and Seasonal Variation Characteristics of the Spatial Niche of Dominant Fishery Species-A Case Study of the East China Sea.

The spatial niche has garnered significant attention in ecological research, particularly regarding species distribution patterns. The East China Sea, known for its favorable natural conditions and abundant fishery resources, exhibits diverse spatial distribution patterns among species, shaped by their seasonal physiological needs. This study utilized a habitat suitability index model to explore the spatial distribution patterns of key fishery resources in the East China Sea across four seasons and their interactions. Two methodologies were employed to identify key environmental factors and assess the ecological niche overlap among different species and seasons. Results indicated that the initial method identified water temperature as the critical factor for hairtail, while the subsequent method emphasized water temperature and salinity for hairtail, salinity for small yellow croaker, and water depth for Bombay duck. The main spatial habitat overlap was observed between paired species, likely driven by predator-prey interactions. During summer and autumn, increased overlap among multiple species was primarily influenced by synchronized life cycles. An overlap index formula quantified the seasonal species overlap, showing an increase from spring to winter, reflecting changes in convergent habitat preferences. The peak overlap occurred in winter, driven by overwintering, reduced food competition, and enhanced coexistence potential, while the lowest overlap was noted in spring as overwintering ended and predation and competition intensified.

Oceanographical-driven dispersal and environmental variation explain genetic structure in an upwelling coastal ecosystem

The seascape comprises multiple environmental variables that interact with species biology to determine patterns of spatial genetic variation. The environment imposes spatially variable selective forces together with homogenizing and diverging drivers that facilitate or restrict dispersal, which is a complex, time-dependent process. Understanding how the seascape influences spatial patterns of genetic variation remains elusive, particularly in coastal upwelling systems. Here, we combine genome-wide SNP data, Lagrangian larval dispersal simulated over a hydrodynamic model, and ocean environmental information to quantify the relative contribution of ocean circulation and environmental heterogeneity as drivers of the spatial genetic structure of two congeneric intertidal limpets, Scurria scurra and S. araucana, along the central coast of Chile. We find that a genetic break observed in both limpet species coincides with a break in connectivity shown by the Lagrangian dispersal, suggesting that mean ocean circulation is an important seascape feature, in particular for S. scurra. For S. araucana, environmental variation appears as a better predictor of genetic structure than ocean circulation. Overall, our study shows broad patterns of seascape forcing on genetic diversity and contributes to our understanding of the complex ecological and evolutionary interactions along coastal upwelling systems.

Landscape and soil cover diversity in Polissia and Forest-Steppe of Ukraine

Recent research has revealed the patterns of spatial and temporal variability of crop yields for the Polissia and the Forest-Steppe regions of Ukraine. In addition, the approaches to differentiating agroeconomic and agroecological components in the variability of the productive potential of the territories were developed. Approaches have been developed to quantify the spatial and temporal variability of soil erosion for individual areas of the region. The issue of assessing the impact of erosion processes on crop yields at the regional level remains unresolved. The diversity of landscapes and soil cover in Polissia and the Forest-Steppe of Ukraine was assessed in this article. The research covered 10 administrative regions of the north and northwest of Ukraine, which are located mainly within mixed forests (Polissia) and the eastern European forest steppe (Forest-Steppe). Part of the territory is tangential to the Carpathian mountain forests and the Pontic steppe. Within the study area, 30 WRB soils were identified. The largest area is occupied by Phaeozems Albic (21.7% of the total area of the region). These soils are located mainly in the southern and central parts of the region. In the north of the region, Phaeozems Albic form an almost continuous cover, and to the north, the areas of these soils become island-like. Phaeozems Luvic cover 12.1% of the region's territory. The Phaeozems group also includes Phaeozems Gleyic (0.93%), Phaeozems Haplic (0.13%), and Phaeozems Sodic (1.78%). Albeluvisols Umbric (17.1%) occupy a significant part of the region's territory. These soils occupy the north of the region and extend south along the Dnipro River floodplain. Spatially close to these soils are Albeluvisols Gleyic (12.8%). In the western part of the region, in Prykarpattia, there are Albeluvisols Stagnic (0.82%). The organic carbon content in the soils of the administrative districts of the region in the 0-5 cm layer was 5.2±3.3% and ranged 0.5% to 23.9%. In the layers of 5–15 and 15–30 cm, this figure decreased to 1.9 ± 1.1% and 1.9 ± 1.0%, respectively. In the 30–60 cm layer, the organic carbon content was 1.4 ± 0.8% and ranged 0.1% to 6.1%. The lowest organic carbon content was observed in the north central part of the region, and the highest content was observed in the north-east and north-west of the region. In the south of the region, there was found a strip of soils with moderate organic carbon content. The lowest content of organic carbon is characteristic of Albeluvisols and Podzols, which are located in the north of the region. In turn, the highest content of organic carbon is characteristic of organogenic Histosols, which, together with Albeluvisols and Podzols, form the basis of the soil cover structure of the territories in the northeast and northwest of the region. It should be noted that the agronomic role of these soils is insignificant, and their organic carbon content cannot be considered as a traditional indicator of fertility. Nevertheless, organic carbon is a reliable indicator of the anti-erosion properties of both natural and agricultural soils. The organic carbon content of Chernozems is quite high, which is a factor in the high fertility of these soils and their importance in agricultural production. The organic carbon content of Fluvisols and Gleysols is naturally high. The importance of these hydromorphic soils is due to their high productive potential, which ensures their use in agriculture. It is also worth noting their high seed protection potential. Phaeozems cover a large area of the region and contain a high level of organic carbon. These soils form the basis of agricultural production and forestry in the region. The silt content in the region's soils measured 45.6 ± 8.5%, ranging 19.1% to 57.6%. The north of the region is represented by soils with the lowest silt content (19–41%). In the center, in the west of the region, there is a zone with the highest silt content (53–58%). In other parts of the region, there are transitional levels of silt content in the soil. The clay content in the soils was 30.7 ± 13.8% and ranged 7.4% to 36.0%. The zone with the lowest clay content in soils has been formed in the north. The highest clay content in soils is typical for the southern part in the center of the region. The sand content in soils is highest in the northern part of the region, and the lowest in the southwestern and southern parts of the region.

Microfluctuations in Capillary Lumens Independent of Pericyte Lining Density in the Anesthetized Mouse Cortex.

This study aimed to examine the spatiotemporal coherence of capillary lumen fluctuations in relation to spatial variations in the pericyte lining in the cortex of anesthetized mice. Two-photon microscopic angiography data (previously published) were reanalyzed, and spatial variations in capillary diameter fluctuations at rest and in capillary lining with vascular mural cells were measured along capillary centerlines. Relatively large diameters of the capillaries (5.5 μm) coincided with a dense pericyte lining, while small capillaries (4.3 μm) had a sparse pericyte lining. Temporal variations had a frequency of about 0.1 Hz with an amplitude of 0.5 μm, which were negatively correlated with pericyte lining density. Spatial frequency analysis further revealed a common pattern of spatial variations in capillary diameter and pericyte lining, but temporal variations differed. The temporal variations in capillary lumens were locally distinct from those in neighboring locations, suggesting intrinsic fluctuations independent of the pericyte lining. Capillary lumens in the brain exhibit slow microfluctuations that are independent of pericyte lining. These microfluctuations could affect the distribution of flowing blood cells and may be important for homogenizing their distribution in capillary networks.

Modeling and Spatial Variability of Soil Nutrients - A Case from Soil Health Card Project, India

Ascertaining and mapping soil nutrient data is crucial for governments to maintain soil health on farmlands. As part of the soil health card project, a total of 329 geo-referenced soil samples were collected from Thaticherla village, Anantapur mandal, Andhra Pradesh, India. These samples were analyzed for various soil properties such as soil pH, electrical conductivity (EC), organic carbon (OC), available nitrogen (N), available phosphorus (P), available potassium (K), available sulphur (S), DTPA extractable micronutrients (Fe, Mn, Zn, Cu), and hot water-soluble boron (B) at a depth of 0 to 15 cm. The results showed high variability (>35%) in coefficients of variation in Cu, EC, Zn, and B. The findings indicated positive correlation between Zn and Mn; N and OC; and OC and Zn. The data underwent logarithmic and Box-Cox transformations to achieve normalization. The ordinary kriging method was employed to analyze the spatial variability. The findings revealed that exponential model was appropriate for B, Fe, Mn, Zn, and OC; Gaussian for K; J-Bessel for N; K-Bessel for Cu, P, and S; stable for EC and rational quadratic for pH, respectively. The analysis showed a strong to weak spatial dependency. In the study area, the spatial variability maps exhibited deficiencies of 97%, 96% and 40% for N, OC and Zn, respectively. Therefore, it is urgent to apply suitable manures and fertilizers in the study area to address these issues. The study area exhibited significant variation in spatial patterns, emphasizing the importance of implementing field-specific plans for soil health and environmental management.

From source to lake: Multi‒taxon alpha and beta diversity patterns along a river above 4500 ​m AMSL on the Qinghai‒Tibetan Plateau

Understanding the distribution of species is highly important for optimizing future conservation priorities and strategies at the regional scale. Relatively little attention has been given to multi-taxon aquatic biota in extreme alpine environments. We examined the spatial and temporal patterns of alpha and beta diversity, site-specific contributions to beta diversity and assembly mechanisms of four taxonomic groups (fishes, macroinvertebrates, zooplankton and phytoplankton) from the source to the estuary of the Za'gya Zangbo River above 4500 ​m AMSL (above mean sea level) on the northern Qinghai-Tibetan (Q–T) Plateau. A total of 4 fish species, 45 macroinvertebrate taxa, 17 zooplankton taxa and 56 phytoplankton taxa were found in the study area. No consistent patterns in taxonomic richness were observed across taxa from upstream to estuary. The fish communities had the lowest dissimilarity between communities, the phytoplankton community had the highest dissimilarity in the dry season, and the macroinvertebrate community had the highest dissimilarity in the wet season. The relative importance of the turnover and nestedness components varied considerably across taxa and along spatial gradients. The diversity patterns of macroinvertebrate, zooplankton and phytoplankton communities were significantly correlated with several environmental factors, whereas only the beta diversity of fish was correlated with altitude. Stochastic processes dominated in shaping the macroinvertebrate communities whereas deterministic processes dominated the assembly of the phytoplankton communities. Weak congruence of diversity patterns across taxonomic groups suggested that biological groups cannot serve as reliable surrogates for one another and that multiple biological groups should be included in the biomonitoring of high-altitude rivers on the Q‒T Plateau. The relatively unique species in the upstream area and estuary of the Za'gya Zangbo River harbor should receive more attention in future conservation and management schemes.

Temporal and spatial variation patterns of chlorophyll a in marine ranching under global interannual events

Marine ecosystems are facing numerous environmental challenges due to global climate change. In response to these challenges, the establishment and growth of marine ranching has emerged as a pivotal solution. Chlorophyll a concentration (Chla) is recognized as a valuable indicator for the ecological assessment of marine ranching. This study focused on the spatiotemporal distribution of Chla and its response to environmental factors according to the dataset in the marine ranching area of Haizhou Bay (Lianyungang, Jiangsu, China) from 2003 to 2022. The results showed that Chla had a significant cycle of summer > spring > autumn and was distributed evenly in the central area of the marine ranching. During interannual changes, Chla patches were centered in the central region during 2014, 2015, and 2016. The Chla patches predominantly focused on the eastern area in 2018-2019, shifting to the western area in 2020-2021. The generalized additive model (GAM) indicated that salinity, depth, temperature, biological oxygen demand (BOD5) and SiO3––Si were the main environmental factors affecting Chla during spring, summer and autumn. However, during El Niño events, salinity, depth, temperature, BOD5 and transparency became the main environmental factors. We concluded that salinity, depth and temperature consistently played a crucial role in determining Chla under various climate conditions, and SiO3––Si and transparency will no longer be an environmental factor limiting Chla. In addition, The effect of interannual variability on upwelling and vertical mixing of water layers may potentially alter the spatial distribution pattern of Chla. These findings can offer ideas into predicting the variation of Chla in marine ranching under global interannual events in the future. Furthermore, this can contribute to the comprehensive assessment of ecological benefits and the in-depth construction of marine ranching. Ultimately, it can provide essential data and scientific references for offshore ecological environment assessment and ecosystem restoration.

Community structure and assembly of myxomycetes in northern Chinese forests under geographic barriers

ABSTRACT The study of myxomycete biogeography has a long-standing history and has consistently drawn scholarly interest. Nevertheless, studies focusing specifically on the spatial and temporal distribution patterns of myxomycete diversity are relatively limited, with even fewer investigating the mechanisms driving the generation and maintenance of myxomycete diversity. Therefore, this study selected two geographically distant sampling sites within northern Chinese forests to investigate myxomycete species composition, community structure, environmental drivers, and assembly patterns under geographic barriers. We established plots in the Altai Mountains (ALE) and the Greater Khingan Mountains (GKM), gathered bark and litter, and conducted 80-day moist chamber cultures of myxomycetes. Additionally, myxomycete specimens were collected in the field simultaneously to supplement the data set. This study collected 541 myxomycete specimens belonging to 73 species from 28 genera, spanning 12 families and eight orders. The ALE and the GKM had 20 identical species, accounting for 27% of the total species. Myxomycetes from both regions exhibited abundant occurrence 18 days after cultivation, with the quantity on bark substrates notably higher than on litter. Arcyria pomiformis and Comatricha elegans were the most common species in moist chamber cultures. Mantel test outcomes revealed that environmental factors had no significant impact on myxomycete community similarity between the two areas, aligning with findings from the neutral community model analysis, indicating a predominant influence of stochastic processes on myxomycete community structure in moist chamber cultures. This study represents the first application of a quantitative framework to analyze myxomycete community assembly cultivated in moist chambers.

Analysis of Spatial Divergence in Bird Diversity Driven by Built Environment Characteristics of Ecological Corridors in High-Density Urban Areas

Urban ecological corridors play an important role in facilitating bird migration and maintaining biodiversity in urban landscapes as key connections between habitat patches. However, the effects of built environment characteristics of urban ecological corridors on bird diversity have not been well understood. In this study, we used Minhang District, Shanghai, as an example to describe the built environment of urban ecological corridors through three dimensions (habitat characteristics, degree of surrounding urbanization, and degree of slow-traffic connectivity). We calculated species richness, abundance, Shannon–Wiener index, and Simpson Index to assess bird diversity based on the bird observation dataset from the Citizen Science Data Sharing Platform. The effects of built environment characteristics of urban ecological corridors on bird diversity were quantified by the Generalized Linear Model. The results showed that: (1) There were significant differences in the built environment characteristics of urban ecological corridors, which formed the spatial differentiation pattern of bird diversity. (2) Different built environment features of urban ecological corridors have different impacts on bird diversity. Habitat suitability of urban ecological corridors was positively correlated with bird diversity, with birds preferring to inhabit waters with an area of more than 1 ha. The degree of urbanization was negatively correlated with bird diversity, with distance to the center of the area proving to have the strongest positive effect. The degree of slow-traffic connectivity proved that low-intensity human activities in urban ecological corridors had a lower impact on bird diversity. The above findings can provide scientific reference for the construction of urban and regional ecological networks in the future.

Plant phylogenetic diversity along the urban–rural gradient and its association with urbanization degree in Shanghai, China

ContextThe spatial distribution of plant diversity in urban areas is fundamental to understanding the relationship between urbanization and biodiversity. Previous research has primarily focused on taxonomic levels to assess species richness. In contrast, investigations into the spatial patterns of phylogenetic diversity in urban plants remain limited.ObjectivesThis study aims to investigate the spatial patterns of plant phylogenetic diversity along an urban–rural gradient and quantify how phylogenetic diversity and the degree of urbanization are related.MethodsA survey of vascular plants was conducted at 134 randomly selected sample plots along four urban–rural transects in Shanghai, China. Three phylogenetic diversity metrics were calculated: Faith’s phylogenetic diversity (PD), net relatedness index (NRI), and net nearest taxon index (NTI), along with the urbanization degree index (UDI). Regression analysis was employed to quantify the spatial patterns of plant phylogenetic diversity across different taxa along the urban–rural gradients and their relationships with UDI.ResultsThe study observed seven distinct patterns of plant phylogenetic diversity along the urban–rural gradients in different taxa, which support the previous hypotheses that biological distribution patterns at the species level also hold true at the phylogenetic level. Faith’s phylogenetic diversity (PD) showed a linear increase with increasing UDI for total, woody, perennial, and cultivated plant assemblages. The UDI explained 3–36% of the variation in PD for these taxa. In contrast, PD for annual and spontaneous plants exhibited a linear decrease with increasing UDI, which explained 25% and 3% variation in PD for annual and spontaneous plants, respectively. The net relatedness index (NRI) for woody, perennial, and cultivated plants, as well as the net nearest taxon index (NTI) for perennial and cultivated plants, linearly increases with UDI, whereas the NRI for total, annual, and spontaneous plants, as well as NTI for total, woody, annual, and spontaneous plants linearly decrease with UDI. However, some of these trends were only marginally significant.ConclusionsThe spatial patterns of plant phylogenetic diversity varied along the urban-to-rural gradients, indicating that urban environmental filtering has an impact on plant phylogenetic diversity. Urbanization increased the phylogenetic richness of different plant taxa in Shanghai but resulted in more clustering and relatedness of species within plant assemblages. Phylogenetic richness exhibited a linear increase with UDI, while the phylogenetic divergence decreased with UDI. The UDI is a useful predictor for examining variations in plant phylogeny due to urbanization. Our findings provide insights into how urbanization impacts plant phylogenetic diversity, helping urban plant diversity conservation.

Information extraction of seasonal dissolved oxygen in urban water bodies based on machine learning using sentinel-2 imagery: An open access application in Baiyangdian Lake

Water bodies are crucial components of urban ecology. The development of rapid and timely water-quality assessment tools using easily measured variables is essential for the health management of urban water bodies. In this study, we focused on the dissolved oxygen (DO) of Baiyangdian Lake using 251 sets of empirically measured water quality data and corresponding Sentinel-2 satellite images. Nine machine learning algorithms were then used to develop a rapid detection algorithm for the spatial distribution of the DO concentration in Baiyangdian Lake. This study successfully applied these methods to invert the DO concentration in Baiyangdian Lake during spring, summer, and autumn. The results indicated that extra tree regression (ETR) provided the most accurate and stable results for inverting the DO concentration among the nine machine learning methods. In contrast, AdaBoost regression (ABR), Bayesian ridge regression (BRR), and support vector machines (SVM) exhibit relatively poor regression performance and lack sensitivity to DO concentrations. Moreover, the DO concentration in Baiyangdian Lake ranged from approximately 0 to 12 mg/L, with notable spatiotemporal variations. The highest overall DO concentration was observed in the spring, particularly in the southern region. The DO concentration significantly decreased during summer compared to that in spring, with higher values in the southwestern area and lower values in the northern region. The DO concentration reached its lowest value in autumn, with slightly higher values in the southern region. This study focused on the estimation and inversion of DO concentrations in the water bodies of Baiyangdian Lake. By introducing and comparing the performances of commonly used machine learning models, a rapid estimation of the DO concentration was achieved, thereby overcoming the limitations of traditional water quality monitoring methods in DO inversion. It not only intuitively explained the temporal and spatial variation patterns of DO concentration but also laid a foundation for further in-depth exploration of the interactions between DO and other water quality parameters.

The structure of the environment influences the patterns and genetics of local adaptation

Abstract Environmental heterogeneity can lead to spatially varying selection, which can, in turn, lead to local adaptation. Population genetic models have shown that the pattern of environmental variation in space can strongly influence the evolution of local adaptation. In particular, when environmental variation is highly autocorrelated in space local adaptation will more readily evolve. However, there have been few attempts to test this prediction empirically or characterize the consequences it would have for the genetic architecture underlying local adaptation. In this study, I analyze a large-scale provenance trial conducted on lodgepole pine and find suggestive evidence that spatial autocorrelation in environmental variation is related to the strength of local adaptation that has evolved in that species. Motivated by those results, I use simulations to model local adaptation to different spatial patterns of environmental variation. The simulations confirm that local adaptation is expected to increase with the degree of spatial autocorrelation in the selective environment, but also show that highly heterogeneous environments are more likely to exhibit high variation in local adaptation, a result not previously described. I find that the spatial pattern of environmental variation influences the genetic architectures underlying local adaptation. In highly autocorrelated environments, the genetic architecture of local adaptation tends to be composed of high-frequency alleles with small phenotypic effects. In weakly autocorrelated environments, locally adaptive alleles may have larger phenotypic effects but are present at lower frequencies across species’ ranges and experience more evolutionary turnover. Overall, this work emphasizes the profound importance that the spatial pattern of selection can have on the evolution of local adaptation and how spatial autocorrelation should be considered when formulating hypotheses in ecological and genetic studies.

Identifying areas of conservation importance based on spatial patterns of evolutionary diversity for non-volant small mammals in the Andean Puna

Ecosystems around the world face a variety of threats from anthropogenic activities and drylands are among the most affected due to their unique environmental characteristics. To maintain phylogenetic history and ecological functionality in these areas, it is imperative to preserve community structure and composition by identifying and protecting key conservation areas. Various methods have been used to define these areas in need of protection; in this study, we used patterns of taxonomic and phylogenetic diversity in the arid lands of the Altiplano-Puna Bioregion of South America, using non-volant small mammal communities as a model system. Based on detailed records of species presence in the study area we estimated indices of species richness and phylogenetic redundancy. The geographic distribution of these indices was then compared to the distribution of protected areas in the region. These analyses identified areas around Lake Titicaca as being of exceptional conservation importance and in need of protection efforts. We propose a network of interconnected areas that together would provide high conservation value while allowing genetic exchange and facilitating ecological processes across landscapes.

Reversing the decline of threatened koala (Phascolarctos cinereus) populations in New South Wales: Using genomics to enhance conservation outcomes.

Genetic management is a critical component of threatened species conservation. Understanding spatial patterns of genetic diversity is essential for evaluating the resilience of fragmented populations to accelerating anthropogenic threats. Nowhere is this more relevant than on the Australian continent, which is experiencing an ongoing loss of biodiversity that exceeds any other developed nation. Using a proprietary genome complexity reduction-based method (DArTSeq), we generated a data set of 3239 high quality Single Nucleotide Polymorphisms (SNPs) to investigate spatial patterns and indices of genetic diversity in the koala (Phascolarctos cinereus), a highly specialised folivorous marsupial that is experiencing rapid and widespread population declines across much of its former range. Our findings demonstrate that current management divisions across the state of New South Wales (NSW) do not fully represent the distribution of genetic diversity among extant koala populations, and that care must be taken to ensure that translocation paradigms based on these frameworks do not inadvertently restrict gene flow between populations and regions that were historically interconnected. We also recommend that koala populations should be prioritised for conservation action based on the scale and severity of the threatening processes that they are currently faced with, rather than placing too much emphasis on their perceived value (e.g., as reservoirs of potentially adaptive alleles), as our data indicate that existing genetic variation in koalas is primarily partitioned among individual animals. As such, the extirpation of koalas from any part of their range represents a potentially critical reduction of genetic diversity for this iconic Australian species.

Evaluating the utility of weather generators in crop simulation models for in-season yield forecasting

CONTEXTCrop yield forecasting is crucial for ensuring food security and adapting to the impacts of climate change, as it provides early insights into potential harvest outcomes and helps farmers and policymakers make informed decisions in the face of changing environmental conditions. The accuracy of the crop model–based yield forecasting frameworks is affected by the uncertainty in future weather data, which is often substituted with synthetic weather realizations generated by stochastic weather generators. OBJECTIVEThis study aims to assess the performance of three recent stochastic weather generators—Global Weather Generator (GWGEN), WeatherGEN, and R Multi-Sites Autoregressive Weather GENerator (RMAWGEN) — in producing synthetic weather realizations that accurately represent regional climate variations and their impact on winter wheat yield forecasting. METHODSWe utilized historical weather data from Daymet, an interpolation of daily meteorological observations that produces gridded datasets with a spatial resolution of 1 km. This data was used both as an input for the weather generators and for evaluating the performance of the generated weather realizations. Furthermore, the weather realizations generated by these weather generators across multiple winter wheat field sites in Kansas were employed in the calibrated Environmental Policy Integrated Climate (EPIC) crop model to assess the potential impact of variations in weather generators on the accuracy of crop yield forecasts. RESULTS AND CONCLUSIONSRMAWGEN and WeatherGEN excelled in accurately simulating rainy days and precipitation amounts, with WeatherGEN particularly effective in wet months and RMAWGEN performing best in dry months, showcased their proficiency in diverse weather conditions. RMAWGEN consistently showed lowest error across all variables, including precipitation, solar radiation, and both maximum and minimum temperatures. Except for GWGEN, both RMAWGEN and WeatherGEN demonstrate good agreement with Daymet in replicating spatial variability patterns. RMAWGEN notably outperformed other weather generators, particularly during the forecasting period. Consequently, it showed superior capabilities in forecasting crop yields closely matching the simulated results with Daymet data. SIGNIFICANCEThe findings of this study are crucial for selecting accurate weather data estimates for crop yield forecasting. Utilizing alternative sources such as ensembles of multiple weather generators or outputs from sub-seasonal multi-model forecast systems may further enhance the accuracy of crop yield forecasts.

Understanding impact of urban sprawl over sanitation risks using GIS‐based multicriteria decision‐making approach

AbstractUrban sprawl and the shortage of proper sanitary infrastructures significantly jeopardize public health and urban sustainability. The problem is further aggravated as a result of the rapid urbanization and urban sprawl. This study investigated the relationship between urban sprawl and sanitation risk conditions in a rapidly growing city in India. This was accomplished by investigating changes in urban sprawl areas between the periods 2000–2020 using multispectral satellite images and Shanon's entropy model and studying the pattern of spatial variations in basic sanitation services derived from the 100 household‐based surveyed WASH (water availability, sanitation, and hygiene) data collected in 2018 before COVID‐19 from 45 sprawl regions. Spatial statistical techniques, namely, the inverse distance weighted (IDW) interpolation and the multicriteria decision technique, were employed for neighborhood analysis and assessing sanitation risks inside the sprawl region. Results showed that Raipur exhibited urban sprawl and around 93.68% of the sprawl area was classified between high (6.47%)‐ and medium (80.52%)‐risk zones.