Large Geographic Scales Research Articles

Regional climate moderately influences species-mixing effect on tree growth-climate relationships and drought resistance for beech and pine across Europe

Increasing species diversity is considered a promising strategy to mitigate the negative impacts of global change on forests. However, the interactions between regional climate conditions and species-mixing effects on climate-growth relationships and drought resistance remain poorly documented.In this study, we investigated the patterns of species-mixing effects over a large gradient of environmental conditions throughout Europe for European beech (Fagus sylvatica L.) and Scots pine (Pinus sylvestris L.), two species with contrasted ecological traits. We hypothesized that across large geographical scales, the difference of climate-growth relationships and drought resistance between pure and mixed stands would be dependent on regional climate. We used tree ring chronologies derived from 1143 beech and 1164 pine trees sampled in 30 study sites, each composed of one mixed stand of beech and pine and of the two corresponding pure stands located in similar site conditions. For each site and stand, we used Bootstrapped Correlation Coefficients (BCCs) on standardized chronologies and growth reduction during drought years on raw chronologies to analyze the difference in climate-tree growth relationships and resistance to drought between pure and mixed stands.We found consistent large-scale spatial patterns of climate-growth relationships. Those patterns were similar for both species. With the exception of the driest climates where pure and mixed beech stands tended to display differences in growth correlation with the main climatic drivers, the mixing effects on the BCCs were highly variable, resulting in the lack of a coherent response to mixing. No consistent species-mixing effect on drought resistance was found within and across climate zones. On average, mixing had no significant effect on drought resistance for neither species, yet it increased pine resistance in sites with higher climatic water balance in autumn. Also, beech and pine most often differed in the timing of their drought response within similar sites, irrespective of the regional climate, which might increase the temporal stability of growth in mixed compared to pure stands.Our results showed that the impact of species mixing on tree response to climate did not strongly differ between groups of sites with distinct climate characteristics and climate-growth relationships, indicating the interacting influences of species identity, stand characteristics, drought events characteristics as well as local site conditions.

DASCO: A workflow to downscale alien species checklists using occurrence records and to re-allocate species distributions across realms

Information about occurrences of alien species is often provided in so-called checklists, which represents lists of reported alien species in a region. In many cases, available checklists cover whole countries, which is too coarse for many analyses and limits capabilities of assessing status and trends of biological invasions. Information about point-wise occurrences is available in large quantities at online facilities such as GBIF and OBIS, which, however, do not provide information about the invasion status of individual populations. To close this gap, we here provide a semi-automated workflow called DASCO to downscale regional checklists using occurrence records obtained from GBIF and OBIS. Within the workflow, coordinate-based occurrence records for species listed in the provided regional checklists are obtained from GBIF and OBIS, and the status of being an alien population is assigned using the information in the provided checklists. In this way, information in checklists is made available at the local scale, which can then be re-allocated to any other spatial categorisation as provided by the user. In addition, habitats of species are determined to distinguish between marine, brackish, terrestrial, and freshwater species, which allows splitting the provided checklists to the respective realms and ecoregions. By using checklists of global databases, we showcase the usage of the DASCO workflow and revealed > 35 million occurrence records of alien populations in terrestrial and marine regions worldwide, which were back-transformed to terrestrial and marine regions for comparison. DASCO has the potential to be used as a basis for the widely applied species distribution models or assessments of status and trends of biological invasions at large geographic scales. The workflow is implemented in R and in full compliance with the FAIR data principles of open science.

Linking tree water use efficiency with calcium and precipitation.

Water use efficiency (WUE) is a key physiological trait in studying plant carbon and water relations. However, the determinants of WUE across a large geographical scale are not always clear, limiting our capacity to predict WUE in response to future global climate change. We propose that tree WUE is influenced by calcium (Ca) availability and precipitation. In addition, although it is well-known that transpiration is the major driving force for passive nutrient uptake, the linkage between these two processes has not been well-established. Because Ca uptake is an apoplastic and passive process that purely relies on transpiration, and there is no translocation once assimilated, we further developed a theoretical model to quantify the relationship between tree Ca accumulation and WUE using soil-to-plant calcium ratio (SCa/BCa) and tree WUE derived from δ13C. We tested our theoretical model and predicted relationships using three common tree species across their native habitats in Northern China, spanning 2300km and a controlled greenhouse experiment with soil Ca concentrations manipulated. We found that tree WUE was negatively related to precipitation of the growing season (GSP) and positively with soil Ca. A multiple regression model and a path analysis suggested a higher contribution of soil Ca to WUE than GSP. As predicted by our theoretical model, we found a positive relationship between WUE and SCa/BCa across their distribution ranges in all three tree species and in the controlled experiment for one selected species. This relationship suggests a tight coupling between water and Ca uptake and the potential use of SCa/BCa to indicate WUE. A negative relationship between SCa/BCa and GSP also suggests a possible decrease in tree Ca accumulation efficiency in a drier future in Northern China.

Assessing Land Subsidence-Inducing Factors in the Shandong Province, China, by Using PS-InSAR Measurements

Shandong Province (SDP) experienced serious land subsidence from March 2017 to December 2020. Exploring the response relationships between land subsidence and its inducing factors plays an important role in ensuring the development of the economy and residential safety. Firstly, we applied Persistent Scatterers Interferometric Aperture Radar (PS-InSAR) technology to 558 Sentinel-1 images to determine the land subsidence in SDP from March 2017 to December 2020. Secondly, we mosaicked the land subsidence monitoring results of five tracks to obtain a land subsidence map covering the whole SDP and validated the land subsidence monitoring results using Global Positioning System (GPS) monitoring results and leveling benchmark monitoring results observed in the same period. Finally, the response relationships between the land subsidence and its inducing factors in SDP were analyzed. The findings are as follows: (1) the PS-InSAR outcomes showed that the land subsidence was widely distributed in SDP and that the maximum land subsidence rate was −298.9 mm/year during the study period. (2) The PS-InSAR monitoring results coincide well with the GPS monitoring results and leveling benchmark monitoring results; the Pearson correlation coefficient (PCC) values between the PS-InSAR monitoring results and the GPS measurement results and leveling benchmark monitoring results were 0.97 and 0.98, respectively. We found that Spearman’s rank correlation coefficient (SRCC) values between any two adjacent tracks of the mosaic PS-InSAR monitoring results were greater than 0.95, indicating good consistency. (3) The long-term overexploitation of groundwater in middle and deep aquifers and mining of underground mineral resources are the main inducing factors of land subsidence in SDP when considering this problem on a large geographical scale. Moreover, the type of bridge material is an important inducing factor causing the large variation in the land subsidence of the bridge body within a small geographical range. These findings may provide scientific support for land subsidence control measures in SDP.

Enhanced Automatic Identification of Urban Community Green Space Based on Semantic Segmentation

At the neighborhood scale, recognizing urban community green space (UCGS) is important for residential living condition assessment and urban planning. However, current studies have embodied two key issues. Firstly, existing studies have focused on large geographic scales, mixing urban and rural areas, neglecting the accuracy of green space contours at fine geographic scales. Secondly, the green spaces covered by shadows often suffer misclassification. To address these issues, we created a neighborhood-scale urban community green space (UCGS) dataset and proposed a segmentation decoder for HRNet backbone with two auxiliary decoders. Our proposed model adds two additional branches to the low-resolution representations to improve their discriminative ability, thus enhancing the overall performance when the high- and low-resolution representations are fused. To evaluate the performance of the model, we tested it on a dataset that includes satellite images of Shanghai, China. The model outperformed the other nine models in UCGS extraction, with a precision of 83.01, recall of 85.69, IoU of 72.91, F1-score of 84.33, and OA of 89.31. Our model also improved the integrity of the identification of shaded green spaces over HRNetV2. The proposed method could offer a useful tool for efficient UCGS detection and mapping in urban planning.

Below Average Midsummer to Early Autumn Precipitation Evolved Into the Main Driver of Sudden Scots Pine Vitality Decline in the Swiss Rhône Valley

The vitality of Scots pine (Pinus sylvestris L.) is declining since the 1990s in many European regions. This was mostly attributed to the occurrence of hotter droughts, other climatic changes and secondary biotic stressors. However, it is still not well understood which specific atmospheric trends and extremes caused the observed spatio-temporal dieback patterns. In the Swiss Rhône valley, we identified negative precipitation anomalies between midsummer and early autumn as the main driver of sudden vitality decline and dieback events. Whereas climate change from 1981 to 2018 did not lead to a reduced water input within this time of the year, the potential evapotranspiration strongly increased in spring and summer. This prolonged and intensified the period of low soil moisture between midsummer and autumn, making Scots pines critically dependent on substantial precipitation events which temporarily reduce the increased water stress. Thus, local climate characteristics (namely midsummer to early autumn precipitation minima) are decisive for the spatial occurrence of vitality decline events, as the lowest minima outline the most affected regions within the Swiss Rhône valley. Mortality events will most likely spread to larger areas and accelerate the decline of Scots pines at lower elevations, whereas higher altitudes may remain suitable Scots pine habitats. The results from our regional study are relevant on larger geographic scales because the same processes seem to play a key role in other European regions increasingly affected by Scots pine dieback events.

FILTERING LPIS DATA FOR BUILDING TRUSTWORTHY TRAINING DATASETS FOR CROP TYPE MAPPING: A CASE STUDY IN GREECE

Abstract. The need for effective crop monitoring in large geographical scales has become increasingly important in recent years and constitutes a technological and scientific challenge for remote sensing applications. In Europe, member states of the European Union collect geospatial data in the framework of the Land Parcel Information System (LPIS) for agricultural management and subsidizing farmers. These data can be exploited as training datasets of machine learning classifiers for crop-type mapping applications. However, the way the LPIS data are being generated, concerning primarily errors in the farmers’ declarations in terms of crop-type labels, exact geometries, etc, constrains their direct use in such classification frameworks. In this study, we present and assess a methodology for filtering LPIS data based on geometric and spectral criteria in order to build a trustworthy training dataset for machine learning crop-type classifiers. A new nomenclature was developed, oriented towards the spectral discrimination of crop-type classes and sub-classes in Greece. The filtering methodology was applied at national scale for the agricultural year of 2019 and resulted in the selection of a sub-set of the LPIS parcels that were assessed as the most suitable and reliable to represent the different levels of the nomenclature. The developed filtering procedure was validated against actual crop-type labels derived from field visits, while the resulted filtered data were successfully utilized on various crop-type mapping experiments in Greece.

Unraveling the Mugil curema complex of American coasts integrating genetic variations and otolith shapes

The white mullet, Mugil curema, is a commercially important species in coastal areas, with a large phenotypic variability and genetic dissimilarity among populations throughout its distribution. For management purposes it is important to determine whether the morphological variability reflects the genetic differences among groups. This study evaluates whether the genetic differentiation in Mugil curema is reflected in the otolith shape on a large geographic scale in the Neotropical Atlantic and the Mexican Pacific. We analyzed the COI (Cytochrome Oxidase I) gene polymorphism as a marker and followed the otolith contour-based Fourier analysis as a morphometric method. Seven locations were studied, four in coastal lagoons of the Gulf of Mexico, one in the Mexican Pacific, one in the Caribbean Sea at Nueva Esparta, Venezuela and one in San Antonio Lagoon, Brazil. The genetic divergence accounted by the COI and the morphological differentiation in M. curema otoliths did not, in general, present cross-scale patterns, and the variability of otolith shapes was not reflected in the mitochondrial genetic variability. Other molecular methods could potentially reveal genetic differences. In particular, the variability in otolith shape among the Gulf of Mexico individuals may indicate that local divergences are accumulated in the otoliths, reflecting a possible interaction effect between local and regional drivers that is not evidenced at the genetic level.

A Bocage Landscape Restricts the Gene Flow of Pest Vole Populations.

The population dynamics of most animal species inhabiting agro-ecosystems may be determined by landscape characteristics, with agricultural intensification and the reduction of natural habitats influencing dispersal and hence limiting gene flow. Increasing landscape complexity would thus benefit many endangered species by providing different ecological niches, but it could also lead to undesired effects in species that can act as crop pests and disease reservoirs. We tested the hypothesis that a highly variegated landscape influences patterns of genetic structure in agricultural pest voles. Ten populations of fossorial water vole, Arvicola scherman, located in a bocage landscape in Atlantic NW Spain were studied using DNA microsatellite markers and a graph-based model. The results showed a strong isolation-by-distance pattern with a significant genetic correlation at smaller geographic scales, while genetic differentiation at larger geographic scales indicated a hierarchical pattern of up to eight genetic clusters. A metapopulation-type structure was observed, immersed in a landscape with a low proportion of suitable habitats. Matrix scale rather than matrix heterogeneity per se may have an important effect upon gene flow, acting as a demographic sink. The identification of sub-populations, considered to be independent management units, allows the establishment of feasible population control efforts in this area. These insights support the use of agro-ecological tools aimed at recreating enclosed field systems when planning integrated managements for controlling patch-dependent species such as grassland voles.

Variation and determinants of leaf anatomical traits from boreal to tropical forests in eastern China

Leaf anatomical traits are responsive to environmental factors and thus highly plastic in their development and biochemical function. However, how they vary across large geographical scales and the main driving factors remain unclear, especially for forest plants. Here, by combining field sampling with plant semi-thin sectioning methods, eight anatomical traits (including leaf epidermis and mesophyll traits, leaf midrib and vascular traits) that can fully reflect leaf structure were measured in 60 plant species inhabiting eight forests in eastern China, and their geographical patterns and possible determinants were explored. Our results showed that leaf anatomical traits varied significantly among different plant functional types (PFTs), and phylogeny had a negligible effect on them. At the species level, leaf anatomical traits exhibited significant geographical patterns, and the thickness of leaf tissues tended to increase from boreal to tropical forests. Compared to leaf epidermis and mesophyll traits, leaf midrib and vascular traits showed similar and more significant geographical patterns. Moreover, the spatial variations in leaf anatomical traits were mainly determined by the shifts in PFTs, while climate and soil nutrient availability had relatively marginal effects. Our findings emphasized that leaf anatomical trait coordination could reflect the resource trade-off and utilization strategies of plants, which is expected to improve our understanding of the responses and adaptation mechanisms of plants to environmental changes.

DEVELOPMENT OF AUTOMATED SATELLITE DATA DOWNLOADING AND PROCESSING PIPELINE ON AWS CLOUD FOR NEAR-REAL-TIME AGRICULTURE APPLICATIONS

Abstract. Remote sensing satellites allow users to acquire detailed information about the Earth's surface on a temporal basis. Widen time-series analysis at a large geographical scale involves a huge amount (in Terabytes) of satellite data downloading and processing operations. Such processes need good computational power, large storage, and sophisticated tools. Maintaining such infrastructure can cost heavily to the research/commercial enterprises. To overcome such issues, Amazon Web Service (AWS) offers a sophisticated cloud computing environment. We developed an in-house automated satellite data downloading and processing (ADDPro) pipeline on the AWS platform. The ADDPro pipeline employed Sentinel-2 satellite data to offer current and relative vegetation health information of the agriculture region on a temporal basis at the pan-India scale. Image compositing and multi-sensor data fusion technique have been incorporated into the ADDPro pipeline to produce cloud-free raster (GeoTIFF) outputs. ADDPro pipeline also facilitates lossless raster data compression, which reduces AWS data transfer costs between regions. Data compression also aids in reducing raster publishing time on GeoServer. Operationally, AWS allows users to download only the bands required to generate a certain index (e.g. NDVI) rather than the entire Sentinel-2 data package. The entire ADDPro pipeline is extremely cost-effective, efficient, and scalable.

RESEARCH ON NDVI NORMALIZATION METHOD BASED ON GF IMAGES

Abstract. The existing NDVI products have problems in terms of low spatial resolution and inconsistent values at a large geographical scale. Based on medium and high-resolution multi-source remote sensing data (GF-1 and GF-2 data), this paper normalized NDVI by combining absolute radiation normalization with relative radiation normalization. And the existing relative radiation normalization method, single-scene global linear normalization (SGloLM) method, is improved to adapt to the production of large-range high-resolution NDVI products. Aiming at the problem of obvious mosaic seams when the SGloLM method is applied to multi-scene images, it is mainly improved from two aspects. One is to improve the coefficient solution of the SGloLM algorithm and propose a new method considering the surrounding multi-scene data, the multi-scene global linear model (MGloLM). The other is to incorporate the Maximum Value Composite (MVC) method to synthesize the maximum value of NDVI at different times in a season, to represent the optimal situation of vegetation growth in the current season. In this study, combined experiments of different methods were performed, as well as qualitative and quantitative evaluations. The experimental results show that SGloLM+MVC and the MGloLM+MVC methods can better eliminate the mosaic seams, and their histogram is most similar to the histogram of standard data, and all quantitative evaluation indexes of SGloLM+MVC are optimal (CC=0.7804, MAD=0.0643, RMSE=0.1012).

The geography of social vulnerability and nursing home facility factors related to infectious disease transmission

Background: The impacts of health inequities on healthcare access, utilization, and outcomes have been highlighted by the COVID-19 pandemic, but these issues have been ongoing, yet understudied, in infectious disease epidemiology. Health inequities affect access to care, quality of care, and health outcomes in all healthcare settings. One healthcare setting that has yet to be fully studied in the context of health inequities is nursing homes. Nursing homes have a host of facility and population-specific issues that differ from other healthcare settings, making the impacts of health inequities likely unique and imperative to understand. The impacts of health inequities on nursing homes are unclear, and they likely have downstream effects on trends in morbidity, mortality, and transmission of multidrug-resistant organisms (MDROs) and other pathogens. Method: Here, we present a descriptive analysis, integrating multiple datasets relating to nursing home facility factors (data from the CMS Provider of Services and the CDC NHSN), nursing-home staffing trends (data from the CMS Payroll-Based Journal data), and social vulnerability (data from the CDC Social Vulnerability Index). We conducted a spatial analysis of nursing-home locations and the social vulnerability of the area. Results: Investigations of facilities and health inequities are best conducted in small spatial geographies. Analyses with less detailed spatial geographies miss high levels of heterogeneity in social vulnerability. Figure 1 provides an example, showing that analyzing nursing homes at a smaller spatial scale (ie, healthcare service area or HSA) shows heterogeneity in poverty levels that might be overlooked at a rough spatial scale, like Hospital Referral Regions (HRR). The poverty level associated with a nursing home will differ greatly depending on the geography of the analysis. Conclusions: These findings highlight that health inequities affect the quality and quantity of care of in nursing homes and that research conducted at larger geographical scales may overlook important mechanistic factors. This work will inform epidemiological models for disease transmission in nursing homes, accounting for the impacts of health inequities on transmission. Abating health inequities in all healthcare settings is a necessity to improve public health for the entire United States.Funding: NoneDisclosures: None

Degrowth and the city

Degrowth is both an academic debate and an activist call for a necessary socio-ecological transformation. It proposes a just and selective quantitative reduction of societal throughput to achieve ecological sustainability, social justice and individual well-being. What does such a transformation imply for cities, for place and space in general? Recently research has begun to explore this question, at the intersections of the degrowth project with geography, urban and planning studies. The present systematic review of this stream of the degrowth literature argues that contributions convincingly criticise mainstream solutions of sustainable urban development and portray an inspiring variety of local and sectoral alternatives. They also discuss the possibilities of spatial planning for degrowth. But the literature, related to a limited conceptualisation of space, lacks consideration for larger geographical scales (localism is prevalent). Also, limited attention is paid to material flows (the focus is on formal outcomes in the built environment) and there sometimes is a lack of reflection about positionality (with a tendency to apparently universalist solutions). Drawing in particular on Doreen Massey’s conceptualisation of the relationality of space and place, a conceptual framework is proposed for further research. It evidences questions neglected in the reviewed literature: how to spatialise degrowth beyond the local scale, not reducing the argument to a dualism between local = good and global = bad? And, how to transform not only the physicality of places but also the material and immaterial relations they are based on? The proposed framework, embracing a situated, relational and multiscalar understanding of space and its socio-ecological transformation, might be a first step in approaching these and other open questions in the debate on degrowth, cities and space.

Dewlap colour variation in Anolis sagrei is maintained among habitats within islands of the West Indies.

Animal signals evolve in an ecological context. Locally adapting animal sexual signals can be especially important for initiating or reinforcing reproductive isolation during the early stages of speciation. Previous studies have demonstrated that dewlap colour in Anolis lizards can be highly variable between populations in relation to both biotic and abiotic adaptive drivers at relatively large geographical scales. Here, we investigated differentiation of dewlap colouration among habitat types at a small spatial scale, within multiple islands of the West Indies, to test the hypothesis that similar local adaptive processes occur over smaller spatial scales. We explored variation in dewlap colouration in the most widespread species of anole, Anolis sagrei, across three characteristic habitats spanning the Bahamas and the Cayman Islands, namely beach scrub, primary coppice forest and mangrove forest. Using reflectance spectrometry paired with supervised machine learning, we found significant differences in spectral properties of the dewlap between habitats within small islands, sometimes over very short distances. Passive divergence in dewlap phenotype associated with isolation‐by‐distance did not seem to explain our results. On the other hand, these habitat‐specific dewlap differences varied in magnitude and direction across islands, and thus, our primary test for adaptation—parallel responses across islands—was not supported. We suggest that neutral processes or selection could be involved in several ways, including sexual selection. Our results shed new light on the scale at which signal colour polymorphism can be maintained in the presence of gene flow, and the relative role of local adaptation and other processes in driving these patterns of dewlap colour variation across islands.

Incorporation of latitude-adjusted bioclimatic variables increases accuracy in species distribution models

Latitudinal variations in species niche due to factors such as phenotypic plasticity and local adaptation pose fundamental problems for ecological niche modelling at large geographic scales. Species adaptation to varying climates across latitudes thus necessitates the latitudinal adjustment of climatic variables for incorporation into more accurate models of habitat suitability and species distribution. Previous studies have identified changes in species’ elevational distributions across latitudes, however few studies incorporate latitude-adjusted variables into suitability or distribution models. In this study, we utilized generalized additive models (GAMs) to adjust bioclimatic variables by latitude in order to remove latitudinal variation in ecological niche models. We incorporated these latitude-adjusted variables into maximum entropy (MaxEnt) models of two species of toad, Bufo sachalinensis (previously Bufo gargarizans) and Bufo stejnegeri, in northeast Asia. We additionally identified thresholds in bioclimatic and terrain variables that delineate boundaries between the two Bufo species where their ranges overlap. We found that GAM adjustment of bioclimatic variables effectively removed latitudinal variation in said variables. MaxEnt models incorporating these latitude-adjusted variables had significantly improved model fit (AUC and TSS) for both Bufo species. We identified a potential sympatric area shared by the two species and delineated a geographic boundary thresholding the probable presence of one species over the other. This study shows a clear improvement for distribution models with the inclusion of latitude-adjusted bioclimatic variables for both narrow and wide-ranging species. This has implications for future distribution modelling practices, especially for geographically widespread species, and has potential for modelling species distributions in climate change scenarios. Further, the methodology for delimiting species thresholds has future use in modelling contact zones of related species.

Genetic Variability in Balkan Paleoendemic Resurrection Plants Ramonda serbica and R. nathaliae Across Their Range and in the Zone of Sympatry.

The genus Ramonda includes three Paleoendemic and Tertiary relict species that survived in refugial habitats of the Balkan Peninsula (R. nathaliae and R. serbica) and the Iberian Peninsula (R. myconi). They are all “resurrection plants,” a rare phenomenon among flowering plants in Europe. Ramonda myconi and R. nathaliae are diploids (2n = 2x = 48), while R. serbica is a hexaploid (2n = 6x = 144). The two Balkan species occur in sympatry in only two localities in eastern Serbia, where tetraploid potential hybrids (2n = 4x = 96) were found. This observation raised questions about the existence of gene flow between the two species and, more generally, about the evolutionary processes shaping their genetic diversity. To address this question, genetic markers (AFLP) and an estimate of genome size variation were used in a much larger sample and at a larger geographic scale than previously. The combination of AFLP markers and genome size results suggested ongoing processes of interspecific and interploidy hybridization in the two sites of sympatry. The data also showed that interspecific gene flow was strictly confined to sympatry. Elsewhere, both Ramonda species were characterized by low genetic diversity within populations and high population differentiation. This is consistent with the fact that the two species are highly fragmented into small and isolated populations, likely a consequence of their postglacial history. Within sympatry, enormous variability in cytotypes was observed, exceeding most reported cases of mixed ploidy in complex plant species (from 2x to >8x). The AFLP profiles of non-canonical ploidy levels indicated a diversity of origin pathways and that backcrosses probably occur between tetraploid interspecific hybrids and parental species. The question arises whether this diversity of cytotypes corresponds to a transient situation. If not, the question arises as to the genetic and ecological mechanisms that allow this diversity to be maintained over time.

Ecological, environmental, and management data indicate apple production is driven by wild bee diversity and management practices

Climate, landscape composition, management practice, and wild bee pollination are all variables thought to play significant roles in commercial apple production. However, how these variables affect production efficiency under field-realistic conditions has not been investigated at large geographical scales. We combined intensive standardized field surveys (using netting and pan traps) with structural equation models to explore the relative impact of biotic and abiotic variables on bee diversity, apple yield and fruit quality, and their ability to represent reliable proxies of apple production. Here we show that apple yields are mainly driven by management practice, without evidence for a significantly superior contribution by managed honey bees. Total wild bee diversity, while negatively correlated with honey bee dominance, promoted apple quality by enhancing seed set number. Our study demonstrates that even across a broad geographical range there is potential to harness wild bee diversity as nature-based solution and as a substitute to an exclusive reliance on honey bees in the context of commercial apple production.

Habitat-linked genetic variation supports microgeographic adaptive divergence in an island-endemic bird species.

We investigated the potential mechanisms driving habitat‐linked genetic divergence within a bird species endemic to a single 250‐km2 island. The island scrub‐jay (Aphelocoma insularis) exhibits microgeographic divergence in bill morphology across pine–oak ecotones on Santa Cruz Island, California (USA), similar to adaptive differences described in mainland congeners over much larger geographic scales. To test whether individuals exhibit genetic differentiation related to habitat type and divergence in bill length, we genotyped over 3000 single nucleotide polymorphisms in 123 adult island scrub‐jay males from across Santa Cruz Island using restriction site‐associated DNA sequencing. Neutral landscape genomic analyses revealed that genome‐wide genetic differentiation was primarily related to geographic distance and differences in habitat composition. We also found 168 putatively adaptive loci associated with habitat type using multivariate redundancy analysis while controlling for spatial effects. Finally, two genome‐wide association analyses revealed a polygenic basis to variation in bill length with multiple loci detected in or near genes known to affect bill morphology in other birds. Our findings support the hypothesis that divergent selection at microgeographic scales can cause adaptive divergence in the presence of ongoing gene flow.

Geographical Distribution and Driving Meteorological Forces of Facial Expressions of Visitors in Urban Wetland Parks in Eastern China

Interacting with aquatic environments in blue spaces is believed to benefit mental well-being. Relevant understanding is limited to regional pilot studies using self-reported emotions on questionnaires. We assessed emotional response by rating facial expressions on a large geographical scale with the purpose of detecting a relationship to microclimates. A total of 920 facial photographs were collected from Sina Weibo from 20 wetland parks in 14 eastern cities of China during 2020. Daily average air temperature, rainfall, average relative humidity (RH), and wind velocity were also recorded from the days when photographs were posted online. We found that happy expressions were higher in wetlands of eastern cities than in northern and inland cities. Sad expressions varied statistically among wetland locations. Weather records differed between temperate and subtropical climatic zones and were highly varied among cities. Happy and sad scores were driven by the change in average air temperature. Combined multivariable regression and binomial correlation suggested that increasing air temperature would not evoke positive emotions unless higher than 11.5°C, and an air temperature range of 17.5–22.3°C will be optimum to induce the presentation of a smiling face. Air humidity generally imposed a negative effect on expressions of positive emotions. Further verification of our findings is suggested on a larger geographical scale using more powerful big-data to obtain more robust conclusions.