Infrastructure inequality is a characteristic of urbanization.

Urbanization can challenge sustainable development if it produces unequal outcomes. Infrastructure is an important urbanization dimension, providing services to support diverse urban activities. However, it can lock in unequal outcomes due to its durable nature. This paper studies inequalities in infrastructure distributions to derive insights into the structure and characteristics of unequal outcomes associated with urbanization. We analyzed infrastructure inequalities in two emerging economies in the Global South: India and South Africa. We developed and applied an inequality measure to understand the structure of inequality in infrastructure provisioning (based on census data) and infrastructure availability (based on satellite nighttime lights [NTLs] data). Consistent with differences in economic inequality, results show greater inequalities in South Africa than in India and greater urban inequalities than rural inequalities. Nevertheless, inequalities in urban infrastructure provisioning and infrastructure availability increase from finer to coarser spatial scales. NTL-based inequality measurements additionally show that inequalities are more concentrated at coarse spatial scales in India than in South Africa. Finally, results show that urban inequalities in infrastructure provisioning covary with urbanization levels conceptualized as a multidimensional phenomenon, including demographic, economic, and infrastructural dimensions. Similarly, inequalities in urban infrastructure availability increase monotonically with infrastructure development levels and urban population size. Together, these findings underscore infrastructure inequalities as a feature of urbanization and suggest that understanding urban inequalities requires applying an inequality lens to urbanization.

Host-Parasite Coevolution in Continuous Space Leads to Variation in Local Adaptation across Spatial Scales.

AbstractPrevious host-parasite coevolutionary theory has focused on understanding the determinants of local adaptation using spatially discrete models. However, these studies fall short of describing patterns of host-parasite local adaptation across spatial scales. In contrast, empirical work demonstrates that patterns of adaptation depend on the scale at which they are measured. Here, we propose a mathematical model of host-parasite coevolution in continuous space that naturally leads to a scale-dependent definition of local adaptation. In agreement with empirical research, we find that patterns of adaptation vary across spatial scales. In some cases, not only the magnitude of local adaptation but also the identity of the locally adapted species will depend on the spatial scale at which measurements are taken. Building on our results, we suggest a way to consistently measure parasite local adaptation when continuous space is the driver of cross-scale variation. We also describe a way to test whether continuous space is driving cross-scale variation. Taken together, our results provide a new perspective that can be used to understand empirical observations previously unexplained by theoretical expectations and deepens our understanding of the mechanics of host-parasite local adaptation.

Review of terrestrial temporarily conserved areas in Canada, the United States, and Mexico.

The establishment of protected areas is a cornerstone of conservation, but permanent protection could be inefficient or even impossible in some situations. We synthesized the literature on temporarily conserved areas (TCAs) across Canada, the United States, and Mexico. We used a comprehensive search string to retrieve peer-reviewed articles published from 2000 to 2021 from the Web of Science. We identified 27 relevant peer-reviewed articles that examined the potential benefits of TCAs in the study area, indicating TCA is a relatively understudied area of research in the peer-reviewed literature. The TCA studies were highly clustered; 77% of studies focused on protecting a single life stage of migratory species and 61% of studies related to temporary conservation of breeding or staging habitats for migratory birds. Ninety-three percent of studies focused on preventing human-driven threats, mainly on public lands of coastal areas, the Great Plains, and the Mississippi Valley in the central United States. Short-term and experimental studies were the dominant study types. TCAs have the potential to complement permanently protected areas and provide protection when permanent protection is difficult. Some included studies examined their conservation value, but the ecological, social, and economic outcomes of TCAs are unclear. More TCA research is needed to determine the role they could play in conservation worldwide. Embracing the concept of TCAs as conservation tool could lead to more comprehensive and consistent reporting of the outcomes of temporary area-based conservation measures. However, a global review and analysis of effectiveness of TCAs will be required if they are to play a formal role in meeting international targets for biodiversity conservation.

Revisión de áreas terrestres conservadas temporalmente en Canadá, Estados Unidos y México Resumen La creación de áreas protegidas es una piedra angular de la conservación, aunque en algunos casos la protección permanente podría ser ineficiente o incluso imposible. Condensamos la literatura sobre las áreas de conservación temporal (ACT) en Canadá, Estados Unidos y México. Usamos una cadena completa de búsqueda para obtener artículos revisados por pares publicados del 2000 al 2021 en Web of Science. Identificamos 27 artículos relevantes que analizaban el potencial de las ACT en el área de estudio, lo que indica que las ACT es un área poco estudiada en la literatura revisada por pares. Los estudios sobre ACT estaban muy agrupados: el 77% se enfocaban en la protección de un solo estadio de vida de las especies migratorias y el 61% se relacionaban con la conservación temporal de los hábitats de reproducción o de descanso de las aves migratorias. El 93% de los estudios se enfocó en la prevención de amenazas causadas por humanos, principalmente en los terrenos públicos de las áreas costeras, las Grandes Llanuras y el valle del Mississippi en el centro de los Estados Unidos. Los estudios experimentales y a corto plazo fueron el tipo de estudio dominante. Las áreas de conservación temporal tienen el potencial para complementar las áreas de protección permanente y proporcionar protección cuando es complicado proporcionarla permanentemente. Algunos de los estudios incluidos analizaron el valor para la conservación de las ACT, pero aún no están claros sus resultados ecológicos, sociales y económicos. Se necesita más investigación sobre las ACT para determinar el papel que podrían tener en la conservación mundial. Si se acepta el concepto de ACT como una herramienta de conservación, se podrían reportar los resultados de las medidas de conservación basadas en las ACT de forma más completa y consistente. Sin embargo, se requerirá una revisión y análisis global de la eficiencia de las ACT si se espera que tengan un papel formal en el cumplimiento de los objetivos internacionales de la conservación de la biodiversidad.

Measuring social equity in urban energy use and interventions using fine-scale data.

Cities seek nuanced understanding of intraurban inequality in energy use, addressing both income and race, to inform equitable investment in climate actions. However, nationwide energy consumption surveys are limited (<6,000 samples in the United States), and utility-provided data are highly aggregated. Limited prior analyses suggest disparity in energy use intensity (EUI) by income is ∼25%, while racial disparities are not quantified nor unpacked from income. This paper, using new empirical fine spatial scale data covering all 200,000 households in two US cities, along with separating temperature-sensitive EUI, reveals intraurban EUI disparities up to a factor of five greater than previously known. We find 1) annual EUI disparity ratios of 1.27 and 1.66, comparing lowest- versus highest-income block groups (i.e., 27 and 66% higher), while previous literature indicated only ∼25% difference; 2) a racial effect distinct from income, wherein non-White block groups (highest quintile non-White percentage) in the lowest-income stratum reported up to a further ∼40% higher annual EUI than less diverse block groups, providing an empirical estimate of racial disparities; 3) separating temperature-sensitive EUI unmasked larger disparities, with heating-cooling electricity EUI of lowest-income block groups up to 2.67 times (167% greater) that of highest income, and high racial disparity within lowest-income strata wherein high non-White (>75%) population block groups report EUI up to 2.56 times (156% larger) that of majority White block groups; and 4) spatial scales of data aggregation impact inequality measures. Quadrant analyses are developed to guide spatial prioritization of energy investment for carbon mitigation and equity. These methods are potentially translatable to other cities and utilities.

The Impact of Scale on Extracting Individual Mobility Patterns from Location-Based Social Media.

Understanding human movement patterns is crucial for comprehending how a city functions. It is also important for city planners and policymakers to create more efficient plans and policies for urban areas. Traditionally, human movement patterns were analyzed using origin-destination surveys, travel diaries, and other methods. Now, these patterns can be identified from various geospatial big data sources, such as mobile phone data, floating car data, and location-based social media (LBSM) data. These extensive datasets primarily identify individual or collective human movement patterns. However, the impact of spatial scale on the analysis of human movement patterns from these large geospatial data sources has not been sufficiently studied. Changes in spatial scale can significantly affect the results when calculating human movement patterns from these data. In this study, we utilized Weibo datasets for three different cities in China including Beijing, Guangzhou, and Shanghai. We aimed to identify the effect of different spatial scales on individual human movement patterns as calculated from LBSM data. For our analysis, we employed two indicators as follows: an external activity space indicator, the radius of gyration (ROG), and an internal activity space indicator, entropy. These indicators were chosen based on previous studies demonstrating their efficiency in analyzing sparse datasets like LBSM data. Additionally, we used two different ranges of spatial scales-10-100 m and 100-3000 m-to illustrate changes in individual activity space at both fine and coarse spatial scales. Our results indicate that although the ROG values show an overall increasing trend and the entropy values show an overall decreasing trend with the increase in spatial scale size, different local factors influence the ROG and entropy values at both finer and coarser scales. These findings will help to comprehend the dynamics of human movement across different scales. Such insights are invaluable for enhancing overall urban mobility and optimizing transportation systems.

Spatial scale effects on the value of ecosystem services in China's terrestrial area.

Identifying the response characteristics of ecosystem service value (ESV) to changes in spatial scales, known as spatial scale effects, is crucial in guiding the development of corresponding management strategies. This paper examines ESV in China's terrestrial area during the year 2020, revealing the spatial aggregation characteristics of ESV and the trade-off and synergistic relationships of ecosystem services at different spatial scales, ranging from 1 km × 1 km-10 km × 10 km, with a gradient of 1 km. The results indicate: 1) The distribution pattern of ESV in China's terrestrial area is "high in the southeast and low in the northwest." 2) The spatial characteristics of ESV in China's terrestrial area undergo a distinct transition at the 3 km × 3 km scale. In detail, the spatial clustering features show a trend of first rising and then falling with the increase in spatial scale, while the synergistic relationships between different ecosystem services strengthen and the trade-off relationships weaken with the increase of the spatial scale. These findings can inform the formulation of differentiated ecological protection compensation policies and enable cross-area trading of ecological values in China.

Both fine-grained and coarse-grained spatial patterns of neural activity measured by functional MRI show preferential encoding of pain in the human brain.

How pain emerges from human brain remains an unresolved question in pain neuroscience. Neuroimaging studies have suggested that all brain areas activated by painful stimuli were also activated by tactile stimuli, and vice versa. Nonetheless, pain-preferential spatial patterns of voxel-level activation in the brain have been observed when distinguishing painful and tactile brain activations using multivariate pattern analysis (MVPA). According to two hypotheses, the neural activity pattern preferentially encoding pain could exist at a global, coarse-grained, regional level, corresponding to the "pain connectome" hypothesis proposing that pain-preferential information may be encoded by the synchronized activity across multiple distant brain regions, and/or exist at a local, fine-grained, voxel level, corresponding to the "intermingled specialized/preferential neurons" hypothesis proposing that neurons responding specially or preferentially to pain could be present and intermingled with non-pain neurons within a voxel. Here, we systematically investigated the spatial scales of pain-distinguishing information in the human brain measured by fMRI using machine learning techniques, and found that pain-distinguishing information could be detected at both coarse-grained spatial scales across widely distributed brain regions and fine-grained spatial scales within many local areas. Importantly, the spatial distribution of pain-distinguishing information in the brain varies across individuals and such inter-individual variations may be related to a person's trait about pain perception, particularly the pain vigilance and awareness. These results provide new insights into the longstanding question of how pain is represented in the human brain and help the identification of characteristic neuroimaging measurements of pain.

Drivers of nematode diversity in forest soils across climatic zones.

Nematodes are the most abundant multi-cellular animals in soil, influencing key processes and functions in terrestrial ecosystems. Yet, little is known about the drivers of nematode abundance and diversity in forest soils across climatic zones. This is despite forests covering approximately 30% of the Earth's land surface, providing many crucial ecosystem services but strongly varying in climatic conditions and associated ecosystem properties across biogeographic zones. Here, we collected nematode samples from 13 forests across a latitudinal gradient. We divided this gradient into temperate, warm-temperate and tropical climatic zones and found that, across the gradient, nematode abundance and diversity were mainly influenced by soil organic carbon content. However, mean annual temperature and total soil phosphorus content in temperate zones, soil pH in warm-temperate zones, and mean annual precipitation in tropical zones were more important in driving nematode alpha-diversity, biomass and abundance. Additionally, nematode beta-diversity was higher in temperate than in warm-temperate and tropical zones. Together, our findings demonstrate that the drivers of nematode diversity in forested ecosystems are affected by the spatial scale and climatic conditions considered. This implies that high resolution studies are needed to accurately predict how soil functions respond if climate conditions move beyond the coping range of soil organisms.

Hierarchical metacommunity structure of fungal endophytes.

The ecological and evolutionary processes shaping community structure and functions of microbial symbionts are known to be scale-dependent. Nonetheless, understanding how the relative importance of these processes changes across spatial scales, and deciphering the hierarchical metacommunity structure of fungal endophytes has proven challenging. We investigated metacommunities of endophytic fungi within leaves of an invasive plant (Alternanthera philoxeroides) across wide latitudinal transects both in its native (Argentina) and introduced (China) ranges to test whether metacommunities of fungal endophytes were structured by different drivers at different spatial scales. We found Clementsian structures with seven discrete compartments (distinctive groups of fungal species with coincident distribution ranges), which coincided with the distribution of major watersheds. Metacommunity compartments were explicitly demarcated at three spatial scales, that is, the between-continent, between-compartment, and within-compartment scales. At larger spatial scales, local environmental conditions (climate, soil, and host plant traits) were replaced by other geographical factors as principal determinants of metacommunity structure of fungal endophytes and community diversity-function relationships. Our results reveal novel insights into the scale dependency of diversity and functions of fungal endophytes, which are likely similar for plant symbionts. These findings can potentially improve our understanding of the global patterns of fungal diversity.

Geographical distance, host evolutionary history and diet drive gut microbiome diversity of fish across the Yellow River.

Fish represent a large part of the taxonomic diversity of vertebrates and are of high commercial value. However, the factors influencing the gut microbiota composition of freshwater fish over large spatial scales remain unclear. Therefore, this study explored gut microbiome diversity in 24 fish species from the Yellow River, which spans over 1500 km across China. The results showed that geographical distance, host phylogeny and diet significantly influenced gut microbial community diversity, whereas sex, body length and body weight had minimal influence. Geographical distance was the primary factor shaping gut microbiota, and dissimilarity in microbial community structure increased with an increase in geographical distance, which was mainly driven by dispersal limitation. The microbial communities were more homogeneous at higher host taxonomic resolutions due to the dominant role of homogeneous selection in community convergence. Phylosymbiosis was observed across all host species, with a stronger pattern in Cypriniformes, which harbour host-specific microbial taxa. Host diet explained little variation in gut microbiome diversity, although it was significant for all diversity metrics tested. These findings collectively suggest that the geographical and host-based patterns of fish gut microbiota tend to be shaped by different ecological forces across the Yellow River. The present work provides a robust assessment of multiple factors driving fish gut microbial community assembly and offers insight into the mechanisms underlying shifts in fish gut microbiota in rivers across large spatial scales.

Support for an area-heterogeneity tradeoff for biodiversity in croplands.

Rapid expansion of the human population poses a challenge for wildlife conservation in agricultural landscapes. One proposal for addressing this challenge is to increase biodiversity in such landscapes by increasing crop diversity. However, studies report both positive and negative effects of crop diversity on biodiversity. One possible explanation, derived from the "area-heterogeneity tradeoff hypothesis," is that the effect of crop diversity on biodiversity depends on a tradeoff between increasing the number of crop types in a landscape and decreasing the amount of each single crop type. This should cause positive effects of increasing crop diversity at low to intermediate crop diversity and negative effects at intermediate to high crop diversity. We also propose two factors that could change the point at which the effect of increasing crop diversity shifts from positive to negative. First, we predicted that this shift would occur at a lower crop diversity when the surrounding landscape contains less semi-natural habitat and at a higher crop diversity when the landscape contains more semi-natural habitat. This should increase the likelihood of detecting negative effects of crop diversity when semi-natural cover is low and positive effects when it is high. Second, we predicted that the shift from a positive to negative effect would occur at a lower crop diversity when it is measured locally than when it is measured at greater distances from the site, making detection of negative crop diversity effects more likely when measurements are at local extents. We tested these predictions using data on the biodiversity of herbaceous plants, butterflies, syrphid flies, woody plants, bees, carabid beetles, spiders, and birds at 221 crop field edges in Eastern Ontario, Canada. We found support for an area-crop diversity tradeoff. Semi-natural cover and measurement extent influenced the biodiversity-crop diversity relationship, with positive effects when semi-natural cover was high and negative effects when semi-natural cover was low and when crop diversity was measured at local extents. The results suggest that policies/guidelines designed to increase crop diversity will not benefit biodiversity in the landscapes where conservation action is most urgently needed, that is, in landscapes with high agricultural use and low semi-natural cover.

Moving towards a comprehensive view of the spatial processes in seed dispersal networks: Embracing metacommunities.

The current biodiversity crisis requires efficient approaches to address the ongoing impoverishment of natural communities and the depletion of ecosystem services and functions. In this sense, identifying key species that promote the functioning of ecological processes can be strategic to guide actions aiming at the conservation and restoration of biodiversity. Node-level metrics in interaction networks can be helpful to identify those key species, as they measure the role each species plays in organizing the interactions. Moreover, ecological correlates of species structural roles may vary between local and global networks of interactions, reflecting distinct mechanisms acting at different spatial scales. By studying local seed dispersal networks and one global meta-network combining those local networks, Moulatlet et al. identified the most important traits explaining bird species centrality at varying spatial scales. They found that body mass was the main trait explaining centrality at the local scale, whereas range size was the main predictor of species centrality at the global scale. In this contribution, besides assessing local interaction networks, Moulatlet et al. adopt a biogeographical perspective to seed dispersal systems, extending our knowledge about the possible mechanisms that underlie the organization of interacting assemblages when changing the spatial scale of observation. Future efforts on this field could include an intermediate scale, comprising the level of metacommunities, shedding light on the interplay between local and spatial processes, both embedded in biogeographical realms, when determining the organization of interactions and the ecological correlates of species roles.

A atual crise da biodiversidade requer abordagens eficientes para lidar com o empobrecimento contínuo das comunidades naturais e com o esgotamento das funções e dos serviços ecossistêmicos. Neste sentido, identificar espécies-chave que promovam o funcionamento dos processos ecológicos pode ser estratégico para guiar ações que visam a conservação e a restauração da biodiversidade. Métricas em nível dos nós em redes de interação podem ser úteis para identificar tais espécies-chave, já que quantificam o papel que cada espécie desempenha em organizar as interações. Além disso, os correlatos ecológicos dos papéis estruturais das espécies podem variar entre redes de interações locais e globais, refletindo os distintos mecanismos que atuam em diferentes escalas espaciais. Ao estudar redes de dispersão de sementes locais e uma meta-rede global que combina essas redes locais, Moulatlet et al. identificaram as características mais importantes para explicar a centralidade das espécies de aves em diferentes escalas espaciais. Eles encontraram a massa corporal como principal característica que explicava a centralidade na escala local, enquanto o tamanho da distribuição foi o principal preditor da centralidade das espécies na escala global. Nesta contribuição, além de avaliar redes de interação locais, Moulatlet et al. adotaram uma perspectiva biogeográfica ao tratar os sistemas de dispersão de sementes, ampliando nosso conhecimento sobre os possíveis mecanismos subjacentes à organização das interações quando mudamos a escala espacial de observação. Esforços futuros neste campo poderiam incluir uma escala intermediária, compreendendo o nível de metacomunidades, buscando esclarecer as relações entre processos locais e processos espaciais, ambos inseridos em domínios biogeográficos, ao determinar a organização das interações e os correlatos ecológicos dos papéis estruturais das espécies.

The relative importance of abiotic and biotic environmental conditions for taxonomic, phylogenetic, and functional diversity of spiders across spatial scales.

Both abiotic and biotic conditions may be important for biodiversity. However, their relative importance may vary among different diversity dimensions as well as across spatial scales. Spiders (Araneae) offer an ecologically relevant system for evaluating variation in the relative strength abiotic and biotic biodiversity regulation. We quantified the relative importance of abiotic and biotic conditions for three diversity dimensions of spider communities quantified across two spatial scales. Spiders were surveyed along elevation gradients in northern Sweden. We focused our analysis on geomorphological and climatic conditions as well as vegetation characteristics, and quantified the relative importance of these conditions for the taxonomic, phylogenetic, and functional diversity of spider communities sampled across one intermediate (500 m) and one local (25 m) scale. There were stronger relationships among diversity dimensions at the local than the intermediate scale. There were also variation in the relative influence of abiotic and biotic conditions among diversity dimensions, but this variation was not consistent across spatial scales. Across both spatial scales, vegetation was related to all diversity dimensions whereas climate was important for phylogenetic and functional diversity. Our study does not fully support stronger abiotic regulation at coarser scales, and conversely stronger abiotic regulation at more local scales. Instead, our results indicate that community assembly is shaped by interactions between abiotic constrains in species distributions and biotic conditions, and that such interactions may be both scale and context dependent.

The scale dependency of spatial crop species diversity and its relation to temporal diversity.

Increasing crop species diversity can enhance agricultural sustainability, but the scale dependency of the processes that shape diversity and of the effects of diversity on agroecosystems is insufficiently understood. We used 30 m spatial resolution crop classification data for the conterminous United States to analyze spatial and temporal crop species diversity and their relationship. We found that the US average temporal (crop rotation) diversity is 2.1 effective number of species and that a crop's average temporal diversity is lowest for common crops. Spatial diversity monotonically increases with the size of the unit of observation, and it is most strongly associated with temporal diversity when measured for areas of 100 to 400 ha, which is the typical US farm size. The association between diversity in space and time weakens as data are aggregated over larger areas because of the increasing diversity among farms, but at intermediate aggregation levels (counties) it is possible to estimate temporal diversity and farm-scale spatial diversity from aggregated spatial crop diversity data if the effect of beta diversity is considered. For larger areas, the diversity among farms is usually much greater than the diversity within them, and this needs to be considered when analyzing large-area crop diversity data. US agriculture is dominated by a few major annual crops (maize, soybean, wheat) that are mostly grown on fields with a very low temporal diversity. To increase crop species diversity, currently minor crops would have to increase in area at the expense of these major crops.

Effects of temperature heterogeneity on freshwater turtle habitat selection at their northern range limit.

Environmental temperature is a crucial resource for ectotherms, affecting their physiology, behaviour and fitness. To maintain body temperatures within a suitable performance range, ectotherms select thermally-favourable locations, but this selection may be challenging in environments with high spatio-temporal heterogeneity. We assessed thermal habitat selection in two freshwater turtles (Emydoidea blandingii; Chrysemys picta) within a thermally heterogeneous environment at two spatial scales (selection of home ranges within the landscape, selection of locations within home ranges) and across seasons, by comparing temperatures at turtle locations vs. those available in the environment. Turtles selected warmer locations compared to those available in aquatic and terrestrial habitats only within home ranges, but did not show any temperature preferences when selecting home ranges at the larger scale. Turtles selected locations that were less thermally-variable than their surroundings, both at the home range scale and within home ranges. Thermal habitat selection was strongest during colder and more thermally-variable pre-nesting season compared to later periods. Despite differences in thermal mass between species, both species responded similarly to temperature variation. We conclude that freshwater turtles at their northern range margin select suitable microclimates within the suite of conditions that are naturally available.

Wetland water quality patterns and anthropogenic pressure associations across the continental USA.

Anthropogenic impacts on lake and stream water quality are well established but have been much less studied in wetlands. Here we use data from the 2016 National Wetland Condition Assessment to characterize water quality and its relationship to anthropogenic pressure for inland wetlands across the conterminous USA. Water samples obtained from 525 inland wetlands spanned pH from <4 to >9 and 3 to 5 orders of magnitude in ionic strength (chloride, sulfate, conductivity), nutrients (total N and P), turbidity, planktonic chlorophyll, and dissolved organic carbon (DOC). Anthropogenic pressure levels were evaluated at two spatial scales - an adjacent scale scored from field checklists, and a catchment scale indicated by percent agricultural plus urban landcover. Pressure at the two spatial scales were uncorrelated and varied considerably across regions and wetland hydrogeomorphic types. Both adjacent- and catchment-scale pressure were associated with elevated ionic-strength metrics; chloride elevation was most evident in road-salt using states, and sulfate was strongly elevated in a few sites with coal mining nearby. Nutrients were elevated in association with catchment-scale pressure but concomitant changes were not seen in planktonic chlorophyll. Acidic pH and high DOC occurred primarily in upper Great Lakes and eastern seaboard sites having low anthropogenic pressure, suggesting natural organic acid sources. Ionic strength and nutrients increased with increasing catchment-scale pressure even in Flats and closed Depression and Lacustrine sites, which indicates connectivity to rather than isolation from upland anthropogenic landuse even for wetlands lacking inflowing streams.

Non-Iterative Multiscale Estimation for Spatial Autoregressive Geographically Weighted Regression Models.

Multiscale estimation for geographically weighted regression (GWR) and the related models has attracted much attention due to their superiority. This kind of estimation method will not only improve the accuracy of the coefficient estimators but also reveal the underlying spatial scale of each explanatory variable. However, most of the existing multiscale estimation approaches are backfitting-based iterative procedures that are very time-consuming. To alleviate the computation complexity, we propose in this paper a non-iterative multiscale estimation method and its simplified scenario for spatial autoregressive geographically weighted regression (SARGWR) models, a kind of important GWR-related model that simultaneously takes into account spatial autocorrelation in the response variable and spatial heterogeneity in the regression relationship. In the proposed multiscale estimation methods, the two-stage least-squares (2SLS) based GWR and the local-linear GWR estimators of the regression coefficients with a shrunk bandwidth size are respectively taken to be the initial estimators to obtain the final multiscale estimators of the coefficients without iteration. A simulation study is conducted to assess the performance of the proposed multiscale estimation methods, and the results show that the proposed methods are much more efficient than the backfitting-based estimation procedure. In addition, the proposed methods can also yield accurate coefficient estimators and such variable-specific optimal bandwidth sizes that correctly reflect the underlying spatial scales of the explanatory variables. A real-life example is further provided to demonstrate the applicability of the proposed multiscale estimation methods.

A Substantive View of Social Enterprises as Neo-endogenous Rural Development Actors.

Social enterprises are recognised as relevant rural development actors. The specific features of social enterprises operating within rural areas (i.e. their relational, socially innovative and multi-stakeholder character and their focus on integrated development) concur with the principles of the neo-endogenous approach to rural development, which stress the potential role of third sector organisations as development actors within governance frameworks. In order to study this phenomenon, that links social enterprises and rural development, we propose a conceptual and methodological framework drawing from Polanyi's socio-economic theory, complemented with the concepts of place, spatial scale and corporate agency. Through the proposed framework, we advocate for a plural vision of the economy, socio-spatial and geopolitical sensitive concepts and overcoming methodological individualism for the study of an increasingly relevant phenomenon such as the participation of third sector organisations like social enterprises in the (neo-endogenous) development of rural areas.

Spatial scaling of gregarious host populations and nonlinearities in infectious disease transmission.

Research Highlight: Lunn, T. J., Peel, A. J., Eby, P., Brooks, R., Plowright, R. K., Kessler, M. K., & McCallum, H. (2021). Counterintuitive scaling between population abundance and local density: Implications for modelling transmission of infectious diseases in bat populations. Journal of Animal Ecology, https://doi.org/10.1111/1365-2656.13634. Quantifying the transmission of an infectious disease is often difficult and for natural animal systems it can be a major challenge. Animals move over time and space changing their degree of aggregation and rate of contact, which, in turn, affects the risk of infection and the onward spread of the pathogen. Capturing the fundamentals of these processes requires the identification of both the correct spatial scale at which the processes take place and what constitutes a meaningful host population unit. Lunn et al. collected data on the gregarious Pteropus (flying foxes) bats from roost sites in Australia and investigated whether total bat abundance at the roost level, the spatial scale commonly used to model pathogen spread in bat populations, was representative of bat measurements at the tree level, the scale at which pathogen transmission between bats most likely occurs. Their findings showed that bat population measurements at the sub-plot level were strong predictors for potential transmission at the tree scale, while roost-level measurements were less robust. This study suggests that bat abundance at roost is inadequate to capture the gregarious structure of bat populations and the fundamental processes of transmission at lower scale.

Changes in temperature alter competitive interactions and overall structure of fig wasp communities.

Organisms exist within ecological networks, connected through interactions such as parasitism, predation and mutualism which can modify their abundance and distribution within habitat patches. Differential species responses make it hard to predict the influence of climate change at the community scale. Understanding the interplay between climate and biotic interactions can improve our predictions of how ecosystems will respond to current global warming. We aim to understand how climate affects the multitrophic biotic interactions as well as the community structure using the enclosed communities of wasps associated with figs as study system. To examine the presence and strength of multitrophic species interactions, we first characterized the multitrophic community of fig wasps associated with Ficus racemosa and then applied hierarchical joint species distribution models, fitted to community monitoring data. We further evaluated the effect of climate on individual species trends as well as interspecific interactions. We found that the competitive balance shifted to favour non-pollinating galling wasps and disadvantage the dominant pollinator in suboptimal conditions. Furthermore, suboptimal conditions for galling wasps facilitated the occurrence of their specialized parasitoid, as changes cascaded across trophic levels and led to alternative community structures. Our results highlight the role of how species interactions can be modified across multiple trophic levels in a fig wasp community according to climate.