Multiple Spatial Scales Research Articles

Estimating scale-specific and localized spatial patterns in allele frequency.

Characterizing spatial patterns in allele frequencies is fundamental to evolutionary biology because these patterns contain evidence of underlying processes. However, the spatial scales at which gene flow, changing selection, and drift act are often unknown. Many of these processes can operate inconsistently across space, causing non-stationary patterns. We present a wavelet approach to characterize spatial pattern in allele frequency that helps solve these problems. We show how our approach can characterize spatial patterns in relatedness at multiple spatial scales, i.e. a multi-locus wavelet genetic dissimilarity. We also develop wavelet tests of spatial differentiation in allele frequency and quantitative trait loci (QTL). With simulation we illustrate these methods under different scenarios. We also apply our approach to natural populations of Arabidopsis thaliana to characterize population structure and identify locally-adapted loci across scales. We find, for example, that Arabidopsis flowering time QTL show significantly elevated genetic differentiation at 300 to 1300 km scales. Wavelet transforms of allele frequencies offer a flexible way to reveal geographic patterns and underlying evolutionary processes.

Landscape drives zoonotic malaria prevalence in non-human primates.

Zoonotic disease dynamics in wildlife hosts are rarely quantified at macroecological scales due to the lack of systematic surveys. Non-human primates (NHPs) host Plasmodium knowlesi, a zoonotic malaria of public health concern and the main barrier to malaria elimination in Southeast Asia. Understanding of regional P. knowlesi infection dynamics in wildlife is limited. Here, we systematically assemble reports of NHP P. knowlesi and investigate geographic determinants of prevalence in reservoir species. Meta-analysis of 6322 NHPs from 148 sites reveals that prevalence is heterogeneous across Southeast Asia, with low overall prevalence and high estimates for Malaysian Borneo. We find that regions exhibiting higher prevalence in NHPs overlap with human infection hotspots. In wildlife and humans, parasite transmission is linked to land conversion and fragmentation. By assembling remote sensing data and fitting statistical models to prevalence at multiple spatial scales, we identify novel relationships between P. knowlesi in NHPs and forest fragmentation. This suggests that higher prevalence may be contingent on habitat complexity, which would begin to explain observed geographic variation in parasite burden. These findings address critical gaps in understanding regional P. knowlesi epidemiology and indicate that prevalence in simian reservoirs may be a key spatial driver of human spillover risk.

Different roads, same destination: The shared future of plant ecophysiology and ecohydrology.

Terrestrial water fluxes are substantially mediated by vegetation, while the distribution, growth, health, and mortality of plants are strongly influenced by the availability of water. These interactions, playing out across multiple spatial and temporal scales, link the disciplines of plant ecophysiology and ecohydrology. Despite this connection, the disciplines have provided complementary, but largely independent, perspectives on the soil-plant-atmosphere continuum since their crystallization as modern scientific disciplines in the late 20th century. This review traces the development of the two disciplines, from their respective origins in engineering and ecology, their largely independent growth and maturation, and the eventual development of common conceptual and quantitative frameworks. This common ground has allowed explicit coupling of the disciplines to better understand plant function. Case studies both illuminate the limitations of the disciplines working in isolation, and reveal the exciting possibilities created by consilience between the disciplines. The histories of the two disciplines suggest opportunities for new advances will arise from sharing methodologies, working across multiple levels of complexity, and leveraging new observational technologies. Practically, these exchanges can be supported by creating shared scientific spaces. This review argues that consilience and collaboration are essential for robust and evidence-based predictions and policy responses under global change.

Does 2D and 3D built environment matter for the spreading of COVID-19 at early stages in Wuhan, China: A spatial and multi-scale analysis

Evidence for the impacts of urban physical attributes on the spread of COVID-19 remains weak due to few investigations into the modifiable areal unit problem (MAUP) and spatial autocorrelation, as well as the lack of fine-grained COVID-19 case data. This study presents a spatial and multi-scale approach to examine the relationships between two-dimensional (2D) and three-dimensional (3D) urban parameters and accumulative confirmed infection cases. The spatial distributions of COVID-19 infections are mapped using anonymized neighborhood-level report data with nearly 50,000 confirmed cases at the early stages of the epidemic in Wuhan, China, and the 2D and 3D built environment factors at multiple spatial scales are characterized. Next, geographical detector model is used to examine the MAUP in the spread of COVID-19 and effects of urban parameters, and spatial regression models are then used to address spatial autocorrelation in the results at the identified appropriate spatial scales. Results reveal that the influences of most urban parameters are sensitive to the scale and areal unit used, and 3D urban parameters, such as building height, have a greater influence than 2D parameters. The estimates from both spatial and non-spatial models suggest the presence of spatial dependence and unobserved autocorrelated factors, and the overestimation of the effects of most urban parameters.

Occupancy dynamics of free ranging American mink (Neogale vison) in Greece.

Identifying the environmental factors that determine the occurrence of invasive species is essential in defining and implementing effective control campaigns. Here, we applied multi-season occupancy models to analyze American mink (Neogale vison) track data collected using 121 floating rafts, as a function of factors occurring at multiple spatial scales. Our overall aim was to identify those factors that determine the use, colonization or abandonment of rafts by free ranging individuals found in western Macedonia, Greece. We found that increasing values of shrubs and rock cover at the micro-habitat scale were positively associated with the species' probability of raft use, as was the density of medium-sized rivers at the landscape scale. Colonization was found to increase with increasing amounts of shrub and reed cover; however, both variables were not informative. Conversely, the distance from the nearest fur farm was highly informative in predicting raft abandonment by the species. Effective control actions may require removal by trapping along rocky or densely vegetated riverbanks or lake shores located in the vicinity of the established fur farms in the area. Habitat management, although possible, may be difficult to implement due to the ability of the species to adapt. Finally, fur farms should maximize security and establish an early warning and rapid eradication system in case of future escapes.

Multi-Scale methodology of breakup and atomization for liquid jets in crossflow

Liquid jets in crossflow represent a highly complex phenomenon, characterized by intricate interactions across multiple temporal and spatial scales spanning orders of magnitude. To better understand the atomization mechanisms and characteristics of liquid jets in crossflow, a hybrid multi-scale methodology, integrating volume of fluid and discrete phase models with an enhanced coupling algorithm based on Large Eddy Simulation, has been developed and implemented as a multiphase solver in OpenFOAM. This methodology enables the comprehensive reproduction of the atomization process, including primary breakup and secondary atomization, obviating the requirement for complex tunable atomization models. For further reducing computational costs, a parallel acceleration technology is proposed by integrating the adaptive mesh refinement with dynamic load balancing into the solver. The multi-scale methodology is validated against experimental data regarding the trajectory of the liquid jet, as well as the distribution of droplet sizes and velocities. The validated methodology is then used to predict the behavior of Jet-A in crossflow. Simulation results demonstrate that, under the multi-mode breakup regime, large droplets are formed through the deformation of ligaments, small droplets are stripped from threads, and even smaller droplets are generated after secondary breakup. In contrast, in the shear breakup mode, large droplets are directly squeezed from the sides of the liquid column, while smaller droplets are stripped from ligaments and threads. Additionally, compared to the multi-mode breakup, droplet diameters are smaller in the downstream field for the shear breakup mode.

Global warming significantly increases the risk of Pierce’s disease epidemics in European vineyards

Pierce’s disease (PD) is a vector-borne disease caused by the bacteria Xylella fastidiosa, which affects grapevines in the Americas. Currently, vineyards in continental Europe, the world’s largest producer of quality wine, have not yet been affected by PD. However, climate change may alter this situation. Here we incorporate the latest regional climate change projections into a climate-driven epidemiological model to assess the risk of PD epidemics in Europe for different levels of global warming. We found a significant increase in risk above +2∘C\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$+\\,2\\,^{\\circ }\\hbox {C}$$\\end{document} in the main wine-producing regions of France, Italy and Portugal, in addition to a critical tipping point above +3∘C\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$+\\,3\\,^{\\circ }\\hbox {C}$$\\end{document} for the possible spread of PD beyond the Mediterranean. The model identifies decreasing risk trends in Spain, as well as contrasting patterns across the continent with different velocities of risk change and epidemic growth rates. Although there is some uncertainty in model projections over time, spatial patterns of risk are consistent across different climate models. Our study provides a comprehensive analysis of the future of PD at multiple spatial scales (country, Protected Designation of Origin and vineyard), revealing where, why and when PD could become a new threat to the European wine industry.

Deciphering Photoinduced Catalytic Reaction Mechanisms in Natural and Artificial Photosynthetic Systems on Multiple Temporal and Spatial Scales Using X-ray Probes.

Utilization of renewable energies for catalytically generating value-added chemicals is highly desirable in this era of rising energy demands and climate change impacts. Artificial photosynthetic systems or photocatalysts utilize light to convert abundant CO2, H2O, and O2 to fuels, such as carbohydrates and hydrogen, thus converting light energy to storable chemical resources. The emergence of intense X-ray pulses from synchrotrons, ultrafast X-ray pulses from X-ray free electron lasers, and table-top laser-driven sources over the past decades opens new frontiers in deciphering photoinduced catalytic reaction mechanisms on the multiple temporal and spatial scales. Operando X-ray spectroscopic methods offer a new set of electronic transitions in probing the oxidation states, coordinating geometry, and spin states of the metal catalytic center and photosensitizers with unprecedented energy and time resolution. Operando X-ray scattering methods enable previously elusive reaction steps to be characterized on different length scales and time scales. The methodological progress and their application examples collected in this review will offer a glimpse into the accomplishments and current state in deciphering reaction mechanisms for both natural and synthetic systems. Looking forward, there are still many challenges and opportunities at the frontier of catalytic research that will require further advancement of the characterization techniques.

Hierarchically embedded scales of movement shape the social networks of vampire bats.

Social structure can emerge from hierarchically embedded scales of movement, where movement at one scale is constrained within a larger scale (e.g. among branches, trees, forests). In most studies of animal social networks, some scales of movement are not observed, and the relative importance of the observed scales of movement is unclear. Here, we asked: how does individual variation in movement, at multiple nested spatial scales, influence each individual's social connectedness? Using existing data from common vampire bats (Desmodus rotundus), we created an agent-based model of how three nested scales of movement-among roosts, clusters and grooming partners-each influence a bat's grooming network centrality. In each of 10 simulations, virtual bats lacking social and spatial preferences moved at each scale at empirically derived rates that were either fixed or individually variable and either independent or correlated across scales. We found that numbers of partners groomed per bat were driven more by within-roost movements than by roost switching, highlighting that co-roosting networks do not fully capture bat social structure. Simulations revealed how individual variation in movement at nested spatial scales can cause false discovery and misidentification of preferred social relationships. Our model provides several insights into how nonsocial factors shape social networks.

Multiple dimensions of phyllostomid bat biodiversity across ecosystems of the Orinoco Llanos

AbstractUnderstanding the impacts of habitat conversion on species assemblages across multiple biodiversity dimensions (taxonomic, functional, and phylogenetic) and spatial scales is pivotal for implementing effective conservation strategies. Here, we surveyed phyllostomid bats using mist nets in riparian and unflooded forests, flooded savannahs, and conventional rice fields to investigate how changes in habitat quality affect multifaceted diversity from two Colombian farming systems in the Orinoco Llanos: traditional farmlands with high‐intensity agriculture (mainly rice production) and Civil Society Nature Reserves with greater ecosystem protection. We used a unified framework based on Hill numbers for quantifying bat taxonomic, functional, and phylogenetic diversity and modeled the relationship of these diversity facets with landscape variables (habitat cover and patch density) across three spatial scales (0.5, 1.5, 3 km) using Bayesian generalized linear mixed‐effect models. Our results indicate that increasing human activity toward rice monocultures representative of traditional farmlands negatively affected all diversity facets. In contrast, forested habitats associated mainly with riparian forests within private reserves contained higher taxonomic, functional, and phylogenetic diversity than savannahs and rice fields. However, the differences between riparian forests and rice crops were significant only for phylogenetic diversity, indicating loss of evolutionary history after habitat conversion. At the landscape scale, forest cover was a significant predictor for functional (0.5‐ and 3‐km scale) and phylogenetic diversity (0.5 km), and bats responded negatively at the 3‐km scale to rice patch density from a functional diversity perspective. Increasing habitat quality through preserving forest cover and patches should minimize the harmful effects of habitat conversion on multidimensional bat biodiversity. Furthermore, the conservation of riparian forests and the creation of more wildlife‐friendly farming, as practiced in the reserves, should be prioritized to ensure high levels of bat taxonomic, functional, and phylogenetic diversity across Orinoco countryside landscapes.

Partitioning genetic structure of a subterranean rodent at multiple spatial scales: accounting for isolation by barriers, distance, and environment

ContextUnderstanding genetic structure at multiple spatial scales and identifying drivers of genetic isolation are important for developing comprehensive conservation plans including for grassland conservation efforts. However, few studies account for multiple genetic isolation processes nor partition genetic variance among these processes.ObjectivesWe assess key processes that can create spatial genetic patterns including isolation by barrier (IBB), isolation by distance (IBD), and isolation by environment (IBE) for a widespread pocket gopher species (Geomys bursarius) and a spatially restricted subspecies (Geomys bursarius illinoensis). We further partition genetic variation to each isolating effect and identify genetic variation that was shared between processes.MethodsWe used seven microsatellites to determine spatial genetic clustering and identify environmental factors impacting genetic similarities. Then, we used redundancy analysis to partition variance explained by IBB, IBD, and IBE.ResultsMajor rivers including the Mississippi River acted as barriers and explained the most genetic variation across the species. In contrast, IBD explained the most genetic variation for G. b. illinoensis. Gophers had genetic associations to soil sand percent and soil color, but IBE uniquely explained a small amount of genetic structure for G. bursarius, with additional variation shared with other isolating processes.ConclusionsGopher genetic structure resulted from barriers, distance, and environmental factors at the species range as well as for a subspecies’ region, but the relative amount of genetic variance assigned to unique isolating processes differed between scales. Delineation of conservation units should consider major rivers as natural boundaries, and finer-scale management should identify and protect areas close to source populations with similar soil friability. Our study exemplifies how analyzing gene flow at rangewide and regional scales can aid managers in developing localized strategies that fit within broader conservation units.

Ecosystem services potential is declining across European capital metropolitan areas

Ecosystem services (ES) are essential to sustainable development at multiple spatial scales. Monitoring ES potential (ESP) at the metropolitan level is imperative to sustainable cities. We developed a procedure for long-term monitoring of metropolitan ESP dynamics, utilizing open-source land use land cover (LULC) data and the expert matrix method. We compared the ESP results of 38 European Capital Metropolitan Areas (ECMA) regarding biodiversity integrity, drinking water provision, flood protection, air quality, water purification, and recreation & tourism. Our results show significant declines in ESP across ECMA due to LULC alteration between 2006, 2012, and 2018. We found that ECMA in post-socialist European countries like Poland (Warszawa) have experienced high rates of land use transformation with a remarkable impact on ESP. Surprisingly, we found that Fennoscandinan ECMA, like Helsinki, Stockholm, and Oslo which lead the cumulative ESP ranking, faced the ESP reduction of the highest impact in recent years. The correlation analysis of ESP dynamics to urban expansion and population growth rates suggests that inattentive urbanization processes impact ESP more than population growth. We unveil the implications of our results to the EU and global level agendas like the European Nature Conservation Law and the Sustainable Development Goals.

Three-dimensional dipole orientation mapping with high temporal-spatial resolution using polarization modulation

Fluorescence polarization microscopy is widely used in biology for molecular orientation properties. However, due to the limited temporal resolution of single-molecule orientation localization microscopy and the limited orientation dimension of polarization modulation techniques, achieving simultaneous high temporal-spatial resolution mapping of the three-dimensional (3D) orientation of fluorescent dipoles remains an outstanding problem. Here, we present a super-resolution 3D orientation mapping (3DOM) microscope that resolves 3D orientation by extracting phase information of the six polarization modulation components in reciprocal space. 3DOM achieves an azimuthal precision of 2° and a polar precision of 3° with spatial resolution of up to 128 nm in the experiments. We validate that 3DOM not only reveals the heterogeneity of the milk fat globule membrane, but also elucidates the 3D structure of biological filaments, including the 3D spatial conformation of λ-DNA and the structural disorder of actin filaments. Furthermore, 3DOM images the dipole dynamics of microtubules labeled with green fluorescent protein in live U2OS cells, reporting dynamic 3D orientation variations. Given its easy integration into existing wide-field microscopes, we expect the 3DOM microscope to provide a multi-view versatile strategy for investigating molecular structure and dynamics in biological macromolecules across multiple spatial and temporal scales.

Understanding the impact of modifiable areal unit problem on urban vitality and its built environment factors

ABSTRACT Urban vitality is an essential reference for formulating urban planning and urban development policies, while the Modifiable Areal Unit Problem (MAUP) is a crucial issue that affects the accurate assessment of urban vitality and the understanding of its driving factors. Currently, MAUP in urban vitality studies has not received sufficient attention, and there are limited investigations on whether MAUP significantly affects the spatial autocorrelation of urban vitality. Moreover, existing studies have mainly focused on the impact of individual factors on urban vitality, with minor consideration of the interactions between factors and their effects on urban vitality at different spatial scales. This study takes the Pearl River Delta Core (PRDC) region as the research area. It used the Optimal Parameters-based Geographic Detector (OPGD) model and spatial autocorrelation to analyze the impact of the MAUP on urban vitality and its Built Environment (BE) factors. The results indicated that (1) the five types of BE driving factors, including work, living, rest, traffic, and Points of Interest (POI) diversity, were spatially sensitive and exhibited scale threshold effects. (2) The zoning schemes demonstrated the ability to alter the explanatory power (q-value) of driving factors and their trends. The spatial granularity and aggregation level of the grid-based zoning scheme, NPP-VIIRS nighttime light zoning scheme, and land surface temperature zoning scheme exhibited a logarithmic relationship, where spatial autocorrelation levels decreased with increasing aggregation level. (3) Compared to single-factor effects, the interactive effects of BE factors exhibited a higher q-value for urban vitality. Additionally, the q-values for factor interactions were more stable in multiple spatial scales than those q-values for individual factors. This study provides decision-making references for urban planners and policymakers to accurately assess urban vitality and find balanced, improved paths to enhance it.

A network approach for multiscale catchment classification using traits

Abstract. The classification of river catchments into groups with similar biophysical characteristics is useful to understand and predict their hydrological behavior. The increasing availability of remote sensing and other large-scale geospatial datasets has enabled the use of advanced data-driven approaches to classify catchments using traits such as topography, geology, climate, land cover, land use, and human influence. Unsupervised clustering algorithms based on the Euclidean distance are commonly used for trait-based classification but are not suitable for highly dimensional data. In this study we present a new network-based method for multi-scale catchment classification, which can be applied to large datasets and used to determine the traits associated with different catchment groups. In this framework, two networks are analyzed in parallel: the first being where the nodes are traits and the second being where the nodes are catchments. In both cases, edges represent pairwise similarity, and a network cluster detection algorithm is used for the classification. The trait network is used to investigate redundancy in the trait data and to condense this information into a small number of interpretable categories. The catchments network is used to classify the catchments into clusters and to identify representative catchments for the different groups using the degree centrality metric. We apply this method to classify 9067 river catchments across the contiguous United States at both regional and continental scales using 274 non-categorical traits. At the continental scale, we identify 25 interpretable trait categories and 34 catchment clusters of sizes greater than 50. We find that catchments with similar trait categories are typically located in the same region, with different spatial patterns emerging among clusters dominated by natural and anthropogenic traits. We also find that the catchment clusters exhibit distinct hydrological behavior based on an analysis of streamflow indices. This network approach provides several advantages over traditional means of classification, including better separation of clusters, the use of alternate similarity metrics that are more suitable for highly dimensional data, and reducing redundancy in the trait information. The paired catchment–trait networks enable analysis of hydrological behavior using the dominant trait categories for each catchment cluster. The approach can be used at multiple spatial scales since the network topologies adjust automatically to reflect the trait patterns at the scale of investigation. Finally, the representative catchments identified as hub nodes in the network can be used to guide transferable observational and modeling strategies. The method is broadly applicable beyond hydrology for classification of other complex systems that utilize different types of trait datasets.

Simulation of national-scale groundwater dynamics in geologically complex aquifer systems: an example from Great Britain

ABSTRACT The national-scale British Groundwater Model (BGWM) is implemented to simulate groundwater dynamics and budgets in Great Britain. Notwithstanding the challenges of integrating a very large amount of data, finding a trade-off between computational efficiency and realism, performing automatic calibration, and addressing multiple sources of structural and parameter uncertainty, a quantitative–qualitive evaluation approach showed that the BGWM provides a reasonably accurate digital representation of groundwater systems and processes at a national scale. In this work, the model was applied to understand the variability of budget components across multiple spatial and temporal scales. Comparisons showed regional differences linked to lithological and climatic factors, which in turn can be associated with more or less groundwater resilience to extreme climatic events. There is confidence that the current and future versions of the BGWM can become valuable tools for effective water resources management and adaptation strategies under future climatic and population changes.

Forest carbon storage and sink estimates under different management scenarios in China from 2020 to 2100

Forests play a crucial role in mitigating climate change through carbon storage and sequestration, though environmental change drivers and management scenarios are likely to influence these contributions across multiple spatial and temporal scales. In this study, we employed three tree growth models—the Richard, Hossfeld, and Korf models—that account for the biological characteristics of trees, alongside national forest inventory (NFI) datasets from 1994 to 2018, to evaluate the carbon sink potential of existing forests and afforested regions in China from 2020 to 2100, assuming multiple afforestation and forest management scenarios. Our results indicate that the Richard, Hossfeld, and Korf models provided a good fit for 26 types of vegetation biomass in both natural and planted Chinese forests. These models estimate that in 2020, carbon stocks in existing Chinese forests are 7.62 ± 0.05 Pg C, equivalent to an average of 44.32 ± 0.32 Mg C/ ha. Our predictions then indicate this total forest carbon stock is expected to increase to 15.51 ± 0.99 Pg C (or 72.26 ± 4.6 Mg C/ha) in 2060, and further to 19.59 ± 1.36 Pg C (or 91.31 ± 6.33 Mg C/ha) in 2100. We also show that plantation management measures, namely tree species replacement, would increase carbon sinks to 0.09 Pg C/ year (contributing 38.9 %) in 2030 and 0.06 Pg C/ year (contributing 32.4 %) in 2060. Afforestation using tree species with strong carbon sink capacity in existing plantations would further significantly increase carbon sinks from 0.02 Pg C/year (contributing 10.3 %) in 2030 to 0.06 Pg C/year (contributing 28.2 %) in 2060. Our results quantify the role plantation management plays in providing a strong increase in forest carbon sequestration at national scales, pointing to afforestation with native tree species with high carbon sequestration as key in achieving China's 2060 carbon neutrality target.

Sensitivity of insectivorous bat foraging guilds to urbanization and implications for sustainable development

Substantial urban expansion is expected in global biodiversity hotspots over the next decade, especially in Asia. One such hotspot is Sulawesi, Indonesia, which hosts a diverse array of wild mammals, including bats. While urbanization may threaten some bats, species are not uniformly sensitive to urbanization. Many bat species’ sensitivity to urbanization is associated with their foraging strategies (or foraging guild), but information from Asia, generally, is severely lacking. Here we address this knowledge gap regarding urban sensitivity among insectivorous, echolocating bats within the context of urban informal settlements around the city of Makassar, South Sulawesi. Globally and in Makassar, informal settlements often exist on the fringe of cities, forming an urban-undeveloped land interface. Consequently, they may present opportunities to support conservation for some bats, given a growing focus on nature-based sustainable development solutions to improve the lives of informal settlement residents. We examined how, among informal settlements across Makassar, relative activity of bat sonotypes (in lieu of taxonomic species) from different foraging guilds was related to environmental factors associated with urban expansion. We found bat activity was influenced by processes interacting across multiple spatial scales ranging from the landscape- (e.g., spatial location relative to dense development in the urban core) to local-level (e.g., particular environmental features within 500 m). Broadly, we found some foraging guilds had lower overall relative activity, as well lower activity within the urban core compared to the peri-urban zone, indicating differential sensitivity to urbanization among Makassar’s bats that matches findings elsewhere. However, intensity of both urban and peri-urban informal settlement habitat use by particular bats was driven by a combination of landscape- and local-scale features. At the local scale, tree cover and inland water area frequently influenced sonotype activity in settlements, including urban core habitat use by urban-sensitive bats. Our work demonstrates that, especially if coordinated across broader spatial scales, local nature-based upgrades in informal settlements incorporating diverse green and blue spaces have the potential to enhance suitability of urban zones for both bats and for people.

Activation and depression of neural and hemodynamic responses induced by the intracortical microstimulation and visual stimulation in the mouse visual cortex.

Objective. Intracortical microstimulation (ICMS) can be an effective method for restoring sensory perception in contemporary brain-machine interfaces. However, the mechanisms underlying better control of neuronal responses remain poorly understood, as well as the relationship between neuronal activity and other concomitant phenomena occurring around the stimulation site.Approach. Different microstimulation frequencies were investigatedin vivoon Thy1-GCaMP6s mice using widefield and two-photon imaging to evaluate the evoked excitatory neural responses across multiple spatial scales as well as the induced hemodynamic responses. Specifically, we quantified stimulation-induced neuronal activation and depression in the mouse visual cortex and measured hemodynamic oxyhemoglobin and deoxyhemoglobin signals using mesoscopic-scale widefield imaging.Main results. Our calcium imaging findings revealed a preference for lower-frequency stimulation in driving stronger neuronal activation. A depressive response following the neural activation preferred a slightly higher frequency stimulation compared to the activation. Hemodynamic signals exhibited a comparable spatial spread to neural calcium signals. Oxyhemoglobin concentration around the stimulation site remained elevated during the post-activation (depression) period. Somatic and neuropil calcium responses measured by two-photon microscopy showed similar dependence on stimulation parameters, although the magnitudes measured in soma was greater than in neuropil. Furthermore, higher-frequency stimulation induced a more pronounced activation in soma compared to neuropil, while depression was predominantly induced in soma irrespective of stimulation frequencies.Significance. These results suggest that the mechanism underlying depression differs from activation, requiring ample oxygen supply, and affecting neurons. Our findings provide a novel understanding of evoked excitatory neuronal activity induced by ICMS and offer insights into neuro-devices that utilize both activation and depression phenomena to achieve desired neural responses.

Scale-dependent effects of herbivory on moss communities in Arctic wetlands: A 25-year experiment.

Arctic ecosystems are undergoing rapid changes, including increasing disturbance by herbivore populations, which can affect plant species coexistence and community assemblages. Although the significance of mosses in Arctic wetlands is well recognized, the long-term influence of medium-sized herbivores on the composition of moss communities has received limited attention. We used data from a long-term (25 years) Greater Snow Goose (Anser caerulescens atlanticus) exclusion experiment in Arctic tundra wetlands to assess changes in the composition of moss communities at multiple spatial scales (cell, 4 cm2; quadrat, 100 cm2; exclosure, 16 m2). We investigated how snow goose grazing and grubbing can alter the composition of the moss community by measuring changes in alpha and beta diversity, as well as in the strength of plant interspecific interactions between moss species. Our results indicate that goose foraging significantly increased species diversity (richness, evenness, and inverse Simpson index) of moss communities at the cell and quadrat scales but not the exclosure scale. Goose foraging reduced the dissimilarity (beta diversity) of moss communities at all three scales, mainly due to decreased species turnover. Furthermore, goose foraging increased positive interaction between moss species pairs. These findings emphasize the critical role of geese in promoting moss species coexistence and increasing homogeneity in Arctic wetlands. This study illustrates how top-down regulation by herbivores can alter plant communities in Arctic wetlands and highlights the importance of considering herbivores when examining the response of Arctic plant biodiversity to future climate change.