Fine Spatial Scales Research Articles

Emergence of a brainstem somatosensory tonotopic map for substrate vibration.

Perceiving substrate-borne vibrations is a fundamental component of tactile perception. How location (somatotopy) and frequency tuning (tonotopy) of vibrations are integratively processed is poorly understood. Here we addressed this question using in vivo electrophysiology and two-photon calcium imaging along the dorsal column-medial lemniscal pathway. We found that both frequency and location are organized into structured maps in the dorsal column nuclei (DCN). Both maps are intimately related at the fine spatial scale, with parallel map gradients that are consistent across the depth of the DCN and preserved along the ascending pathway. The tonotopic map only partially reflects the distribution of end organs in the skin and deep tissue; instead, the emergence of the fine-scale tonotopy is due to the selective dendritic sampling from axonal afferents, already at the first synaptic relay. We conclude that DCN neural circuits are key to the emergence of these two fine-scale topographical organizations in early somatosensory pathways.

Regional variation in growth and survival responses to atmospheric nitrogen and sulfur deposition for 140 tree species across the United States

Atmospheric deposition of nitrogen (N) and sulfur (S) alter tree demographic processes via changes in nutrient pools, soil acidification, and biotic interactions. Previous work established tree growth and survival response to atmospheric N and S deposition in the conterminous United States (CONUS) data by species; however, it was not possible to evaluate regional variation in response using that approach. In this study, we develop species- and region-specific relationships for growth and survival responses to N and S deposition for roughly 140 species within spatially demarcated regions of the U.S. We calculated responses to N and S deposition separately for 11 United States Forest Service (USFS) Divisions resulting in a total of 241 and 268 species × Division combinations for growth and survival, respectively. We then assigned these relationships into broad categories of vulnerability and used ordinal logistic regressions to explore the covariates associated with vulnerability in growth and survival to N and S deposition. As with earlier studies, we found growth and survival responses to air pollution differed by species; but new to this study, we found 45%−70% of species responses also varied spatially across regions. The regional variation in species responses was not simply related to atmospheric N and S deposition, but was also associated with regional effects from precipitation, soil pH, mycorrhizal association, and deciduousness. A large amount of the variance remained unexplained (total variation explained ranged from 6.8%−13.8%), suggesting that these or additional factors may operate at finer spatial scales. Taken together, our results demonstrate that regional variation in tree species' response has significant implications for setting critical load targets, as critical loads can now be tailored for specific species at management-relevant scales.

Using Commercial Satellite Imagery to Reconstruct 3 m and Daily Spring Snow Water Equivalent

AbstractSnow water equivalent (SWE) distribution at fine spatial scales (≤10 m) is difficult to estimate due to modeling and observational constraints. However, the distribution of SWE throughout the spring snowmelt season is often correlated to the timing of snow disappearance. Here, we show that snow cover maps generated from PlanetScope's constellation of Dove Satellites can resolve the 3 m date of snow disappearance across seven alpine domains in California and Colorado. Across a 5‐year period (2019–2023), the average uncertainty in the date of snow disappearance, or the period of time between the last date of observed snow cover and the first date of observed snow absence, was 3 days. Using a simple shortwave‐based snowmelt model calibrated at nearby snow pillows, the PlanetScope date of snow disappearance could be used to reconstruct spring SWE. Relative to lidar SWE estimates, the SWE reconstruction had a spatial coefficient of correlation of 0.75, and SWE spatial variability that was biased by 9%, on average. SWE reconstruction biases were then improved to within 0.04 m, on average, by calibrating snowmelt rates to track the spring temporal evolution of fractional snow cover observed by PlanetScope, including fractional snow cover over the full modeling domain, and across domain subsections where snowmelt rates may differ. This study demonstrates the utility of fine‐scale and high‐frequency optical observations of snow cover, and the simple and annually repeatable connections between snow cover and spring snow water resources in regions with seasonal snowpack.

A New SDM-Based Approach for Assessing Climate Change Effects on Plant–Pollinator Networks

Current methods for studying the effects of climate change on plants and pollinators can be grouped into two main categories. The first category involves using species distribution models (SDMs) to generate habitat suitability maps, followed by applying climate change scenarios to predict the future distribution of plants and pollinators separately. The second category involves constructing interaction matrices between plants and pollinators and then either randomly removing species or selectively removing generalist or specialist species, as a way to estimate how climate change might affect the plant–pollinator network. The primary limitation of the first approach is that it examines plant and pollinator distributions separately, without considering their interactions within the context of a pollination network. The main weakness of the second approach is that it does not accurately predict climate change impacts, as it arbitrarily selects species to remove without knowing which species will truly shift, decline, or increase in distribution due to climate change. Therefore, a new approach is needed to bridge the gap between these two methods while avoiding their specific limitations. In this context, we introduced an innovative approach that first requires the creation of binary climate suitability maps for plants and pollinators, based on SDMs, for both the current and future periods. This step aligns with the first category of methods mentioned earlier. To assess the effects of climate change within a network framework, we consider species co-overlapping in a geographic matrix. For this purpose, we developed a Python program that overlays the binary distribution maps of plants and pollinators, generating interaction matrices. These matrices represent potential plant–pollinator interactions, with a ‘0’ indicating no overlap and a ‘1’ where both species coincide in the same cell. As a result, for each cell within the study area, we can construct interaction matrices for both the present and future periods. This means that for each cell, we can analyze at least two pollination networks based on species co-overlap. By comparing the topology of these matrices over time, we can infer how climate change might affect plant–pollinator interactions at a fine spatial scale. We applied our methodology to Chile as a case study, generating climate suitability maps for 187 plant species and 171 pollinator species, resulting in 2906 pollination networks. We then evaluated how climate change could affect the network topology across Chile on a cell-by-cell basis. Our findings indicated that the primary effect of climate change on pollination networks is likely to manifest more significantly through network extinctions, rather than major changes in network topology.

Macro- and micro-geographic genetic variation in early fitness traits in populations of maritime pine (Pinus pinaster Ait.).

Assessing adaptive genetic variation and its spatial distribution is crucial to conserve forest genetic resources and manage species' adaptive potential. Macro-environmental gradients commonly exert divergent selective pressures that enhance adaptive genetic divergence among populations. Steep micro-environmental variation might also result in adaptive divergence at finer spatial scales, even under high gene flow, but it is unclear how often this is the case. Here, we assess genetic variation in early fitness traits among distant and nearby maritime pine (Pinus pinaster Ait.) populations, to investigate climatic factors associated with trait divergence, and to examine trait integration during seedling establishment. Open pollinated seeds were collected from seven population pairs across the European species distribution, with paired populations spatially close (between <1 km up to 21 km) but environmentally divergent. Seeds were sown in semi-natural conditions at three environmentally contrasting sites, where we monitored seedling emergence, growth and survival. At large spatial scales, we found significant genetic divergence among populations in all studied traits, with certain traits exhibiting association with temperature and precipitation gradients. Significant trait divergence was also detected between pairs of nearby populations. Besides, we found consistent trait correlations across experimental sites, notably heavier seeds and earlier seedling emergence were both associated with higher seedling survival and fitness over two years in all experimental conditions. We identified mean annual temperature and precipitation seasonality as potential drivers of P. pinaster population divergence in the studied early-life traits. Populations genetically diverge also at local spatial scales, potentially suggesting that divergent natural selection can override gene flow along local-scale ecological gradients. These results suggest the species exhibits substantial adaptive potential that has allowed it to survive and evolve under contrasting environmental conditions.

An individual‐based model trained on multiple data sources estimates population connectivity and facilitates aggregation of harvest management units

Abstract Management boundaries are often delimited by political and social factors, whereas animal movements are affected by ecological and geophysical constraints. Thus, understanding connectivity among distinct management units is of considerable importance, particularly for harvested species, where quotas set in ignorance of connectivity may fail to meet management goals. We constructed an individual‐based model (IBM) to better understand wild turkey movements at large scales, benefiting from multiple data sources that are often available for harvested species. We built an IBM from spring seasonal movements of wild turkey, using data from ringed, radio‐, and GPS‐marked turkeys captured in Maine, USA. Our IBM accommodated variation in individual turkey response to landscape connectivity metrics and identified emergent migratory connectivity dynamics among harvest management regions. We calculated a low degree of connectivity among wildlife management districts (WMD) which, in combination with the substantial number of boundary crossings observed, indicated a more diffuse distribution of turkeys among WMDs. Synthesis and applications: Estimates of turkeys moving between districts provided a clear delineation of where immigration was strongest, identifying which WMDs should be managed as singular population units. This approach has widespread utility for any species or system where harvest management decisions are made at finer spatial scales than the movement dynamics affecting population processes.

Near-surface particulate backscattering observations with bio-optical Lagrangian drifters

Abstract Particulate matter concentration is an essential ocean variable (EOV) useful for understanding biogeochemical processes, improving ocean productivity estimates, and constraining coupled physical and biogeochemical numerical models. While direct observations of this parameter are difficult to obtain, the optical backscattering coefficient of marine particles (bbp) can be used as a reliable proxy. However, most in-situ multi-spectral bbp measurements are ship-borne or obtained from moored systems, thus with a limited spatial and temporal coverage. Utilizing Surface Velocity Programme (SVP) drifting buoys with self-contained backscatter sensors designed for extended deployment periods offers a promising solution for collecting data in challenging marine environments. In this study, we presented for the first time the integration of a commercially available, high-frequency and multispectral optical backscatter sensor into an SVP drifter, the so-called BO-SVP drifter designed to collect bbp measurements near the ocean surface. bbp measurements obtained by the BO-SVP drifter were reliable over a wide range of environmental conditions, showing a good agreement with independent datasets (relative bias &lt; 10%; relative standard deviation &lt; 36%). The BO-SVP drifter captures the satellite sub- and pixel scale variability by combining the Lagrangian approach and a high frequency sampling. This configuration enables the acquisition of measurements across numerous pixels in a single day, enhancing validation activities for ongoing and future satellite products and the quantification of associated uncertainties. The measurements acquired by these platforms can offer valuable insights into particle distribution at fine spatial scales, daily variability, and its relationship with water masses type and ocean dynamics.

Assessment of Fine-Scale Urban Heat Health Risk and Its Potential Driving Factors Based on Local Climate Zones in Shenzhen, China

Cities are facing increased heat-related health risks (HHRs) due to the combined effects of global warming and rapid urbanization. However, few studies have focused on HHR assessment based on fine-scale information. Moreover, most studies only analyze spatial HHR patterns and do not explore the potential driving factors. In this study, we estimated the potential HHRs based on the “hazard–exposure–vulnerability” framework by using multisource data, including the modified thermal–humidity index (MTHI), population density, and land cover. Then, the variations in the HHRs among different local climate zones (LCZs) at the fine spatial scale were analyzed in detail. Finally, we compared the different contributions of the LCZs and types of land cover to the HHRs and their three components by using multiple linear regression models. The results indicate that the spatial pattern of the HHRs was different from those of the individual components, and high-hazard regions do not mean high HHRs. There were huge variations in the HHRs among the different LCZs. The built-up LCZs typically had much higher HHRs than the natural ones, with compact LCZs facing the most severe risk. LCZ 6 (open low-rise buildings) had a relatively low HHR and should be paid more attention in future urban planning. Compared to the LCZs, the land covers better explained the variations in the HHR. In contrast, the LCZs better predicted the land surface temperatures. However, both the LCZs and land covers made only slight contributions to the heat exposure and vulnerability. Furthermore, the manmade buildings and impervious surface areas contributed much more to the HHR than the natural land covers. Therefore, the arrangement of the warming LCZs and land cover types is worthy of further investigation from the perspective of HHR mitigation.

Modelling the spatial variability and uncertainty for under-vaccination and zero-dose children in fragile settings

Universal access to childhood vaccination is important to child health and sustainable development. Here we identify, at a fine spatial scale, under-immunized children and zero-dose children. Using Chad, as an example, the most recent nationally representative household survey that included recommended vaccine antigens was assembled. Age-disaggregated population (12–23 months) and vaccination coverage were modelled at a fine spatial resolution scale (1km × 1 km) using a Bayesian geostatistical framework adjusting for a set of parsimonious covariates. There was a variation at fine spatial scale in the population 12–23 months a national mean of 18.6% (CrI 15.8%–22.6%) with the highest proportion in the South-East district of Laremanaye 20.0% (14.8–25.0). Modelled coverage at birth was 49.0% (31.2%–75.3%) for BCG, 44.8% (27.1–74.3) for DTP1, 24.7% (12.5–46.3) for DTP3 and 47.0% (30.6–71.0) for measles (MCV1). Combining coverage estimates with the modelled population at a fine spatial scale yielded 312,723 (Lower estimate 156055–409266) zero-dose children based on DTP1. Improving routine immunization will require investment in the health system as part of enhancing primary health care. The uncertainties in our estimates highlight areas that require further investigation and higher quality data to gain a better understanding of vaccination coverage.

A Pleistocene Biogeography in Miniature: The Small‐Scale Evolutionary History of Podarcis lusitanicus (Squamata, Lacertidae)

ABSTRACTAimRecent literature is unveiling more complex responses of biodiversity to Pleistocenic climatic oscillations than those derived from initial models based solely on southern glacial macrorefugia. Here, we zoom in to delve into the genetic diversity and population structure of Podarcis lusitanicus, a lizard species native to the north‐western Iberian Peninsula.LocationNorth‐western Iberian Peninsula.TaxonPodarcis lusitanicus.MethodsUtilising a comprehensive multilocus approach, we explored the species' phylogeography and demographic history at a very fine spatial scale and timeframe. Concurrently, we evaluated both current and historical habitat suitability for the species, linking it to the observed demographic trends. We examined DNA sequences from two mitochondrial (cytb and ND4) and three nuclear genes (ACM4, MC1R and PDC) in 230 specimens collected from 21 populations spanning most of the species' distribution range.ResultsOur findings corroborate cytonuclear discordances in Podarcis, with nuclear genes failing to identify the mitochondrial clades in P. lusitanicus. Despite its separation from other Podarcis species approximately 4 million years ago, its diversification occurred much more recently, around 0.4 million years ago, resulting in three monophyletic lineages that are geographically coherent. This pattern suggests that some lineages of P. lusitanicus might have gone extinct after the split from the common ancestor. Pleistocene climatic oscillations profoundly influenced the demographic history of the species. During warmer periods, such as the Last Interglacial, populations expanded and came into secondary contact, whereas during the Last Glacial Maximum, populations contracted and became isolated in multiple micro‐refugia. The subsequent Mid‐Holocene warming facilitated population recovery, range expansion and lineage admixture.Main ConclusionsThis study underscores the intricate interplay between isolation and dispersal at a microscale, driven by Pleistocene climatic fluctuations, which have profoundly shaped the genetic structure and diversity of Iberian terrestrial biodiversity and may remain overlooked by biogeographic studies at coarser scales.

Modeling Urban Temperature Using Measurements from Mobile and Stationary Monitoring Stations

Heat waves are occurring more frequently worldwide as global warming continues, and urban heat islands can threaten conventional life in cities. Measuring, analyzing, and simulating weather data at fine spatial and temporal scales are essential to prevent and reduce the damage caused by extreme heat waves. In urban environments, handling complex micrometeorological situations using current meteorological stations and global simulation models (e.g., weather research forecasting models) is challenging. In this study, the thermal environments of urban areas were measured using a mobile meteorological measurement platform. Both mobile and stationary datasets were incorporated into the meteorological modeling process to simulate the spatial and temporal distribution of temperature. Additionally, various mobile observation implementation scenarios for temperature modeling were examined. We compared simulation combinations with the temperature field generated from the total dataset to obtain a better sampling campaign and properly incorporate mobile data scenarios. When collecting mobile data, it is important to consider spatial features to improve the efficiency of sampling programs. This can substantially reduce the cost of mobile data collection, together with the sensor error bound.

Towards the understanding of genetic and morphological variations of a highly abundant seaweed-associated marine invertebrate

Unraveling the patterns of genetic structure and demographic history of marine species, as well as the factors that shape their genetic variations, is fundamental for informing conservation strategies for species and their environments. In this work, we investigate the current population structure and historical demographic patterns of the conspicuous seaweed-associated amphipod Hyale niger at a fine spatial scale in the subtropical SW Atlantic coast, in Brazil, by using both genome-wide and mitochondrial DNA markers. We also investigate how geographic distance, current oceanographic conditions, and variations in a key morphological trait contribute to the genetic variability of the amphipod. We observed an evident population genetic structure, even at a fine spatial scale, although genetic differentiation was lower than our expectations for a benthic direct brooder. Demographic history inferences were consistent across populations and showed two major demographic expansions on interglacial periods during the late Pleiostocene, before and after the last glacial maximum. We also demonstrated that isolation-by-environment (IBE) was the main driver of genetic differentiation, although we could not separate it from the effects of isolation-by-distance (IBD). Among environmental factors, nutrient concentrations in seawater were most relevant for explaining genetic structure. In addition, our data suggest that morphological variation in gnathopod 2 structure of males were not genetic-related and were probably plastic as a response to variations in macroalgae frond size. Our study reinforces the importance of using multiple molecular markers and analytical approaches to unveil patterns and processes generating genetic variation in natural populations.

Phylogenetic structure and turnover between lowland and montane subtropical forests indicate differential community assembly processes, affected by successional stage and spatial gradients

Secondary forests represent an increasing proportion of global forest cover and offer a range of ecosystem services that are integral to environmental policy targets. Highly disturbed landscapes with temporal records of forest plant community composition offer key insights into the processes that shape plant communities as forests undergo secondary succession. We investigated patterns of plant community phylogenetic structure and phylogenetic beta diversity. Mean pairwise distance (MPD) and Mean Nearest Taxon Distance (MNTD) metrics were determined between co-occurring species within plant communities, in addition to phylogenetic beta diversity metrics relative to null models of random phylogenetic assembly. MPD and MNTD were compared between elevational and successional classes and modelled as products of intercommunity distance (metres) and forest community age (years). Phylogenetic nonmetric multidimensional scaling explored phylogenetic community structure between lowland and montane forest type in Hong Kong. We found that plant communities in secondary forests in Hong Kong exhibited patterns of increased basal phylogenetic clustering with increasing community elevation, while phylogenetic turnover was influenced by spatial and successional factors in lowland and montane forest. Our findings indicate differential community assembly in lowland compared to montane forest type in Hong Kong, as well as evidence for barriers to plant dispersal in secondary forest communities due to patterns of spatial phylogenetic clustering. Plant communities in montane forests were found to be phylogenetically distinct from lowland forest plant communities. Patterns of spatial phylogenetic clustering may suggest significant dispersal or post-dispersal processes causing the clustering of related species at fine spatial scales, while phylogenetic turnover with increasing successional age may indicate compositional changes during the process of passive forest regeneration. Collectively, these results emphasize the need to investigate active pathways for rewilding dispersal limited late successional forest tree species in Hong Kong.

Intercomparison of fast airborne ozone instruments to measure eddy covariance fluxes: spatial variability in deposition at the ocean surface and evidence for cloud processing

Abstract. The air–sea exchange of ozone (O3) is controlled by chemistry involving halogens, dissolved organic carbon, and sulfur in the sea surface microlayer. Calculations also indicate faster ozone photolysis at aqueous surfaces, but the role of clouds as an ozone sink is currently not well established. Fast-response ozone sensors offer opportunities to measure eddy covariance (EC) ozone fluxes in the marine boundary layer. However, intercomparisons of fast airborne O3 sensors and EC O3 fluxes measured on aircraft have not been conducted before. In April 2022, the Technological Innovation Into Iodine and GV Environmental Research (TI3GER) field campaign deployed three fast ozone sensors (gas chemiluminescence and a combination of UV absorption with coumarin chemiluminescence detection, CID) together with a fast water vapor sensor and anemometer to study iodine chemistry in the troposphere and stratosphere over Colorado and over the Pacific Ocean near Hawaii and Alaska. Here, we present an instrument comparison between the NCAR Fast O3 instrument (FO3, gas-phase CID) and two KIT Fast AIRborne Ozone instruments (FAIRO, UV absorption and coumarin CID). The sensors have comparable precision &lt; 0.4 % Hz−0.5 (0.15 ppbv Hz−0.5), and ozone volume mixing ratios (VMRs) generally agreed within 2 % over a wide range of environmental conditions: 10 &lt; O3 &lt; 1000 ppbv, below detection &lt; NOx &lt; 7 ppbv, and 2 ppmv &lt; H2O &lt; 4 % VMR. Both instrument designs are demonstrated to be suitable for EC flux measurements and were able to detect O3 fluxes with exchange velocities (defined as positive for upward) as slow as −0.010 ± 0.004 cm s−1, which is in the lower range of previously reported measurements. Additionally, we present two case studies. In one, the direction of ozone and water vapor fluxes was reversed (vO3 = +0.134 ± 0.005 cm s−1), suggesting that overhead evaporating clouds could be a strong ozone sink. Further work is needed to better understand the role of clouds as a possibly widespread sink of ozone in the remote marine boundary layer. In the second case study, vO3 values are negative (varying by a factor of 6–10 from −0.036 ± 0.006 to −0.003 ± 0.004 cm s−1), while the water vapor fluxes are consistently positive due to evaporation from the ocean surface and spatially homogeneous. This case study demonstrates that the processes governing ozone and water vapor fluxes can become decoupled and illustrates the need to elucidate possible drivers (physical, chemical, or biological) of the variability in ozone exchange velocities on fine spatial scales (∼ 20 km) over remote oceans.

Spatial-temporal patterns of foliar and bulk soil 15N isotopic signatures across a heterogeneous landscape: Linkages to soil N status, nitrate leaching, and N2O fluxes

The natural abundance of plant and bulk soil 15N isotopic signatures provides valuable insights into the magnitude of nitrogen cycling and loss processes within terrestrial ecosystems. However, 15N isotopic signatures are highly variable in space due to natural and anthropogenic factors affecting N cycling processes and losses. To date, most studies on foliar and bulk soil 15N isotopic signatures have focused on N-limited forest ecosystems at relatively large spatial scales, while similar studies in N-enriched ecosystems at finer spatial scales are lacking. To address this gap and evaluate links between soil 15N isotopic signatures and ecosystem N cycling and loss processes (plant N uptake, N leaching, and gaseous loss), this study quantified foliar and bulk soil 15N isotopic signatures, soil physicochemical parameters, gaseous (N2O), and hydrological (NO3) N losses at 80 sites distributed across a heterogeneous landscape (∼5.8 km2). To account for the spatial-temporal heterogeneity, the measurements were performed in four campaigns (March, June, September 2022, and March 2023) at sites that considered different land uses, soil types, and topography. Results indicated that foliar and bulk soil 15N isotopic signatures were significantly (P < 0.05) more enriched in arable and grassland ecosystems than forests, suggesting a more open N cycle with significant N cycling and losses due to higher N inputs from fertilizers. Similar to soil inorganic N, N2O fluxes, and NO3 leaching rates, landscape-scale foliar and soil 15N isotopic signatures varied widely spatially, particularly at grassland and arable land (−3 to 9.0‰), with bivariate and multivariate analyses also showing significant relationships between landscape-scale soil 15N isotopic signatures and the aforementioned parameters (r2: 0.29 to 0.82). Based on these relationships, our findings suggested that foliar and bulk 15N isotopic signatures may capture fine-scale areas with persistently high and low environmental N losses (N2O fluxes and NO3 leaching) within a heterogeneous landscape.

Investigating the Biotic and Abiotic Drivers of Body Size Disparity in Communities of Non‐Volant Terrestrial Mammals

ABSTRACTAimThe species that compose local communities possess unique sets of functional and ecological traits that can be used as indicators of biotic and abiotic variation across space and time. Body size is a particularly relevant trait because species with different body sizes typically have different life history strategies and occupy distinct niches. Here we used the body sizes of non‐volant (i.e., non‐flying) terrestrial mammals to quantify and compare the body size disparity of mammal communities across the globe.LocationGlobal.Time PeriodPresent.Major Taxa StudiedNon‐volant terrestrial mammals.MethodsWe used IUCN range maps of 3982 terrestrial mammals to identify 1876 communities. We then combined diet data with data on climate, elevation and anthropogenic pressures to evaluate these variables' relative importance on the observed body size dispersion of these communities and its deviation from a null model.ResultsDispersion for these communities is significantly greater than expected in 54% of communities and significantly less than expected in 30% of communities. The number of very large species, continent, range sizes, diet disparity and annual temperature collectively explain &gt; 50% of the variation in observed dispersion, whereas continent, the number of very large species, and precipitation collectively explain &gt; 30% of the deviation from the null model.Main ConclusionsClimate and elevation have minimal predictive power, suggesting that biotic factors may be more important for explaining community body size distributions. However, continent is consistently a strong predictor of dispersion, likely due to it capturing the combined effects of climate, size‐selective human‐induced extinctions and more. Overall, our results are consistent with several plausible explanations, including, but not limited to, competitive exclusion, unequal distribution of resources, within‐community environmental heterogeneity, habitat filtering and ecosystem engineering. Further work focusing on other confounding variables, at finer spatial scales and/or within more causal frameworks is required to better understand the driver(s) of these patterns.

Salinity tolerance of the invasive blue crab Callinectes sapidus: From global to local, a new tool for implementing management strategy

The latest report from the Intergovernmental Platform on Biodiversity and Ecosystem Services (IPBES) raises concerns about the global proliferation of non-native species (NIS) driven by increasing temperatures. In 2023, the invasive blue crab Callinectes sapidus experienced a significant range expansion in the French Mediterranean lagoons, now present in over 20 lagoons and numerous estuaries with different invasion gradients. It has been established that this species is eurytherm (tolerates a wide range of temperatures; 0–40 °C), rendering temperature a non-limiting factor for its proliferation. On the other hand, salinity is a critical factor to consider, as C. sapidus requires brackish water for copulation and saline water for egg maturation. In this study, we present the salinity tolerance of C. sapidus using the metabolic performance to define the tolerance of the species to a large range of salinities (13 levels from 0 to 65 psu). Results showed that C. sapidus tolerates a large range of salinities with a minimum critical threshold (CTmin) at 0 psu, an optimum at 18.5 psu, and a CTmax at 62.4 psu. Using the performance curve equation, we applied the curve to real salinity data measured each month in 2023 in 20 lagoons invaded. Using this approach, we were able to map, on a fine spatial scale, the distribution of suitable habitats for C. sapidus in the year 2023. Additionally, we have developed a tool to prioritize the lagoons based on their suitability, thereby providing a decision-making framework for management measures in each lagoon. It emerged that 50 % of lagoons were priority areas, 10 % were intermediate and 40 % required monitoring. On the basis of this approach, we can respond to European regulations to help decision-makers implement action plans and/or early detection programs for invasive species management.

Fine spatial scale assessment of structure and configuration of vegetation cover for northern bobwhites in grazed pastures

BackgroundMonitoring forage in livestock operations is critical to sustainable rangeland management of soil and ecological processes that provide both livestock and wildlife habitat. Traditional ground-based sampling methods have been widely used and provide valuable information; however, they are time-consuming, labor-intensive, and limited in their ability to capture larger extents of the spatial and temporal dynamics of rangeland ecosystems. Drones provide a solution to collect data to larger extents than field-based methods and with higher-resolution than traditional remote sensing platforms. Our objectives were to (1) assess the accuracy of vegetation cover height in grasses using drones, (2) quantify the spatial distribution of vegetation cover height in grazed and non-grazed pastures during the dormant (fall–winter) and growing seasons (spring–summer), and (3) evaluate the spatial distribution of vegetation cover height as a proxy for northern bobwhite (Colinus virginianus) habitat in South Texas. We achieved this by very fine scale drone-derived imagery and using class level landscape metrics to assess vegetation cover height configuration.ResultsEstimated heights from drone imagery had a significant relationship with the field height measurements in September (r2 = 0.83; growing season) and February (r2 = 0.77; dormant season). Growing season pasture maintained residual landscape habitat configuration adequate for bobwhites throughout the fall and winter of 2022–2023 following grazing. Dormant season pasture had an increase in bare ground cover, and a shift from many large patches of tall herbaceous cover (40–120 cm) to few large patches of low herbaceous cover (5–30 cm) (p < 0.05).ConclusionsDrones provided high-resolution imagery that allowed us to assess the spatial and temporal changes of vertical herbaceous vegetation structure in a semi-arid rangeland subject to grazing. This study shows how drone imagery can be beneficial for wildlife conservation and management by providing insights into changes in fine-scale vegetation spatial and temporal heterogeneity from livestock grazing.

A new airborne system for simultaneous high-resolution ocean vector current and wind mapping: first demonstration of the SeaSTAR mission concept in the macrotidal Iroise Sea

Abstract. Coastal seas, shelf seas and marginal ice zones are dominated by small-scale ocean surface dynamic processes that play a vital role in the transport and exchange of climate-relevant properties such as carbon, heat, water and nutrients between land, ocean, ice and atmosphere. Mounting evidence indicates that ocean scales below 10 km have far-ranging impacts on air–sea interactions, lateral ocean dispersion, vertical stratification, ocean carbon cycling and marine productivity – governing exchanges across key interfaces of the Earth system, the global ocean, and atmosphere circulation and climate. Yet, these processes remain poorly observed at the fine spatial and temporal scales necessary to resolve them. The Ocean Surface Current Airborne Radar (OSCAR) is a new airborne instrument with the capacity to inform these questions by mapping vectorial fields of total ocean surface currents and winds at high resolution over a wide swath. Developed for the European Space Agency (ESA), OSCAR is the airborne demonstrator of the satellite mission concept SeaSTAR, which aims to map total surface current and ocean wind vectors with unprecedented accuracy, spatial resolution and temporal revisit across all coastal seas, shelf seas and marginal ice zones. Like SeaSTAR, OSCAR is an active microwave synthetic aperture radar along-track interferometer (SAR-ATI) with optimal three-azimuth sensing enabled by unique highly squinted beams. In May 2022, OSCAR was flown over the Iroise Sea, France, in its first scientific campaign as part of the ESA-funded SEASTARex project. The campaign successfully demonstrated the capabilities of OSCAR to produce high-resolution 2D images of total surface current vectors and near-surface ocean vector winds, simultaneously, in a highly dynamic, macrotidal coastal environment. OSCAR current and wind vectors show excellent agreement with ground-based X-band-radar-derived surface currents, numerical model outputs and NovaSAR-1 satellite SAR imagery, with root mean square differences from the X-band radar better than 0.2 m s−1 for currents at 200 m resolution. These results are the first demonstration of simultaneous retrieval of total current and wind vectors from a high-squint three-look SAR-ATI instrument and the first geophysical validation of the OSCAR and SeaSTAR observing principle. OSCAR presents a remarkable new ocean observing capability to support the study of small-scale ocean dynamics and air–sea interactions across the Earth's coastal, shelf and polar seas.

Downscaling Vapor Pressure Deficit across Complex Forested Terrain

Abstract The forest microclimate shapes many aspects of forest functioning, including plant regeneration and wildfire occurrence. In complex landscapes with varying terrain, the forest microclimate varies at fine spatial scales (10–100 m2). However, accurately mapping this variation remains challenging. Vapor pressure deficit (VPD) is an important microclimatic variable for plant growth and fire activity, yet few studies have specifically focused on downscaling VPD. The aim of this study was to examine the drivers of in-forest VPD in temperate eucalypt forests and develop a model to predict in-forest VPD. We use microclimate data from 37 in-forest weather stations, installed across an aridity gradient in southeastern Australia. We used linear mixed models within an information theoretic approach to develop a predictive model for daily maximum in-forest VPD using open VPD and topographic variables. The highest-ranked model included fundamental topographic drivers of vegetation structure and microclimate in forested landscapes: aspect, elevation, and slope, in addition to open VPD. The model had high accuracy when tested against independent data. We used this model to map fine-scale (30 m2, daily) maximum in-forest VPD across a topographically complex case study landscape. Predicted in-forest VPD showed considerable spatial and temporal variations not captured by coarse-scale open VPD. This represents a significant advancement in our ability to model microclimatic conditions in temperate eucalypt forests and has the potential to advance our understanding of how ecosystem processes vary at fine spatial scales.