Fine-scale Variation Research Articles

Ecophenotypic variation in a cosmopolitan reef-building coral suggests reduced deep-sea reef growth under ocean change

Sensitivity of reef-building corals to environmental factors has far-reaching ecosystem implications, especially in the limited number of cold-water coral (CWC) species that form reefs in the deep sea. Understanding CWC responses to large-scale oceanographic variation in their natural habitat can elucidate their sensitivity to global anthropogenic stressors. Here, we use skeletal samples to analyse fine-scale phenotypic variation in the widespread reef-building CWC Desmophyllum pertusum (Lophelia pertusa) in relation to broad physicochemical gradients in different sites across the Atlantic Ocean and Mediterranean Sea. We find evidence, amidst local and regional differentiation, of species-wide growth responses to physicochemical factors, mainly affecting corallite length, width and their ratio (slenderness). Our results suggest that higher temperature and lower oxygen levels negatively affect skeletal linear extension and budding rate of polyps. As also hinted by the reduced corallite length and slenderness in less developed reefs, these widespread responses may lead to a general decline in CWC reef growth rates as a long-term consequence of ocean warming and deoxygenation. Given this relevance, such responses can be used to model reef growth in a changing ocean.

Some unique anatomical scaling relationships among genera in the grass subfamily Pooideae.

Members of the grass family Poaceae have adapted to a wide range of habitats and disturbance regimes globally. The cellular structure and arrangements of leaves can help explain how plants survive in different climates, but these traits are rarely measured in grasses. Most studies are focussed on individual species or distantly related species within Poaceae. While this focus can reveal broad adaptations, it is also likely to overlook subtle adaptations within more closely related groups (subfamilies, tribes). This study, therefore, investigated the scaling relationships between leaf size, vein length area (VLA) and vessel size in five genera within the subfamily Pooideae. The scaling exponent of the relationship between leaf area and VLA was -0.46 (±0.21), which is consistent with previous studies. In Poa and Elymus, however, minor vein number and leaf length were uncorrelated, whereas in Festuca these traits were positively correlated (slope = 0.82±0.8). These findings suggest there are broad-scale and fine-scale variations in leaf hydraulic traits among grasses. Future studies should consider both narrow and broad phylogenetic gradients.

A spatially explicit assessment of factors shaping attitudes toward African elephant conservation.

Conservation plans that explicitly account for the social landscape where people and wildlife co-occur can yield more effective and equitable conservation practices and outcomes. Yet, social data remain underutilized, often because social data are treated as aspatial or are analyzed with approaches that do not quantify uncertainty or address bias in self-reported data. We conducted a survey (questionnaires) of 177 households in a multiuse landscape in the Kenya-Tanzania borderlands. In a mixed-methods approach, we used Bayesian hierarchical models to quantify and map local attitudes toward African elephant (Loxodonta africana) conservation while accounting for response bias and then combined inference from attitude models with thematic analysis of open-ended responses and cointerpretation of results with local communities to gain deeper understanding of what explains attitudes of people living with wildlife. Model estimates showed that believing elephants have sociocultural value increased the probability of respondents holding positive attitudes toward elephant conservation in general (mean increase=0.31 [95% credible interval, CrI, 0.02-0.67]), but experiencing negative impacts from any wildlife species lowered the probability of respondents holding a positive attitude toward local elephant conservation (mean decrease=-0.20 [95% CrI -0.42 to 0.03]). Qualitative data revealed that safety and well-being concerns related to the perceived threats that elephants pose to human lives and livelihoods, and limited incentives to support conservation on community and private lands lowered positive local attitude probabilities and contributed to negative perceptions of human-elephant coexistence. Our spatially explicit modeling approach revealed fine-scale variation in drivers of conservation attitudes that can inform targeted conservation planning. Our results suggest that approaches focused on sustaining existing sociocultural values and relationships with wildlife, investing in well-being, and implementing species-agnostic approaches to wildlife impact mitigation could improve conservation outcomes in shared landscapes.

Estimation of surface soil moisture from Sentinel-1 synthetic aperture radar imagery using machine learning method

Surface soil moisture (SM) is a crucial variable representing the water content in soil at the topmost soil layer. Accurate data of SM are essential for various purposes, including the monitoring of drought, vegetation modeling, weather forecasting, and agriculture management. Over the past decades, microwave remote sensing has been employed to estimate SM at large scales, with the Sentinel-1 satellite mission recently offering Synthetic Aperture Radar (SAR) data and enabling to estimate SM at high spatial resolution. Machine learning (ML) techniques have further enhanced these estimations, with random forest (RF) emerging as a promising method due to its strong capabilities. However, the performance of RF in estimating SM with satellite data has not yet been thoroughly evaluated across large areas. This study presents a new RF-based model for estimating SM over Europe with SAR data from Sentinel-1, along with the climate and terrain data. The predictions from the RF model were compared against the ground measurements from the International Soil Moisture Network (ISMN), Integrated Carbon Observation System (ICOS), and official SMAP/Sentinel-1 SM products. The results demonstrated that the RF model yielded accurate predictions with a Pearson's correlation coefficient (R) of 0.847 outperforming the official SMAP/Sentinel-1 product at spatial resolutions of 1 km and 3 km, which achieved R values of 0.599 and 0.616, respectively. Additionally, the impact of vegetation cover that is represented by using multiple satellite vegetation products on the RF model was investigated. Despite a moderate correlation between backscattering coefficients and vegetation cover, no correlation was found between the RF model's errors and vegetation cover. The results suggest that the RF model and Sentinel-1 SAR data can be used to provide SM estimations at high spatial resolution, characterizing the fine-scale variations in SM, to support various applications such as precision agriculture at the small, localized scales.

Genomic variation of European beech reveals signals of local adaptation despite high levels of phenotypic plasticity

Local adaptation is key for ecotypic differentiation and species evolution. Understanding underlying genomic patterns can allow the prediction of future maladaptation and ecosystem stability. Here, we report the whole-genome resequencing of 874 individuals from 100 range-wide populations of European beech (Fagus sylvatica L.), an important forest tree species in Europe. We show that genetic variation closely mirrors geography with a clear pattern of isolation-by-distance. Genome-wide analyses for genotype-environment associations (GEAs) identify relatively few potentially adaptive variants after correcting for an overwhelming signal of statistically significant but non-causal GEAs. We characterize the single high confidence genomic region and pinpoint a candidate gene possibly involved in winter temperature adaptation via modulation of spring phenology. Surprisingly, allelic variation at this locus does not result in any apparent fitness differences in a common garden. More generally, reciprocal transplant experiments across large climate distances suggest extensive phenotypic plasticity. Nevertheless, we find indications of polygenic adaptation which may be essential in natural ecosystems. This polygenic signal exhibits broad- and fine-scale variation across the landscape, highlighting the relevance of spatial resolution. In summary, our results emphasize the importance, but also exemplify the complexity, of employing natural genetic variation for forest conservation under climate change.

Fire history in northern Sierra Nevada mixed conifer forests across a distinct gradient in productivity

BackgroundUnderstanding the role of fire in forested landscapes is fundamental to fire reintroduction efforts, yet few studies have examined how fire dynamics vary in response to interactions between local conditions, such as soil productivity, and more broadscale changes in climate. In this study, we examined historical fire frequency, seasonality, and spatial patterning in mixed conifer forests across a distinct gradient of soil productivity in the northern Sierra Nevada. We cross-dated 46 different wood samples containing 377 fire scars from 6 paired sites, located on and off of ultramafic serpentine soils. Forests on serpentine-derived soils have slower growth rates, lower biomass accumulation, and patchier vegetation than adjacent, non-serpentine sites. Due to these differences, we hypothesized that historical fire frequency and spatial extent would be reduced in mixed conifer forests growing on serpentine soils.ResultsFire scars revealed a history of frequent fire at all of our sites (median composite interval: 6–22.5 years) despite clear differences in soil productivity. Fire frequency was slightly shorter in more productive non-serpentine sites, but this difference was not consistently significant within our sample pairs. While fires were frequent, both on and off of serpentine, they were also highly asynchronous, and this was largely driven by differing climate–fire relationships. Fires in more productive sites were strongly associated with drought conditions in the year of the fire, while fires in less productive serpentine sites appeared to be more dependent on a cycle of wet and dry conditions in the years preceding the fire. Widespread fires that crossed the boundary between serpentine and non-serpentine were associated with drier than normal years.ConclusionsIn our study, fine-scale variation in historical fire regime attributes was linked to both bottom-up and top-down controls. Understanding how these factors interact to create variation in fire frequency, timing, and spatial extent can help managers more effectively define desired conditions, develop management objectives, and identify management strategies for fire reintroduction and forest restoration projects.

Characterizing the structural complexity of the Earth’s forests with spaceborne lidar

Forest structural complexity is a key element of ecosystem functioning, impacting light environments, nutrient cycling, biodiversity, and habitat quality. Addressing the need for a comprehensive global assessment of actual forest structural complexity, we derive a near-global map of 3D canopy complexity using data from the GEDI spaceborne lidar mission. These data show that tropical forests harbor most of the high complexity observations, while less than 20% of temperate forests reached median levels of tropical complexity. Structural complexity in tropical forests is more strongly related to canopy attributes from lower and middle waveform layers, whereas in temperate forests upper and middle layers are more influential. Globally, forests exhibit robust scaling relationships between complexity and canopy height, but these vary geographically and by biome. Our results offer insights into the spatial distribution of forest structural complexity and emphasize the importance of considering biome-specific and fine-scale variations for ecological research and management applications. The GEDI Waveform Structural Complexity Index data product, derived from our analyses, provides researchers and conservationists with a single, easily interpretable metric by combining various aspects of canopy structure.

Canopy temperatures strongly overestimate leaf thermal safety margins of tropical trees.

Current estimates of temperature effects on plants mostly rely on air temperature, although it can significantly deviate from leaf temperature (Tleaf). To address this, some studies have used canopy temperature (Tcan). However, Tcan fails to capture the fine-scale variation in Tleaf among leaves and species in diverse canopies. We used infrared radiometers to study Tleaf and Tcan and how they deviate from air temperature (ΔTleaf and ΔTcan) in multispecies tropical tree plantations at three sites along an elevation and temperature gradient in Rwanda. Our results showed high Tleaf (up to c. 50°C) and ΔTleaf (on average 8-10°C and up to c.20°C) of sun-exposed leaves during 10:00 h-15:00 h, being close to or exceeding photosynthetic heat tolerance thresholds. These values greatly exceeded simultaneously measured values of Tcan and ΔTcan, respectively, leading to strongly overestimated leaf thermal safety margins if basing those on Tcan data. Stomatal conductance and leaf size affected Tleaf and Tcan in line with their expected influences on leaf energy balance. Our findings highlight the importance of leaf traits for leaf thermoregulation and show that monitoring Tcan is not enough to capture the peak temperatures and heat stress experienced by individual leaves of different species in tropical forest canopies.

Multivariate Poisson cokriging: A geostatistical model for health count data.

Multivariate disease mapping is important for public health research, as it provides insights into spatial patterns of health outcomes. Geostatistical methods that are widely used for mapping spatially correlated health data encounter challenges when dealing with spatial count data. These include heterogeneity, zero-inflated distributions and unreliable estimation, and lead to difficulties when estimating spatial dependence and poor predictions. Variability in population sizes further complicates risk estimation from the counts. This study introduces multivariate Poisson cokriging for predicting and filtering out disease risk. Pairwise correlations between the target variable and multiple ancillary variables are included. By means of a simulation experiment and an application to human immunodeficiency virus incidence and sexually transmitted diseases data in Pennsylvania, we demonstrate accurate disease risk estimation that captures fine-scale variation. This method is compared with ordinary Poisson kriging in prediction and smoothing. Results of the simulation study show a reduction in the mean square prediction error when utilizing auxiliary correlated variables, with mean square prediction error values decreasing by up to 50%. This gain is further evident in the real data analysis, where Poisson cokriging yields a 74% drop in mean square prediction error relative to Poisson kriging, underscoring the value of incorporating secondary information. The findings of this work stress on the potential of Poisson cokriging in disease mapping and surveillance, offering richer risk predictions, better representation of spatial interdependencies, and identification of high-risk and low-risk areas.

Source and variation of the amazing live Sea-Monkey microbiome.

An embryonic diapause in unfavourable conditions has allowed brine shrimp to thrive in hypersaline environments and, unexpectedly, mail-order sachets and small, novelty tanks. Marketed as Sea-Monkeys®, each kit involves a 3-step process to generate adult Artemia within a matter of weeks. Whether these kits also allow for the maintenance of a host-associated microbiome is unclear. Therefore, comparing five replicate tanks under the same culture conditions, we sequenced the 16S ribosomal small subunit (SSU) gene to analyse bacterial community compositions in adults, their surrounding tank water, and their feed. Adult Sea-Monkeys® harboured a bacterial microbiome that was clearly distinguishable from the tank water and food. Furthermore, individual tanks had a notable effect on fine-scale microbiome variation. Several Sea-Monkey bacterial variants appeared absent in environmental samples and included genera (Leucobacter and Microbacterium) known to confer desiccation resistance in other hosts. Although Sea-Monkeys® taxonomy is unclear, phylogenetic inference of the cytochrome c oxidase I (COXI) gene from the host animal suggests Sea-Monkeys® belong to the Artemia franciscana 'superspecies'. Overall, Sea-Monkeys® kits appear to be a convenient and scalable mesocosm for the study of host-microbiome interactions and could serve as a useful tool for future invertebrate microbiome research, outreach, and education.

Niche breadth and divergence in sympatric cryptic coral species (Pocillopora spp.) across habitats within reefs and among algal symbionts.

While the presence of morphologically cryptic species is increasingly recognized, we still lack a useful understanding of what causes and maintains co-occurring cryptic species and its consequences for the ecology, evolution, and conservation of communities. We sampled 724 Pocillopora corals from five habitat zones (the fringing reef, back reef, and fore reef at 5, 10, and 20 m) at four sites around the island of Moorea, French Polynesia. Using validated genetic markers, we identified six sympatric species of Pocillopora, most of which cannot be reliably identified based on morphology: P. meandrina (42.9%), P. tuahiniensis (25.1%), P. verrucosa (12.2%), P. acuta (10.4%), P. grandis (7.73%), and P. cf. effusa (2.76%). For 423 colonies (58% of the genetically identified hosts), we also used psbA ncr or ITS2 markers to identify symbiont species (Symbiodiniaceae). The relative abundance of Pocillopora species differed across habitats within the reef. Sister taxa P. verrucosa and P. tuahiniensis had similar niche breadths and hosted the same specialist symbiont species (mostly Cladocopium pacificum) but the former was more common in the back reef and the latter more common deeper on the fore reef. In contrast, sister taxa P. meandrina and P. grandis had the highest niche breadths and overlaps and tended to host the same specialist symbiont species (mostly C. latusorum). Pocillopora acuta had the narrowest niche breadth and hosted the generalist, and more thermally tolerant, Durusdinium gynnii. Overall, there was a positive correlation between reef habitat niche breadth and symbiont niche breadth-Pocillopora species with a broader habitat niche also had a broader symbiont niche. Our results show how fine-scale variation within reefs plays an important role in the generation and coexistence of cryptic species. The results also have important implications for how niche differences affect community resilience, and for the success of coral restoration practices, in ways not previously appreciated.

Response of spontaneous plant communities to microhabitats in a riparian corridor in Beijing, China

With the increasing urban environmental problems, spontaneous vegetation has been gradually emphasized for high ecological value, whose distribution has been reported as strongly influenced by fine-scale environmental factors. As one of the major zones for urban spontaneous vegetation distribution, urban riparian corridors are well suited for research on the response of spontaneous plants to microhabitats. Taking the Wenyu River-North Canal in Beijing as the study site, we measured six microhabitat factors, including the level of maintenance and visitor activity, canopy density, litter thickness, and distance to water and road, to investigate their effects on spontaneous plant assemblages. The results showed that spontaneous plants respond significantly to fine-scale habitat variation, and were more responsive to human disturbance than other factors. Compared with diversity indicators, the functional trait compositions were more significantly correlated with microhabitat factors. Under lower maintenance of plants, the spontaneous communities had a higher invasion risk for plants. Thick litter can impede the occurrence of invasive species while favoring the growth of native ones. Our findings are important for furthering understanding of the spontaneous plant community establishment, and can serve as a good reference for the maintenance and management of spontaneous plants in urban riparian corridors.

The spatial distribution of heat related hospitalizations and classification of the most dangerous heat events in California at a small-scale level

Many studies have explored the impact of extreme heat on health, but few have investigated localized heat-health outcomes across a wide area. We examined fine-scale variability in vulnerable areas, considering population distribution, local weather, and landscape characteristics. Using 36 different heat event definitions, we identified the most dangerous types of heat events based on minimum, maximum, and diurnal temperatures with varying thresholds and durations. Focusing on California's diverse climate, elevation, and population distribution, we analyzed hospital admissions for various causes of admission (2004–2013). Our matching approach identified vulnerable zip codes, even with small populations, on absolute and relative scales. Bayesian Hierarchical models leveraged spatial correlation. We ranked the 36 heat event types by attributable hospital admissions per zip code and provided code, simulated data, and an interactive web app for reproducibility. Our findings showed high variation in heat-related hospitalizations in coastal cities and substantial heat burdens in the Central Valley. Diurnal heat events had the greatest impact in the Central Valley, while nighttime extreme heat events drove burdens in the southeastern desert. This spatially informed approach guides local policies, prioritizing dangerous heat events to reduce the heat-health burden. The methodology is applicable to other regions, informing early warning systems and characterizing extreme heat impacts.

Space-use strategy drives fine-scale spatial variation of chlorinated paraffins in indo-pacific humpback dolphins

Contaminant accumulation in organisms can be influenced by both biological traits and environmental conditions. However, delineating the main factors affecting contaminant burdens in organisms remains challenging. Here, we conducted an initial investigation into the impact of diet and habitat on the accumulation of short- (SCCPs) and medium-chain chlorinated paraffins (MCCPs) in Indo-Pacific humpback dolphins (2003–2020, n = 128) from the Pearl River Estuary (PRE), a highly polluted estuary in China. The detected levels of SCCPs (5897 ± 3480 ng g−1 lw) and MCCPs (13,960 ± 8285 ng g−1 lw) in blubber samples of humpback dolphin are the highest among recorded values marine mammals. Both SCCPs and MCCPs exhibited biomagnification factor values exceeding 1, suggesting their biomagnification potential within the dolphins and their diet. Quantitative diet analysis using the dolphin fatty acid signatures revealed that humpback dolphins inhabiting the western PRE consumed a larger proportion of carnivorous fish than those from the eastern PRE. However, spatial analysis showed that humpback dolphins in the western PRE contained lower SCCP/MCCP concentrations than those from the eastern PRE. Based on these findings we suggest that, compared to diet differences, spatial variations of SCCPs/MCCPs in humpback dolphins may be predominantly influenced by their space-use strategies, as the eastern PRE is closer to the pollutant discharge source and transfer routes.

Influence of habitat on fine-scale space use by brown lemmings (Lemmus trimucronatus) in the High Arctic.

Space use by small mammals should mirror their immediate needs for food and predator shelters but can also be influenced by seasonal changes in biotic and abiotic factors. Lemmings are keystone species of the tundra food web, but information on their spatial distribution in relation to habitat heterogeneity is still scant, especially at a fine scale. In this study, we used spatially explicit capture-recapture methods to determine how topography, hydrology, vegetation, and soil characteristics influence the fine-scale spatial variations in summer density of brown lemmings (Lemmus trimucronatus). Lemmings were monitored throughout the summer in wet and mesic tundra habitats and in a predator exclusion grid, which was also located in mesic tundra. We found that in wet tundra, lemming densities were higher at sites with a rugged topography dominated by hummocks, but only during snow melt. In both mesic tundra sites, lemming densities were higher in sites with poor drainage and low aspect throughout the summer. We found no clear association between lemming densities and any tested vegetation or soil variables. Overall, hydrology and topography appear to play a dominant role in small-scale space use of brown lemmings with a secondary role for predator avoidance and food plant abundance.

Pursuit and escape drive fine-scale movement variation during migration in a temperate alpine ungulate

Climate change reduces snowpack, advances snowmelt phenology, drives summer warming, alters growing season precipitation regimes, and consequently modifies vegetation phenology in mountain systems. Elevational migrants track spatial variation in seasonal plant growth by moving between ranges at different elevations during spring, so climate-driven vegetation change may disrupt historic benefits of migration. Elevational migrants can furthermore cope with short-term environmental variability by undertaking brief vertical movements to refugia when sudden adverse conditions arise. We uncover drivers of fine-scale vertical movement variation during upland migration in an endangered alpine specialist, Sierra Nevada bighorn sheep (Ovis canadensis sierrae) using a 20-year study of GPS collar data collected from 311 unique individuals. We used integrated step-selection analysis to determine factors that promote vertical movements and drive selection of destinations following vertical movements. Our results reveal that relatively high temperatures consistently drive uphill movements, while precipitation likely drives downhill movements. Furthermore, bighorn select destinations at their peak annual biomass and maximal time since snowmelt. These results indicate that although Sierra Nevada bighorn sheep seek out foraging opportunities related to landscape phenology, they compensate for short-term environmental stressors by undertaking brief up- and downslope vertical movements. Migrants may therefore be impacted by future warming and increased storm frequency or intensity, with shifts in annual migration timing, and fine-scale vertical movement responses to environmental variability.

Hibernation nest site selection but not overwinter activity is associated with microclimatic conditions in a hibernating mammal

Fine-scale variation in microclimates between habitats may impact energy consumption for the organisms that inhabit them. This may be particularly important for sedentary species or those unable to change habitats for long periods, such as hibernators. Low ambient temperatures were traditionally thought key to microclimatic selection for hibernation locations, but recent research suggests that other factors may contribute or exceed ambient temperature in importance. We aimed to characterise microclimates at hibernacula of wild hibernating hazel dormice Muscardinus avellanarius, and test how these microclimates differ to those at locations without hibernacula using a microclimatic modelling approach. Dormice hibernated in areas with warmer soil temperatures and lower variability in humidity and relative shortwave radiation. These results add to the growing body of evidence that low ambient temperatures may not be the primary driver of hibernation microclimate selection, although temperature is still likely to play an important role. We also found that ambient temperatures measured at the microclimatic level were substantially buffered compared to point samples taken at the nearest weather station (∼1.6 km away), highlighting the importance of considering microclimates in wildlife conservation in the face of future environmental change.

Fine-scale habitat suitability modelling of Northern red muntjac (Muntiacus vaginalis) in the Chitwan Annapurna Landscape, Nepal

Abstract Factors associated with the habitat suitability of northern red muntjac (Muntiacus vaginalis) especially outside protected areas in the human-dominated landscape are still lacking. Fine-scale environmental variables can influence the habitat suitability of the animals. This study aimed to explore the different eco-geographic fine-scale variables for the distribution of the northern red muntjac; and predict suitable habitats using the maximum entropy (Maxent) model in the Chitwan Annapurna landscape (CHAL). The presence points of the northern red muntjac (n = 265) were collected between 2018 to 2021 using 150 transects of various lengths in four blocks. Density-based occurrence points rarify and performance-based variable selection were applied to improve the output of the model. The model was evaluated based on the area under the curve (AUC) value of operator characteristic (ROC) and analyzed on the basis of the response curve, the relative importance of variables, Jackknife test and suitability map. Results indicated the model was statistically satisfactory (mean AUC > 0.75). The distance to the nearest cropland was the most contributed variable followed by Normalized Difference Built-up Index (NDBI), distance to developed/settlement area and distance to grassland that explained suitability of Northern red muntjac. The species distribution model predicted 6.52% highly suitable and 23.77% suitable area for northern red muntjac. Therefore, this area is important for the muntjac and provides a possible alternative habitat for other wild animals outside the protected areas. Our research suggests that human dominated landscape should be prioritized in management plans for the conservation of muntjac.

Computed tomography reconstructions of burrow networks for the Opheliid polychaete, Armandia cirrhosa

The morphology and architecture of structures formed by sediment-dwelling invertebrates, such as excavations or burrows, are often assumed to be characteristic of a given species, consistent across a range of environmental conditions, and used to categorise species contributions to ecosystem functioning. However, very few investigations use non-invasive high-resolution techniques capable of determining fine scale variations in burrow form and complexity, or consider whether or not the form of the burrow is context dependent. Here, we provide replicate high-resolution micro-focus computed tomography data for the complete burrow systems of the Opheliid polychaete, Armandia cirrhosa, across a range of salinity and habitat conditions. These data provide reference models which can be used by ecologists investigating intraspecific variation in species traits and organism-sediment interactions and, more generally, by those tasked with pattern and shape recognition of objects that are morphologically highly variable and which adjust their architecture with changing circumstance or context.

Fine-tuning coexistence: Wildlife's short-term responses to dynamic human disturbance patterns

Anthropogenic disturbance elicits adaptive responses in wildlife, generally aimed at risk-avoidance, ultimately imposing constraints on their spatial and temporal niches. Previous studies have largely focused on long-term adaptive responses to stable human pressure, but rapid adjustments in wildlife’s diel and habitat use patterns in response to fine-scale variations in human presence have so far been overlooked. In this study we estimate short-term spatio-temporal deviations in local habitat use and diel activity of medium and large mammal species in response to rapid variations in human disturbance. We employed a year-long camera-trapping within a small private reserve, and recorded spatio-temporal information on all sources of anthropogenic disturbance in the area. By controlling for the average habitat use and diel activity, we explored fine-scale spatiotemporal adjustments in seven mammal species. We found evidence of spatial and/or temporal avoidance across all species, except wild boar, with variations in magnitude and direction coherent with species traits and expected levels of human-tolerance. Most species exhibited temporal avoidance of human activities, with porcupine and roe deer eliciting particularly strong responses. Notably, foxes concurrently displayed temporal avoidance and spatial attraction, likely driven by the presence of anthropogenic trophic resources. Our study underscores the role of behavioral plasticity in enabling wildlife to adjust daily habitat use and activity patterns to varying levels of human pressure across space and time. Understanding these nuanced behavioral strategies can help to promote wildlife-human coexistence and mitigating the adverse impacts of human presence on wildlife fitness.