Biology subjects

Lenoir, J.

Publications and source records attributed to Lenoir, J..

13 recordsLinked to original sources

bioRxiv2025

From smartphones to satellites: Uniting crowdsourced biodiversity monitoring and Earth observation to fill the gaps in global plant trait mapping

Plant functional traits are fundamental to ecosystem dynamics and Earth system processes, but their global characterization is limited by the availability of field surveys and trait measurements. Recent expansions in biodiversity data aggregation, including large collections of vegetation surveys, citizen science observations, and trait measurements, offer new opportunities to overcome these constraints. Here we demonstrate that combining these diverse data sources with high-resolution Earth observation data enables accurate modeling of key plant traits at up to 1 km resolution. Our approach achieves high predictive power, reaching correlations up to 0.63 (15 of 31 traits exceeding 0.50) and improved spatial transferability, effectively bridging gaps in under-sampled regions. By capturing a broad range of traits with high spatial coverage, these maps can enhance our understanding of plant community properties and ecosystem functioning globally, and can serve as useful tools in modeling global biogeochemical processes and informing worldwide conservation efforts. Ultimately, our framework highlights the power and necessity of crowdsourced biodiversity data in high-resolution plant trait modeling. We anticipate that advancements in biodiversity data collection and remote sensing capabilities will further refine global trait mapping, fostering a dynamic trait-based understanding of the biosphere.

ecology↗

bioRxiv2024

Mountain roads across the globe significantly alter local soil microclimates

Mountain roads have repeatedly shown to host significantly different plant species communities compared to the adjacent natural vegetation. Besides the effect of propagule pressure, altered disturbance regime and soil processes, one of the reasons given for the strong influence of mountain roads on species distributions is a significantly altered microclimate in the roadside compared to the adjacent vegetation, a direct consequence of the altered disturbance regime. However, the microclimatic differences between roadside and natural vegetation have rarely been quantified, particularly lacking global analyses, hampering a better understanding of their importance for mountain biodiversity. In this study, we analysed in-situ measured soil temperatures along mountain roads in seven mountain regions across the globe, in order to assess the impact of mountain roads on a range of bioclimatic variables across the elevational gradient. Our results undeniably show the importance of roadsides as unique microhabitats, even in heterogeneous mountain environments. In most regions, roadside soils had warmer maxima (3.95 {+/-} 2.35{degrees}C warmer) and colder minima (0.85 {+/-} 1.11 {degrees}C colder) than the soil in the adjacent vegetation, with higher frost risks in winter. Therefore, we recommend future research to incorporate the notion that the local microclimates created by mountain roads could play a critical role in species redistributions in space and time.

ecology↗

bioRxiv2024

Early signs of plant community responses to climate warming along mountain roads in Switzerland

O_LIGlobal warming is pushing species to shift their ranges towards higher latitudes and elevations, causing a reassembly of plant communities potentially accompanied by community thermophilization (i.e., an increasing number or cover of thermophilic species, sometimes at the expense of mesic or cold-adapted species). Given the large variation typically observed in the magnitude and direction of range shifts, quantifying community thermophilization might provide a sensitive method to detect range shifts within short time periods and across limited spatial extents. Assessing changes in plant community composition as a whole might integrate early signs of range shifts across co-occurring species while accounting for changes in both occurrence and abundance. C_LIO_LIHere, we combine an assessment of (i) species-level range shifts, (ii) changes in species richness and (iii) changes in community-inferred temperatures along three mountain roads in Switzerland to ask whether plant communities have responded to warming climate over a 10 year period, and whether community thermophilization is an appropriate metric for early detection of these changes. C_LIO_LIWe found a community thermophilization signal of +0.13{degrees}C over the 10-year study period based on presence-absence data only. Despite significant upward shifts of species upper range limits in the lower part of the studied elevational gradient and a decrease in species richness at high elevations, significant thermophilization was not detectable if community- inferred temperatures were weighted by species covers. Low cover values of species that were gained or lost over the study period and their similar species-specific temperatures to resident species explained the discrepancy between the thermophilization detected in either cover-weighted or unweighted models. C_LIO_LISynthesis. Our work shows that plant species are shifting to higher elevations along roadsides in the western Swiss Alps and that this translates into a detectable warming signal of plant communities within 10 years. However, the species-level range shifts and the community-level warming effect are mostly based on low cover values of gained/lost species, preventing the detection of community thermophilization signals when incorporating cover changes. We therefore recommend using unweighted approaches for early detection of community-level responses to changing climate, ideally set into context by also assessing species-level range shifts. C_LI

ecology↗

bioRxiv2024

Land-use impacts on plant functional diversity throughout Europe

AimGlobal biodiversity loss resulting from anthropogenic land-use activities is a pressing concern, requiring precise assessments of impacts at large spatial extents. Existing models mainly focus on species richness and abundance, lacking insights into ecological mechanisms and species roles in ecosystem functioning. To bridge this gap, we conducted an extensive analysis of the impact of human land use on vascular plant functional diversity, across diverse land-use classes and bioregions in Europe, comparing it to traditional metrics. Location: Europe Time period: 1992-2019 Major taxa studied: Vascular plants MethodsIntegrating extensive databases of vegetation plots with spatial data on land use and land cover, we paired plots from areas actively used and modified by humans with plots from natural habitats under similar environmental conditions. Using species occurrences and traits, in each plot we computed three complementary functional diversity metrics (functional richness, evenness, and divergence), species richness and abundance. We assessed the impact of land use by comparing the metrics in the paired plots. ResultsOur findings revealed that, compared to natural habitats, anthropogenic land use exhibits lower functional richness and divergence but higher functional evenness across most land-use classes and bioregions. The response of functional richness was more marked than the other two metrics and especially pronounced in croplands and urban areas and in northern bioregions. Functional richness exhibited a pattern that did not fully overlap with the trend in species richness, providing useful complementary information. Main conclusionsWe provide a large-scale precise assessment of anthropogenic land-use impacts on functional diversity across Europe. Our findings indicate that: (i) human disturbance significantly alters plant functional diversity compared to natural habitats; (ii) this alteration goes in the direction of functional homogenization; (i) functional diversity metrics complement traditional metrics by offering deeper insights into the ecological mechanisms in response to anthropogenic land use.

ecology↗

bioRxiv2023

Deep learning to extract the meteorological by-catch of wildlife cameras

Microclimate - proximal climatic variation at scales of meters and minutes - can exacerbate or mitigate the impacts of climate change on biodiversity. However, most microclimate studies are temperature-centric, and do not consider meteorological factors such as sunshine, hail and snow. Meanwhile, remote cameras have become a primary tool to monitor wild plants and animals, even at micro-scales, with deep learning tools to rapidly convert images into ecological data. However, deep learning applications for wildlife imagery have focused exclusively on living subjects. Here, we identify an overlooked opportunity to extract latent, yet ecologically relevant, meteorological information. We produce an annotated image dataset of micrometeorological conditions across 49 wildlife cameras in South Africas Maloti-Drakensberg and the Swiss Alps. We train ensemble deep learning models to classify conditions as overcast, sunshine, hail or snow. Our best model achieves 91.7% accuracy on test cameras not seen during training. Furthermore, we show how effective accuracy is raised to 96% by disregarding 14.1% of classifications where ensemble member models did not reach a consensus. Unlike previous studies we test model performance in remote and novel locations, distinguishing overcast and sunny conditions in Svalbard, Norway with 79.3% accuracy (93.9% consensus accuracy). Our model rapidly classifies sunshine, snow and hail in almost 2 million unlabeled images. Resulting micrometeorological data illustrated common seasonal patterns of summer hailstorms and autumn snowfalls across mountains in the northern and southern hemispheres. However, daily patterns of sunshine and shade diverged between sites, impacting daily temperature cycles. Crucially, we leverage micrometeorological data to demonstrate that (1) experimental warming using open-top chambers shortens early snow events in autumn, and (2) image-derived sunshine marginally outperforms sensor-derived temperature when predicting bumblebee foraging. These methods generate novel micrometeorological variables in synchrony with biological recordings, enabling new insights from an increasingly global network of wildlife cameras.

ecology↗

bioRxiv2023

The drivers of dark diversity in the Scandinavian tundra are metric-dependent

AimDark diversity refers to the set of species that are not observed in an area but could potentially occur based on suitable local environmental conditions. In this paper, we applied both niche-based and co-occurrence-based methods to estimate the dark diversity of vascular plant species in the subarctic tundra. We then aimed to unravel the drivers explaining (1) why some locations were missing relatively more suitable species than others, and (2) why certain plant species were more often absent from suitable locations than others. LocationThe Scandinavian tundra around Abisko, northern Sweden. MethodsWe calculated the dark diversity in 107 plots spread out across four mountain trails using four different methods. Two niche-based (Beals index and hypergeometric method) and two co-occurrences-based (climatic niche model and climatic niche model followed by species-specific threshold) methods. This was then followed by multiple generalized linear mixed models and general linear models to determine which habitat characteristics and species traits contributed most to the dark diversity. ResultsThe study showed a notable divergence in the predicted drivers of dark diversity depending on the method used. Nevertheless, we can conclude that plot-level dark diversity was generally 18% higher in areas at low elevations and 30% and 10% higher in areas with a low species richness or low levels of habitat disturbance, respectively. ConclusionOur findings call for caution when interpreting statistical findings of dark diversity estimates. Even so, all analyses point towards an important role for natural processes such as competitive dominance as main driver of the spatial patterns found in dark diversity in the northern Scandes.

ecology↗

bioRxiv2022

Climatic refugia in the coldest neotropical hotspot, the Andean paramo

AimThe Andean paramo is the most biodiverse high-mountain region on Earth and past glaciation dynamics during the Quaternary are greatly responsible for its plant diversification. Here, we aim at identifying potential climatic refugia since the Last Glacial Maximum (LGM) in the paramo, according to plant family, biogeographic origin, and life-form. LocationThe paramo region in the Northern Andes MethodsWe built species distribution models for 664 plant species to generate range maps under current and LGM conditions, using five General Circulation Models (GCMs). For each species and GCM, we identified potential (suitable) and potential active (likely still occupied) refugia where both current and LGM range maps overlap. We stacked and averaged the resulting refugia maps across species and GCMs to generate consensus maps for all species, plant families, biogeographic origins and life-forms. All maps were corrected for potential confounding effect due to species richness. ResultsWe found refugia to be chiefly located in the southern and central paramos of Ecuador and Peru, especially towards the paramo ecotone with lower-elevation forests. However, we found additional specific patterns according to plant family, biogeographic origin and life-form. For instance, endemics showed refugia concentrated in the northern paramos. Main conclusionsOur findings suggest that large and connected paramo areas, but also the transitional Amotape-Huancabamba zone with the Central Andes, are primordial areas for plant species refugia since the LGM. This study therefore enriches our understanding on paramo evolution and calls for future research on plant responses to future climate change.

ecology↗

bioRxiv2021

Climate-change risk analysis for global urban forests

Urban forests (i.e. all vegetation present in urban areas), provide environmental and socioeconomic benefits1 to more than half of the global population2. Projected climate change threatens these benefits to society3-5. Here, we assess vulnerability to climate change of 16,006 plant species present in the urban forests of 1,010 cities within 93 countries, using three vulnerability metrics: exposure, safety margin and risk. Exposure expresses the magnitude of projected changes in climate in a given area, safety margin measures species sensitivity to climate change, and risk is the difference between exposure and safety margin6. We identified 9,676 (60.5%) and 8,344 (52.1%) species exceeding their current climatic tolerance (i.e. safety margin) for mean annual temperature (MAT) and annual precipitation (AP), respectively. By 2050, 13,479 (84.2%) and 9,960 (62.2%) species are predicted to be at risk from projected changes in MAT and AP, respectively, with risk increasing in cities at lower latitudes. Our results can aid evaluation of the impacts of climate change on urban forests and identify the species most at risk. Considering future climates when selecting species for urban plantings will enhance the long-term societal benefits provided by urban forests, including their contribution to mitigating the magnitude and impacts of climate change.

ecology↗

bioRxiv2021

rasterdiv - an Information Theory tailored R package for measuring ecosystem heterogeneity from space: to the origin and back

O_LIEcosystem heterogeneity has been widely recognized as a key ecological feature, influencing several ecological functions, since it is strictly related to several ecological functions like diversity patterns and change, metapopulation dynamics, population connectivity, or gene flow. C_LIO_LIIn this paper, we present a new R package - rasterdiv - to calculate heterogeneity indices based on remotely sensed data. We also provide an ecological application at the landscape scale and demonstrate its power in revealing potentially hidden heterogeneity patterns. C_LIO_LIThe rasterdiv package allows calculating multiple indices, robustly rooted in Information Theory, and based on reproducible open source algorithms. C_LI

ecology↗

bioRxiv2021

From zero to infinity: minimum to maximum diversity of the planet by spatio-parametric Rao's quadratic entropy

AimThe majority of work done to gather information on Earth diversity has been carried out by in-situ data, with known issues related to epistemology (e.g., species determination and taxonomy), spatial uncertainty, logistics (time and costs), among others. An alternative way to gather information about spatial ecosystem variability is the use of satellite remote sensing. It works as a powerful tool for attaining rapid and standardized information. Several metrics used to calculate remotely sensed diversity of ecosystems are based on Shannons Information Theory, namely on the differences in relative abundance of pixel reflectances in a certain area. Additional metrics like the Raos quadratic entropy allow the use of spectral distance beside abundance, but they are point descriptors of diversity, namely they can account only for a part of the whole diversity continuum. The aim of this paper is thus to generalize the Raos quadratic entropy by proposing its parameterization for the first time. InnovationThe parametric Raos quadratic entropy, coded in R, i) allows to represent the whole continuum of potential diversity indices in one formula, and ii) starting from the Raos quadratic entropy, allows to explicitly make use of distances among pixel reflectance values, together with relative abundances. Main conclusionsThe proposed unifying measure is an integration between abundance- and distance-based algorithms to map the continuum of diversity given a satellite image at any spatial scale.

ecology↗

bioRxiv2020

From local spectral species to global spectral communities: a benchmark for ecosystem diversity estimate by remote sensing

In the light of unprecedented change in global biodiversity, real-time and accurate ecosystem and biodiversity assessments are becoming increasingly essential. Nevertheless, estimation of biodiversity using ecological field data can be difficult for several reasons. For instance, for very large areas, it is challenging to collect data that provide reliable information. Some of these restrictions in Earth observation can be avoided through the use of remote sensing approaches. Various studies have estimated biodiversity on the basis of the Spectral Variation Hypothesis (SVH). According to this hypothesis, spectral heterogeneity over the different pixel units of a spatial grid reflects a higher niche heterogeneity, allowing more organisms to coexist. Recently, the spectral species concept has been derived, following the consideration that spectral heterogeneity at a landscape scale corresponds to a combination of subspaces sharing a similar spectral signature. With the use of high resolution remote sensing data, on a local scale, these subspaces can be identified as separate spectral entities, the so called "spectral species". Our approach extends this concept over wide spatial extents and to a higher level of biological organization. We applied this method to MODIS imagery data across Europe. Obviously, in this case, a spectral species identified by MODIS is not associated to a single plant species in the field but rather to a species assemblage, habitat, or ecosystem. Based on such spectral information, we propose a straightforward method to derive - (local relative abundance and richness of spectral species) and {beta}-diversity (turnover of spectral species) maps over wide geographical areas.

ecology↗

bioRxiv2020

Once upon a time in the south: local drivers of plant invasion in the harsh sub-Antarctic islands

AimHere, we aim to: (i) investigate the local effect of environmental and human-related factors on alien plant invasion in sub-Antarctic islands; (ii) explore the relationship between alien species features and their dependence on anthropogenic propagule pressure; and (iii) unravel key traits conferring invasiveness in the sub-Antarctic. LocationPossession Island, Crozet archipelago (French sub-Antarctic islands). TaxonNon-native vascular plants (Poaceae, Caryophyllaceae, Juncaceae). MethodsSingle-species distribution models were used to explore the effect of high-resolution topoclimatic and human-related variables on the occurrence of six of the most aggressive alien plants colonizing French sub-Antarctic islands. Furthermore, the interaction between alien species traits and their response to anthropogenic propagule pressure was analysed by means of a multi-species distribution model. This allowed identifying the features of species that were associated to low dependence on human-assisted introductions, and were thus potentially more invasive. ResultsWe observed two main invasion patterns: low-spread species strongly dependent on anthropogenic propagule pressure and high-spread species limited mainly by harsh climatic conditions. Differences in invasiveness across species mostly related to their residence time, life history and plant height, with older introductions, perennial and low-stature species being more invasive. Main conclusionsThe availability of high-resolution data improved our understanding of the role of environmental and human-related factors in driving alien species distribution on sub-Antarctic islands. At the same time, the identification of alien species features conferring invasiveness may help anticipating future problematic invasions.

ecology↗

bioRxiv2019

Species better track the shifting isotherms in the oceans than on lands

Despite mounting evidence of species redistribution as climate warms, our knowledge of the coupling between species range shifts and isotherm shifts is limited. Compiling a global geo-database of 30,534 range shifts from 12,415 taxa, we show that only marine taxa closely track the shifting isotherms. In the oceans, the velocity of isotherm shifts interacts synergistically with anthropogenic disturbances and baseline temperatures such that isotherm tracking by marine life happens either in warm and undisturbed waters (e.g. Central Pacific Basin) or in colder waters where human activities are more pronounced (e.g. North Sea). On lands, increasing anthropogenic activities and temperatures negatively impact the capacity of terrestrial taxa to track isotherm shifts in latitude and elevation, respectively. This suggests that terrestrial taxa are lagging behind the shifting isotherms, most likely due to their wider thermal safety margin, more constrained physical environment for dispersal and higher availability of thermal microrefugia at shorter distances.

ecology↗