arXiv subjects

Maxime Lenormand

Publications and source records attributed to Maxime Lenormand.

At least 19 recordsLinked to original sources

arXiv2026

From biodiversity modelling to conservation action: a spatial indicator for prioritising tropical forest protection, restoration, and management

Tropical forests harbour exceptional biodiversity but are increasingly threatened by anthropogenic pressures, making their conservation central to achieving the Convention on Biological Diversity targets. However, national conservation planning is often constrained by heterogeneous monitoring frameworks and limited integration of biodiversity and anthropogenic pressures. We develop a synthetic spatial indicator that combines open-access biodiversity and land-use data to identify refuge and conflict areas between ecological potential and anthropogenic pressure. Using Costa Rica as a national-scale demonstrator, we assess its capacity to support conservation prioritisation and evaluate the current conservation network. Ecological potential was estimated using multi-species distribution models for 254 dominant canopy tree species, serving as an operational proxy for tropical forest biodiversity and ecological structure. We quantified anthropogenic pressure from land-use patterns and combined it with ecological potential to identify refuge and conflict areas. We then tested the spatial significance of these areas and evaluated their representation within the national conservation network. The indicator reveals a clear spatial organisation of biodiversity-pressure interactions: refuge areas coincide with large, continuous forest cores, whereas conflict areas are concentrated in fragmented landscapes and may extend into protected areas. Flexible and transferable, the framework distinguishes areas requiring strict protection from those where restoration, sustainable management, or pressure mitigation should be prioritised. Rather than prescribing conservation actions, the refuge-conflict indicator provides a practical decision-support tool to assess conservation networks, strengthen ecological connectivity, and guide national biodiversity planning.

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arXiv2026

The geopolitics of knowledge: tipping points, national fingerprints, and the unequal globalization of science

Science is often portrayed as a universal and self-contained system, driven solely by the internal logic of knowledge accumulation and isolated from the turbulences of the socio-political world. In this paper, we challenge this narrative by providing systematic quantitative evidence that the global scientific ecosystem is deeply shaped by geopolitical transformations. Using a large-scale dataset of scientific publications drawn from the OpenAlex database, spanning over five decades and covering virtually all countries and disciplinary areas, we track the evolution of national research profiles and show that geopolitical dynamics shape scientific agendas at multiple scales. At the global level, intrinsic scientific change is slow and cumulative, but exogenous shocks, such as Chernobyl, September 11, and COVID-19, produce rapid disruptions that synchronously reconfigure the priorities of many countries at once. At the country level, we document a broad globalization of knowledge, yet deeply heterogeneous: while Global North countries converge toward a shared international agenda, Global South countries display strong dependence on international resources alongside locally distinctive research interests. Among emerging Southern economies, scientific power is increasingly asserted through specialized and independent agendas. Finally, we observe a reorganization of global scientific influence toward a more polycentric structure, with the emergence of a Southern cluster gravitating around Brazil and Indonesia as new regional hubs.

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arXiv2025

Predicted decline in common bird and butterfly species despite conservation policy scenarios in Europe

In response to increasing threats to biodiversity, conservation objectives have been set to halt biodiversity decline by reducing direct anthropogenic drivers. However, the potential effects of these objectives on common species remain rarely studied. We analyse the effect of a range of drivers related to climate, land use and land use intensity, on 265 common bird and 144 common butterfly species from more than 20,000 sites between 2000 and 2021 across 26 European countries. We use land-use and land-use intensity scenarios produced previously using the IPBES Nature Futures Framework, and climate change scenarios in order to project biodiversity drivers in Europe up to 2050. We translate these driver changes into abundance variations for common bird and butterfly species, and for multi-species indicators used to monitor common biodiversity status in Europe. The projected trends relatively improve, while still declining for birds, notably farmland species, under the scenarios meeting conservation objectives, with few effects on butterflies. No scenario shows a stop or a reversal in the average decline in abundance of bird and butterfly species. Our results therefore question the common biodiversity future under current conservation policies and highlight the need for other anticipatory frameworks, not implicitly based on a growing need for natural resources.

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arXiv2025

Modelling species distributions using remote sensing predictors: Comparing Dynamic Habitat Index and LULC

This study compares the predictive capacity of the Dynamic Habitat Index (DHI) - a remote sensing (RS)-based measure of habitat productivity and variability - against traditional land-use/land-cover (LULC) metrics in species distribution modelling (SDM) applications. RS and LULC-based SDMs were built using distribution data for eleven bird, amphibian, and mammal species in \^Ile-de-France. Predictor variables were derived from Sentinel-2 RS data and LULC classifications, with the latter incorporating Euclidean distance to habitat types. Ensemble SDMs were built using nine algorithms and evaluated with the Continuous Boyce Index (CBI) and a calibrated AUC. Habitat suitability scores and their binary transformations were assessed using niche overlap indices (Schoener, Warren, and Spearman rank correlation coefficient). Both RS and LULC approaches exhibited similar predictive accuracy overall. After binarisation however, the resulting niche maps diverged significantly. While LULC-based models exhibited spatial constraints (habitat suitability decreased as distance from recorded occurrences increased), RS-based models, which used continuous data, were not affected by geographic bias or distance effects. These results underscore the need to account for spatial biases in LULC-based SDMs. The DHI may offer a more spatially neutral alternative, making it a promising predictor for modelling species niches at regional scales.

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arXiv2025

Unlocking tropical forest complexity: How tree assemblages in secondary forests boost biodiversity conservation

Secondary forests now dominate tropical landscapes and play a crucial role in achieving COP15 conservation objectives. This study develops a replicable national approach to identifying and characterising forest ecosystems, with a focus on the role of secondary forests. We hypothesised that dominant tree species in the forest canopy serve as reliable indicators for delineating forest ecosystems and untangling biodiversity complexity. Using national inventories, we identified in situ clusters through hierarchical clustering based on dominant species abundance dissimilarity, determined using the Importance Variable Index. These clusters were characterised by analysing species assemblages and their interactions. We then applied object-oriented Random Forest modelling, segmenting the national forest cover using NDVI to identify the forest ecosystems derived from in situ clusters. Freely available spectral (Sentinel-2) and environmental data were used in the model to delineate and characterise key forest ecosystems. We finished with an assessment of distribution of secondary and old-growth forests within ecosystems. In Costa Rica, 495 dominant tree species defined 10 in situ clusters, with 7 main clusters successfully modelled. The modelling (F1-score: 0.73, macro F1-score: 0.58) and species-based characterisation highlighted the main ecological trends of these ecosystems, which are distinguished by specific species dominance, topography, climate, and vegetation dynamics, aligning with local forest classifications. The analysis of secondary forest distribution provided an initial assessment of ecosystem vulnerability by evaluating their role in forest maintenance and dynamics. This approach also underscored the major challenge of in situ data acquisition.

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arXiv2024

Implication of modelling choices on connectivity estimation: A comparative analysis

We focus on connectivity methods used to understand and predict how landscapes and habitats facilitate or impede the movement and dispersal of species. Our objective is to compare the implication of methodological choices at three stages of the modelling framework: landscape characterisation, connectivity estimation, and connectivity assessment. What are the convergences and divergences of different modelling approaches? What are the implications of their combined results for landscape planning? We implemented two landscape characterisation approaches: expert opinion and species distribution model (SDM); four connectivity estimation models: Euclidean distance, least-cost paths (LCP), circuit theory, and stochastic movement simulation (SMS); and two connectivity indices: flux and area-weighted flux (dPCflux). We compared outcomes such as movement maps and habitat prioritisation for a rural landscape in southwestern France. Landscape characterisation is the main factor influencing connectivity assessment. The movement maps reflect the models' assumptions: LCP produced narrow beams reflecting the optimal pathways; whereas circuit theory and SMS produced wider estimation reflecting movement stochasticity, with SMS integrating behavioural drivers. The indices highlighted different aspects: dPCflux the surface of suitable habitats and flux their proximity. We recommend focusing on landscape characterisation before engaging further in the modelling framework. We emphasise the importance of stochasticity and behavioural drivers in connectivity, which can be reflected using circuit theory, SMS or other stochastic individual-based models. We stress the importance of using multiple indices to capture the multi-factorial aspect of connectivity.

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arXiv2024

Coupling in situ and remote sensing data to assess $\alpha$- and $\beta$-diversity over biogeographic gradients

The mapping of plant biodiversity represents a fundamental stage in establishing conservation priorities, particularly in identifying groups of species that share ecological requirements or evolutionary histories. This is often achieved by assessing different spatial diversity patterns in plant population distributions. In this paper, we present two primary data sources crucial for biodiversity monitoring: in situ measurements from botanical observations and remote sensing (RS). In situ methods involve directly collecting data from specific sites, providing detailed insights into ecological patterns but often constrained by resource limitations. Integrating in situ and RS data highlights their complementary strengths, which depend on factors such as study scale, resolution, and logistical feasibility. While in situ approaches are characterized by precision, RS offers efficiency and extensive, repeated coverage. This research integrates in situ and RS data to analyze plant and spectral diversity across France at a spatial resolution of 5 km, encompassing over 23,000 grid cells. We employ four established diversity metrics leveraging the spatial distribution of 6,650 plant species and 250 spectral clusters (derived from MODIS data at a 500-meter resolution). Through bioregionalization network analysis combining these data sources, we identified five distinct bioregions that capture the biogeographical structure of plant biodiversity in France. Additionally, we explore the relationship between plant species diversity and spectral cluster diversity within and between these bioregions, offering novel insights into the spatial dynamics of plant biodiversity.

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arXiv2024

Bioregionalization analyses with the bioregion R-package

Bioregionalization consists in the identification of spatial units with similar species composition and is a classical approach in the fields of biogeography and macroecology. The recent emergence of global databases, improvements in computational power, and the development of clustering algorithms coming from the network theory have led to several major updates of the bioregionalizations of many taxa. A typical bioregionalization workflow involves five different steps: formatting the input data, computing a (dis)similarity matrix, selecting a bioregionalization algorithm, evaluating the resulting bioregionalization, and mapping and interpreting the bioregions. For most of these steps, there are many options available in the methods and R packages. Here, we present bioregion, a package that includes all the steps of a bioregionalization workflow under a single architecture, with an exhaustive list of the bioregionalization algorithms used in biogeography and macroecology. These algorithms include (non-)hierarchical algorithms as well as community detection algorithms coming from the network theory. Some key methods from the literature, such as the network community detection algorithm Infomap or OSLOM (Order Statistics Local Optimization Method), that were not available in the R language are included in bioregion. By combining different methods coming from different fields to communicate easily, bioregion will allow a reproducible and complete comparison of the different bioregionalization methods, which is still missing in the literature.

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arXiv2023

Mapping mobile service usage diversity in cities

The ubiquitous use of mobile devices and associated Internet services generates vast volumes of geolocated data, offering valuable insights into human behaviors and their interactions with urban environments. Over the past decade, mobile phone data have proven indispensable in various fields such as demography, geography, transport planning, and epidemiology. They enable researchers to examine human mobility patterns on unprecedented scales and analyze the spatial structure and function of cities. The relationship between mobile phone data and land use has also been extensively explored, particularly in inferring land use patterns from spatiotemporal activity. However, many studies rely on Call Detail Records (CDR) or eXtended Detail Records (XDR), which may not capture specific mobile application usage. This study aims to address this gap by mapping mobile service usage diversity in 20 French cities and investigating its correlation with land use distribution. Utilizing a Shannon diversity index, the study evaluates mobile service usage diversity based on hourly traffic volume data from 17 mobile services. Furthermore, the study compares temporal diversity with land distribution both within and among cities.

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arXiv2022

Habitat connectivity in agricultural landscapes improving multi-functionality of constructed wetlands as nature-based solutions

The prevention of biodiversity loss in agricultural landscapes to protect ecosystem stability and functions is of major importance in itself and for the maintenance of associated ecosystem services. Intense agriculture leads to a loss in species richness and homogenization of species pools as well as the fragmentation of natural habitats and groundwater pollution. Constructed wetlands stand as nature-based solutions (NBS) to buffer the degradation of water quality by intercepting the transfer of particles, nutrients and pesticides between crops and surface waters. In karstic watersheds where sinkholes short-cut surface water directly to groundwater increasing water resource vulnerability, constructed wetlands are recommended to mitigate agricultural pollutants. Constructed wetlands also have the potential to improve landscape connectivity by providing refuge and breeding sites for wildlife, especially for amphibians. We propose here a methodology to identify optimal locations for water pollution mitigation using constructed wetlands from the perspective of habitat connectivity. We use ecological niche modelling at the regional scale to model the potential of habitat suitability for nine amphibian species, and to infer how the landscape impedes species movements. We combine those results to graph theory to identify connectivity priorities at the operational scale of an agricultural catchment area. Our framework allowed us to identify optimal areas from the point of view of the species, to analyze the effect of multifunctional constructed wetlands aiming to both reduce water pollution and to improve amphibian species habitat overall connectivity. More generally, we show the potential of habitat connectivity assessment to improve multifunctionality of NBS for pollution mitigation.

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arXiv2022

Protection gaps in Amazon floodplains will increase with climate change: Insight from the world's largest scaled freshwater fish

The Amazon floodplains represent important surfaces of highly valuable ecosystems, yet they remain neglected from protected areas. While the efficiency of the protected area network of the Amazon basin may be jeopardised by climate change, floodplains are exposed to important consequences of climate change but are omitted from species distribution models and protection gap analyses. We modelled the current and future (2070) distribution of the giant bony-tongue fish Arapaima sp. accounting for climate and habitat requirements, with consideration of dam presence (already existing and planned constructions) and hydroperiod (high- and low-water stages). We further quantified the amount of suitable environment which falls inside and outside the current network of protected areas to identify spatial conservation gaps. We predict climate change to cause the decline of environmental suitability by 16.6% during the high-water stage, and by 19.4% during the low-water stage. We found that about 70% of the suitable environments of Arapaima sp. remain currently unprotected, which is likely to increase by 5% with future climate change effects. Both current and projected dam constructions may hamper population flows between the central and the Bolivian and Peruvian parts of the basin. We highlight protection gaps mostly in the southwestern part of the basin and recommend the extension of the current network of protected areas in the floodplains of the upper Ucayali, Juru\`a and Purus Rivers and their tributaries. This study showed the importance of taking into account hydroperiods and dispersal barriers in forecasting the distribution of freshwater fish species, and stresses the urgent need to integrate floodplains to the protected area networks.

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arXiv2021

Dispersal-based species pools as sources of connectivity area mismatches

Context - Prioritising is likely to differ depending on the species considered for connectivity assessments, leading to a lack of consensual decisions for territorial planning. Objectives - The objective was to assess the relevance of identifying priority areas for connectivity for groups of species based on common dispersal abilities. We aimed to assess the impact of target groups choices on predicted priority areas. Method - The study was located at the Thau Lagoon territory to demonstrate the methodological approach. Ecological niche modelling was used to quantify species resistance and to identify suitable habitat patches. We coupled the least-cost path methodology with circuit theory to assess species connectivity. We classified connectivity from high to low levels and averaged the results by dispersal groups. Results - We found important differences in identified priority areas between groups with dissimilar dispersal abilities, with little overlap between highly connected areas. We identified a gap between the level of protection of low dispersal species and highly connected areas. We found mismatches between existing corridors and connectivity in low dispersal species, and a greater impact in areas of expected urban sprawl projects on favourably connected areas for species with high dispersal capabilities. Conclusion - We have demonstrated that a diversity of dispersal capacity ranges must be accounted for in order to identify ecological corridors in programmes that aim to restore habitat connectivity at territorial levels. Our findings are oriented to support the decisions of planning initiatives, at both local and regional scale.

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arXiv2021

Mapping of Ebola virus spillover: Suitability and seasonal variability at the landscape scale

The unexpected Ebola virus outbreak in West Africa in 2014 involving the Zaire ebolavirus made clear that other regions outside Central Africa, its previously documented niche, were at risk of future epidemics. The complex transmission cycle and a lack of epidemiological data make mapping areas at risk of the disease challenging. We used a Geographic Information System-based multicriteria evaluation (GIS-MCE), a knowledge-based approach, to identify areas suitable for Ebola virus spillover to humans in regions of Guinea, Congo and Gabon where Ebola viruses already emerged. We identified environmental, climatic and anthropogenic risk factors and potential hosts from a literature review. Geographical data layers, representing risk factors, were combined to produce suitability maps of Ebola virus spillover at the landscape scale. Our maps show high spatial and temporal variability in the suitability for Ebola virus spillover at a fine regional scale. Reported spillover events fell in areas of intermediate to high suitability in our maps, and a sensitivity analysis showed that the maps produced were robust. There are still important gaps in our knowledge about what factors are associated with the risk of Ebola virus spillover. As more information becomes available, maps produced using the GIS-MCE approach can be easily updated to improve surveillance and the prevention of future outbreaks.

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arXiv2021

Intersectional approach of everyday geography

Hour-by-hour variations in spatial distribution of gender, age and social class within cities remain poorly explored and combined in the segregation literature mainly centered on home places from a single social dimension. Taking advantage of 49 mobility surveys compiled together (385,000 respondents and 1,711,000 trips) and covering 60% of France's population, we consider variations in hourly populations of 2,572 districts after disaggregating population across gender, age and education level. We first isolate five district hourly profiles (two 'daytime attractive', two 'nighttime attractive' and one more 'stable') with very unequal distributions according to urban gradient but also to social groups. We then explore the intersectional forms of these everyday geographies. Taking as reference the dominant groups (men, middle-age and high educated people) known as concentrating hegemonic power and capital, we analyze specifically whether district hourly profiles of dominant groups diverge from those of the others groups. It is especially in the areas exhibiting strong increase or strong decrease of ambient population during the day that district hourly profiles not only combine the largest dissimilarities all together across gender, age and education level but are also widely more synchronous between dominant groups than between non-dominant groups (women, elderly and low educated people). These intersectional patterns shed new light on areas where peers are synchronously located over the 24-hour period and thus potentially in better position to interact and to defend their common interests.

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arXiv2021

Uncovering the socioeconomic structure of spatial and social interactions in cities

The relationship between urban mobility, social networks and socioeconomic status is complex and difficult to apprehend, notably due to the lack of data. Here we use mobile phone data to analyze the socioeconomic structure of spatial and social interaction in the Chilean's urban system. Based on the concept of spatial and social events, we develop a methodology to assess the level of spatial and social interactions between locations according to their socioeconomic status. We demonstrate that people with the same socioeconomic status preferentially interact with locations and people with a similar socioeconomic status. We also show that this proximity varies similarly for both spatial and social interactions during the course of the week. Finally, we highlight that these preferential interactions appear to be holding when considering city-city interactions.

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arXiv2021

Assessing the effect of sample bias correction in species distribution models

Open-source biodiversity databases contain a large amount of species occurrence records, but these are often spatially biased, which affects the reliability of species distribution models based on these records. Sample bias correction techniques include data filtering at the cost of record numbers or require considerable additional sampling effort. However, independent data are rarely available and assessment of the correction technique must rely on performance metrics computed with subsets of the only available (biased) data, which may be misleading. Here we assess the extent to which an acknowledged sample bias correction technique is likely to improve models' ability to predict species distributions in the absence of independent data. We assessed the variation in model predictions induced by the correction and model stochasticity. We present an index of the effect of correction relative to model stochasticity, the Relative Overlap Index (ROI). We tested whether the ROI better represented the effect of correction than classic performance metrics and absolute overlap metrics using 64 vertebrate species and 21 virtual species with a generated sample bias. When based on absolute overlaps and cross-validation performance metrics, we found no effect of correction, except for cAUC. When considering its effect relative to model stochasticity, the effect of correction depended on the site and the species. Virtual species enabled us to verify that the correction actually improved distribution predictions and the biological relevance of the selected variables at the sites with a clear gradient of sample bias, and when species distribution predictors are not correlated with sample bias patterns.

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arXiv2021

Animal daily mobility patterns analysis using resting event networks

Characterizing the movement patterns of animals is crucial to improve our understanding of their behavior and thus develop adequate conservation strategies. Such investigations, which could not have been implemented in practice only a few years ago, have been facilitated through the recent advances in tracking methods that enable researchers to study animal movement at an unprecedented spatio-temporal resolution. However, the identification and extraction of patterns from spatio-temporal trajectories is still a general problem that has relevance for many applications. Here, we rely on the concept of resting event networks to identify the presence of daily mobility patterns in animal spatio-temporal trajectories. We illustrate our approach by analyzing spatio-temporal trajectories of several fish species in a large hydropeaking river.

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arXiv2020

On the importance of trip destination for modeling individual human mobility patterns

Getting insights on human mobility patterns and being able to reproduce them accurately is of the utmost importance in a wide range of applications from public health, to transport and urban planning. Still the relationship between the effort individuals will invest in a trip and its purpose importance is not taken into account in the individual mobility models that can be found in the recent literature. Here, we address this issue by introducing a model hypothesizing a relation between the importance of a trip and the distance traveled. In most practical cases, quantifying such importance is undoable. We overcome this difficulty by focusing on shopping trips (for which we have empirical data) and by taking the price of items as a proxy. Our model is able to reproduce the long-tailed distribution in travel distances empirically observed and to explain the scaling relationship between distance traveled and item value found in the data.

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