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  • Publication
    Restriction temporaire
    Towards a multi-dimensional assessment of plant diversity in an enriched oil palm plantation
    (Neuchâtel : Université de Neuchâtel, 2025) ;
    La biodiversité comprend de multiples dimensions qui reflètent des propriétés et des processus écologiques uniques à travers les espèces, les communautés et les écosystèmes. Au-delà de la diversité spécifique, la biodiversité s’exprime à travers des dimensions fonctionnelles, structurelles, phylogénétiques, phytochimiques et spectrales, chacune apportant un éclairage complémentaire sur la complexité, le fonctionnement et la résilience des écosystèmes. Capturer cette multidimensionnalité est essentiel pour comprendre la dynamique des écosystèmes et faire face à l’érosion mondiale de la biodiversité. Les forêts tropicales de plaine, qui abritent une biodiversité terrestre exceptionnelle, sont gravement menacées par l’expansion et l’intensification agricoles. En Asie du Sud-Est, la conversion des forêts en plantations industrielles de palmier à huile et d’hévéa a entraîné une perte considérable d’habitats, une diminution de la richesse spécifique et une perturbation de la stabilité des écosystèmes. Les initiatives de restauration, telles que l’enrichissement en biodiversité par des plantations multi-espèces, constituent une stratégie prometteuse pour atténuer ces impacts en augmentant l’hétérogénéité des habitats et la biodiversité. Cependant, l’évaluation du succès de ces initiatives nécessite des approches innovantes et multidimensionnelles intégrant des perspectives complémentaires sur la biodiversité. Cette thèse doctorale contribue à la recherche sur la biodiversité en explorant la diversité végétale selon des dimensions structurelles, phytochimiques et spectrales dans une plantation de palmier à huile enrichie en biodiversité à Sumatra, en Indonésie. En combinant des mesures au sol, des données et techniques de télédétection, ainsi que la métabolomique non ciblée, j’ai caractérisé la diversité végétale au sein de 52 îlots expérimentaux d’arbres intégrés dans une plantation de 140 hectares. Cette approche multidimensionnelle apporte un éclairage sur les mécanismes écologiques façonnant la biodiversité et fait progresser les cadres méthodologiques pour l’évaluation et le suivi exhaustifs de la biodiversité en contexte de restauration. Dans le Chapitre 2, j’ai évalué la diversité structurelle de la végétation en utilisant la télédétection laser terrestre et aéroportée ainsi que des inventaires au sol, mettant en évidence la complémentarité de ces méthodes pour capturer la complexité tridimensionnelle des écosystèmes en régénération. Dans le Chapitre 3, j’ai analysé la diversité spectrale à l’aide de la spectroscopie d’imagerie et souligné son potentiel et ses limites pour la caractérisation de la biodiversité du sous-bois dans des écosystèmes verticalement stratifiés dominés par les canopées de palmier à huile. Enfin, dans le Chapitre 4, j’ai exploré la diversité phytochimique grâce à une analyse métabolomique non ciblée, révélant une forte variabilité chimique parmi les espèces ligneuses naturellement régénérées. Les résultats de cette thèse doctorale soulignent l’importance d’adopter des approches multidimensionnelles pour évaluer la biodiversité en contexte de restauration. En intégrant les dimensions structurelle, phytochimique et spectrale, cette recherche améliore la compréhension des mécanismes écologiques à l’oeuvre lors du rétablissement de la biodiversité et fournit des éléments essentiels pour améliorer les méthodologies d’évaluation et de suivi de la biodiversité. ABSTRACT Biodiversity encompasses multiple dimensions that reflect unique ecological properties and processes across species, communities, and ecosystems. Beyond species-level diversity, biodiversity is expressed through functional, structural, phylogenetic, phytochemical, and spectral dimensions, each offering complementary insights into ecosystem complexity, functioning, and resilience. Capturing this multidimensionality is essential for understanding the dynamics of ecosystems and addressing global biodiversity loss. Tropical lowland forests, which harbour high terrestrial biodiversity, face severe threats from agricultural expansion and intensification. In Southeast Asia, forest conversion to large-scale oil palm and rubber plantations has led to significant habitat loss, reduced species richness, and disrupted ecosystem stability. Restoration initiatives, such as biodiversity enrichment through mixed-species plantations, offer a promising strategy to mitigate these impacts by enhancing habitat heterogeneity and biodiversity. However, evaluating the success of these initiatives requires innovative, multidimensional approaches that integrate complementary perspectives on biodiversity. This doctoral dissertation contributes to biodiversity research by exploring plant diversity across structural, phytochemical, and spectral dimensions in a biodiversityenriched oil palm plantation in Sumatra, Indonesia. Using ground-based measurements, remote sensing data and techniques, and untargeted metabolomics, I characterised plant diversity within 52 experimental tree islands embedded in a 140-oil palm plantation. This multidimensional approach provides insights into the ecological mechanisms shaping biodiversity and advances methodological frameworks for comprehensive biodiversity assessment and monitoring in restoration contexts. In Chapter 2, I evaluated vegetation structural diversity using terrestrial and airborne laser scanning and ground-based inventories, demonstrating the complementary strength of these methods in capturing the three-dimensional complexity of multilayer recovering ecosystems. In Chapter 3, I assessed spectral diversity using imaging spectroscopy and highlighted its potential and limitations in capturing understorey biodiversity within vertically stratified ecosystems dominated by oil palm canopies. Finally, in Chapter 4, I explored phytochemical diversity through untargeted metabolomic analysis, uncovering high chemical variability among naturally regenerated woody species. The findings of my doctoral dissertation underscore the importance of adopting multidimensional approaches for assessing biodiversity in restoration contexts. By integrating structural, phytochemical, and spectral dimensions, this research advances the understanding of ecological mechanisms during biodiversity recovery and offers critical insights for improving methodologies for biodiversity assessment and monitoring.
  • Publication
    Accès libre
    Comparing airborne and terrestrial LiDAR with ground-based inventory metrics of vegetation structural complexity in oil palm agroforests
    (2024) ;
    Nicolò Camarretta
    ;
    Martin Ehbrecht
    ;
    Michael Schlund
    ;
    Gustavo Brant Paterno
    ;
    Dominik Seidel
    ;
    Nathaly Guerrero-Ramírez
    ;
    Fabian Brambach
    ;
    Dirk Hölscher
    ;
    Holger Kreft
    ;
    Bambang Irawan
    ;
    Leti Sundawati
    ;
    Vegetation structural complexity is an important component of forest ecosystems, influencing biodiversity and functioning. Due to the heterogeneous distribution of vegetation elements, structural complexity underpins ecological dynamics, species composition, microclimate, and habitat diversity. Field measurements and Light Detection and Ranging (LiDAR) data, such as airborne (ALS) and terrestrial (TLS), can assess structural characteristics of forest and agroforestry systems at various spatial scales. This assessment is urgently needed for monitoring ecosystem restoration in degraded lands (e.g., in oil palm landscapes), where it is not well-known how structural measures derived from these different approaches relate to each other. Here, we compared the degree of correlation between individual and multivariate datasets of vegetation structural complexity metrics derived from ALS, TLS, and ground-based inventory approaches. The study was conducted in a 140 ha oil palm monoculture, enriched with 52 plots in the form of tree islands representing agroforestry systems of varying sizes and planted diversity levels in Sumatra, Indonesia. Our datasets comprised 25 ALS, five TLS, and nine ground-based inventory metrics. We studied correlations among metrics related to traditional stand summary, heterogeneity, and vertical and horizontal stand structure. We used principal component analysis for data dimensionality reduction, correlation analysis to quantify the strength of relationships between metrics, and Procrustes analysis to investigate the agreement between datasets. Significant correlations were found between ALS and TLS metrics for canopy density (r = 0.79) and maximum tree height (r = 0.58) and between ALS and ground-based inventory measures of stand heterogeneity and height diversity (r between 0.60 and −0.63). Further, we observed significant agreements between the ordinations of multivariate datasets (r = 0.56 for ALS − TLS; and r = 0.46 for ALS – ground-based inventory). Our findings underline the ability of ALS to capture structural complexity patterns, especially for canopy gap dynamics and vegetation height metrics, as captured by TLS, and for measures of heterogeneity and vertical structure as captured by ground-based inventories. Our study highlights the strength of each approach and underscores the potential of integrating ALS and TLS with ground-based inventories for a comprehensive characterization of vegetation structure in complex agroforestry systems, which can provide guidance for their management and support ecosystem restoration monitoring efforts.
  • Publication
    Accès libre
    Landscape heterogeneity and soil biota are central to multi-taxa diversity for oil palm landscape restoration
    (2023) ;
    Holger Kreft
    ;
    Isabelle Arimond
    ;
    Johannes Ballauff
    ;
    Dirk Berkelmann
    ;
    Fabian Brambach
    ;
    Rolf Daniel
    ;
    Ingo Grass
    ;
    Jes Hines
    ;
    Dirk Hölscher
    ;
    Bambang Irawan
    ;
    Alena Krause
    ;
    Andrea Polle
    ;
    Anton Potapov
    ;
    Lena Sachsenmaier
    ;
    Stefan Scheu
    ;
    Leti Sundawati
    ;
    Teja Tscharntke
    ;
    ;
    Nathaly Guerrero-Ramírez
    Enhancing biodiversity in monoculture-dominated landscapes is a key sustainability challenge that requires considering the spatial organization of ecological communities (beta diversity). Here, we tested whether increasing landscape heterogeneity, through establishing 52 tree islands in an oil-palm landscape, is a suitable restoration strategy to enhance the diversity of six taxa (multi-taxa diversity). Further, we elucidated whether patterns in the spatial distribution of above- and below-ground taxa are related, and their role in shaping multi-taxa beta diversity. After five years, islands enhanced diversity at the landscape scale by fostering unique species (turnover). Partial correlation networks revealed that dissimilarity, in vegetation structural complexity and soil conditions, impacts multi-taxa beta diversity and turnover. In addition, soil fauna, bacteria, and fungi were more strongly associated with the overall community than aboveground taxa. Thus, strategies aiming to enhance multi-taxa diversity should consider the central role of landscape heterogeneity and soil biota.