Biology subjects

Zemp, D. C.

Publications and source records attributed to Zemp, D. C..

5 recordsLinked to original sources

bioRxiv2026

Global failure to track international biodiversity targets on islands

Islands harbour exceptional biodiversity but face severe threats, making their conservation crucial to achieving the goals and targets of the Kunming-Montreal Global Biodiversity Framework. We therefore evaluated whether existing indicators can track progress toward the Framework's 23 targets across islands worldwide. We screened 504 biodiversity and socioeconomic indicators from the official framework and other global initiatives, retaining 47 indicators. Historical time series from 1950 onward were modelled and projected to 2030. Indicators were also classified using the Driver-Pressure-State-Impact-Response (DPSIR) and Theory of Change (ToC). Results showed uneven progress: eight targets improved across all available indicators, while ten displayed conflicting trends. Nearly half of the indicators focused on policy and management responses showed improvement, whereas trends in biodiversity pressures and states were mixed. Critically, 15 of 23 targets (65%) lacked a suitable headline indicator, and five targets had no indicator at all. Notably, Targets 2 and 8, addressing ecosystem restoration and climate change impacts, respectively, lacked island indicators entirely. Over half of the available indicators (29 of 47; 62%) were reported at the national level, limiting their applicability to subnational island jurisdictions and potentially obscuring differences between mainland and island conditions. Most targets also lacked quantitative objectives, limiting evaluation of whether the rate of change is sufficient to meet the targets by 2030. We recommend island-level reporting, island-specific indicators, and quantitative benchmarks tailored to island needs.

ecology↗

bioRxiv2026

Towards Scaling-Up Three-Dimensional Habitat Structural Measurements with Multi-Sensor Remote Sensing

Terrestrial Laser Scanning (TLS) captures fine-scaled three-dimensional measurements of ecosystem structure, supporting monitoring of the Essential Biodiversity Variables (EBVs). Yet employing TLS across landscapes remains challenging in remote and topographically complex areas. Remote sensing provides a potential pathway for upscaling TLS-derived structural metrics, but to what extent is unquantified particularly in heterogenous environments, like oceanic islands. Here, we investigated the ability of remote sensing to estimate TLS-derived habitat structure across three contrasting habitats (lowland rainforest, montane cloud forest, and subalpine summit scrub) on La Reunion island. Sentinel-1, Sentinel-2, and Aerial LiDAR (ALS) data were acquired over plots where TLS was completed. We derived defined indices of backscatter coefficients, vegetation indices, and LiDAR metrics and assessed their alignment with TLS measurements using a Procrustes analysis. Subsequently, we used General Additive Models to estimate TLS habitat structure from remote sensing variables. Sentinel-2 exhibited the highest multivariate alignment with TLS (r = 0.51). TLS measurements of horizontal and vertical structure were estimated with the highest cross-validated predictive accuracy (R2 0.39 - 0.73), whilst structural complexity metrics were estimated with greater difficulty (R2 0.02 - 0.20). Multi-sensor models outperformed all single-sensor models in prediction estimates. Model performance also varied across habitats, with the highest agreement between predicted and observed values in the lowland rainforest (r = 0.38), and the lowest agreement (r = 0.35) in the montane cloud forest. Yet the dominant structural feature of each habitat was most accurately captured with remote sensing. Our results demonstrate the potential of integrating multi-sensor remote sensing data to upscale key dimensions of TLS-derived ecosystem structure but remains challenging for fine-scale structural complexity. These findings highlight both the potential and constraints of remote sensing for developing scalable, long-term monitoring frameworks for EBVs, especially in structurally complex and underrepresented island ecosystems.

ecology↗

bioRxiv2023

Planting diversity begets multifaceted tree diversity in oil palm landscapes

Optimizing restoration outcomes is crucial for enhancing multifaceted diversity, resilience, and ecosystem functioning in monoculture-dominated landscapes globally. Here, we experimentally tested the performance of passive and active restoration strategies to recover taxonomic, phylogenetic, and functional diversity by establishing 52 tree islands in an oil palm landscape. Tree diversity via natural regeneration was shaped by local rather than landscape properties, with the diversity of planted tree species and tree island size driving higher multifaceted diversity. We show that large tree islands with higher initial planted diversity catalyze the recovery of multifaceted diversity at both the local and landscape level, including forest-associated species. Our results demonstrate that planted diversity begets regenerating diversity, overcoming major limitations of natural regeneration in highly modified landscapes. By elucidating the contribution of experimental, local, and landscape drivers to natural regeneration, these findings provide practical insights to make oil palm landscapes more biodiversity-friendly by enhancing functional and phylogenetic diversity within plantations.

ecology↗

bioRxiv2023

Scale-dependent landscape-biodiversity relationships shape multi-taxa diversity in an oil palm monoculture under restoration

Enhancing biodiversity in monoculture-dominated landscapes is a pressing restoration challenge. Tree islands can enhance biodiversity locally, but the role of scale-dependent processes on local biodiversity remains unclear. Using a multi-scale approach, we explored how scale-dependent processes influence the diversity of seven taxa (woody plants, understory arthropods, birds, herbaceous plants and soil bacteria, fauna, and fungi) within 52 experimental tree islands embedded in an oil palm landscape. We show that local, metacommunity (between islands), and landscape properties shaped above- and below-ground taxa diversity, with the stronger effects on above-ground taxa. The spatial extent that best-predicted diversity ranged from 150 m for woody plants to 700 m for understory arthropods with below-ground taxa responding at large spatial extents. Our results underscore the need for multi-scale approaches to restoration. Additionally, our findings contribute to understanding the complex processes shaping multi-taxa diversity and offer insights for targeted conservation and restoration strategies.

ecology↗

bioRxiv2022

Landscape heterogeneity and soil biota are central to multi-taxa diversity for landscape restoration

How to enhance biodiversity in monoculture-dominated landscapes is a key sustainability question that requires considering the spatial organization of ecological communities (beta diversity). Here, we experimentally tested if increasing landscape heterogeneity - through tree islands - is a suitable landscape restoration strategy when aiming to enhance multi-taxa diversity. We found that multi-taxa diversity resulted from islands fostering unique species (turnover: between 0.18 - 0.73) rather than species losses and gains (nestedness: between 0.03 - 0.34), suggesting that tree islands enhance diversity at the landscape scale. Through partial correlation networks, we revealed that landscape heterogeneity is associated with multi-taxa diversity (strength = 0.84). Soil biota were also central to the overall community by connecting beta diversity patterns across taxa. Our results show that increasing landscape heterogeneity enhances multi-taxa diversity in monoculture-dominant landscapes. Furthermore, we highlight that strategies aiming to enhance multi-taxa diversity should consider that spatial distributions of above- and below-ground communities are associated.

ecology↗