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Proceedings Reference Geothermal Enery Use, country update for Belgium, EGC2025
Geothermal energy is progressively gaining ground in Belgium, with tailored strategies emerging across its three Regions. Wallonia has undertaken a comprehensive modernization of its regulatory instruments, set ambitious renewable heat targets, and initiated large-scale subsurface exploration. Flanders is reinforcing its leadership in deep geothermal by targeting new geological formations, while improving shallow geothermal integration and subsurface governance. In the Brussels-Capital Region, efforts focus on incorporating shallow geothermal into urban energy planning through spatial zoning, technical potential mapping, and system monitoring. A suite of regional and European research projects (e.g. GEOCAMB, DESIGNATE, MORE-GEO, URGENT) have played a pivotal role in de-risking geothermal development by providing interdisciplinary tools that address geological complexity, economic feasibility, and environmental performance. Nevertheless, geothermal energy accounted for only 3.3% of Belgium’s renewable heat production in 2023, highlighting the need for accelerated deployment - especially in deep systems. Achieving carbon neutrality by 2050 will require stronger political commitment, harmonized regulatory frameworks, and targeted financial incentives. Ongoing pilot projects and scientific advances confirm geothermal energy's potential to become a cornerstone of Belgium’s sustainable heating transition.
Located in Library / RBINS Staff Publications 2025
Article Reference Glacial melt impacts carbon flows in an Antarctic benthic food web.
Most coastal glaciers on the West Antarctic Peninsula are in retreat. Glacial ice scouring and lithogenic particle runoff increase turbidity and shape soft sediment benthic communities. This, in turn, has the potential to induce a shift in these systems from an autotrophic to a heterotrophic state. In this study, we investigated the influence of glacial runoff on carbon flows in the softsediment food web of Potter Cove, a well-studied shallow fjord located in the northern region of the West Antarctic Peninsula. We constructed linear inverse food web models using a dataset that includes benthic carbon stocks as well as carbon production and respiration rates. The dataset offers detailed spatial information across three locations and seasonal variations spanning three seasons, reflecting different degrees of disturbance from glacial melt runoff. In these highly resolved food web models, we quantified the carbon flows from various resource compartments (phytoplankton detritus, macroalgae, microphytobenthos, sediment detritus) to consumers (ranging from prokaryotes to various functional groups in meio- and macrofauna). Locations and seasons characterized by high glacial melt runoff exhibited distinct patterns of carbon flow compared to those with low glacial melt runoff. This difference was primarily driven by a less pronounced benthic primary production pathway, an impaired microbial loop and a lower secondary production of the dominant bivalve Aequiyoldia eightsii and other infauna in the location close to the glacier. In contrast, the bivalve Laternula elliptica and meiofauna had the highest secondary production close to the glacier, where they are exposed to high glacial melt runoff. This study shows how the effects of glacial melt propagate from lower to higher trophic levels, thereby affecting the transfer of energy in the ecosystem.
Located in Library / RBINS Staff Publications 2024
Article Reference Godshuizenlaan 2, Bijlokesite: Goede tijden, slechte tijden. Een blik op de materiële cultuur van de 16de-eeuwse Bijloke-abdij
Located in Library / RBINS Staff Publications 2020
Article Reference Grâce-Hollogne/Horion-Hozémont : les aiguisoirs et polissoirs du site de la rue de Fontaine.
Located in Library / RBINS Staff Publications 2023
Article Reference Grandes lames en roches alpines (et quelques autres) trouvées dans le Benelux : Synthèse des analyses spectroradiométriques
Located in Library / RBINS Staff Publications
Article Reference Growth and reproduction of the shrimp population in a lagoon system in southern Benin (West Africa)
Located in Library / RBINS Staff Publications 2024
Article Reference Haplotaxis gordioides (Hartmann in Oken, 1819) (Annelida, Clitellata) as a subcosmopolitan species: a commonly held view challenged by DNA barcoding
Located in Library / RBINS Staff Publications 2023 OA
Article Reference Harnessing the power of machine and deep learning for transferring joint species distribution models considering the structure of biotic interactions
The transferability of single or joint species distribution models ((j)SDMs) depends on their ability to predict beyond the observed environmental range and to remain consistent despite shifts in biotic interactions. Transfer accuracy may be improved by recent advances in the application of deep learning that provide greater flexibility and potentially superior predictive accu- racy than traditional approaches. We implemented jSDMs with deep and machine learning algorithms and measured the transfer accuracy from continental to regional areas in communities with different species composition. We ran jSDMs with deep neural networks (DNN), elastic net (EN), and stacked SDMs (sSDM) with random forests (RF). We used 134 689 occurrence records representing 1776 species of six taxonomic groups (beetles, birds, bryophytes, fungi, lichens and plants) from 2387 forest plots in Europe. We employed an agnostic modelling approach that covered most of the environmental con- ditions by including more than 100 satellite-derived variables and 98 climatic variables. The predictive power of the models within the training continental area was evaluated using AUC, whereas the transfer accuracy in the regional area was evalu- ated with the Boyce index calculated with independent presence records. We found that the DNN–jSDMs outperformed other models at continental scale, but model transfer from continental to regional extent was less accurate. We found that the accuracy of regional predictions was higher for taxonomic groups with better representation in the continental data, such as birds, bryophytes and plants. Depending on the algorithm and the taxonomic group, we achieved acceptable (Boyce > 0) to accurate (Boyce > 0.5) transferability for 32–78% of the species. Our findings underscored the need of considering trade-offs among hyperparameter tuning, spatial scales and model complexity. Our findings also suggest that the varying biotic interac- tion structures and, particularly, the different species compositions of the transfer areas, may affect model transferability more than previously considered.
Located in Library / RBINS Staff Publications 2026 OA
Article Reference Hastula strigilata revisited: Part IV. Description of a cryptic new species from Sulawesi (Gastropoda: Conoidea: Terebridae)
Located in Library / RBINS Staff Publications 2023
Article Reference Hastula strigilata revisited: Part III. Description of two new species from Australia and the Hawaiian Islands (Gastropoda: Conoidea: Terebridae)
Two morphospecies that remained undescribed in a previous study are described as new from Australia and the Hawaiian Islands, respectively and facilitated by the availability of recently acquired additional material.
Located in Library / RBINS Staff Publications 2024