Abteilung Aquatische Ökologie

Early-career researchers (ECRs) play a vital role in advancing macrophyte research, bringing fresh perspectives, collaborative skills, and innovative methods to the field. Across marine and freshwater realms, macrophytes function as ecosystem engineers and key indicators of ecosystem health, yet they are declining due to a plethora of threats. As those who will shape the future of the field, ECRs are well-positioned to identify existing knowledge gaps and future priorities for the field in macrophyte research in a creative, integrative, and sustainable manner (both for the ecosystems and the ECRs themselves). Here, we present a unified perspective informed by the results of an international survey of 147 ECRs, capturing how ECRs see the field of macrophyte research at present and envision its future, including priorities for the field and how to overcome systemic barriers that ECRs face. Across realms and regions, ECRs currently use classical methods (e.g., field work, statistics) to study a wide range of topics including biodiversity, biotic interactions, and anthropogenic impacts. Regardless of research topic, ECRs are aware that technological advances are reshaping how research is conducted but acknowledge that they are not a silver bullet. Such advances should be harnessed to complement classical approaches, particularly taxonomy and field work. However, ECRs face structural barriers, including job insecurity and funding constraints, that disproportionately impact researchers in resource-limited regions within an already underrepresented field. Addressing these barriers and strengthening science-society connections is essential for the field’s future, and requires collaborative, interdisciplinary, and innovative research grounded in a strong ecological foundation.

Species distribution models (SDMs) are central tools for predicting and forecasting how species respond to environmental changes, yet their reliability depends on accurately capturing ecological processes across spatial scales while accounting for uneven data availability and resolution. Models calibrated over spatially restricted extents are often prone to truncating species' niches, whereas broad-scale models typically rely on coarse datasets that overlook fine-scale habitat constraints. The spatially nested SDM (N-SDM) approach addresses this challenge by combining global- and regional-level models to couple large-scale drivers with detailed, high-resolution environmental data. Here, we present N-SDM 2.0, a reengineered and extended successor to the original N-SDM software – the first end-to-end high-performance computing platform for spatially nested species distribution modelling. The new version offers improved usability and modularity, along with an extended range of modelling features, while maintaining continuity for users of the previous release. New modelling features include additional nesting methods, background-point generation strategies, and cross-validation options. These developments are complemented by an improved workflow architecture, a refined settings system, streamlined data-preparation steps, and greater control over data usage across spatial levels as well as error handling. N-SDM 2.0 is designed for flexible integration into heterogeneous high-performance computing environments, supporting large-extent and high-resolution biodiversity forecasting across an extensive number of species and projection scenarios. Beyond pure technical advances, N-SDM 2.0 strengthens the conceptual foundation of spatially nested species distribution modelling, introducing new features that form an open and scalable framework for mapping species distributions and robustly projecting their responses to global environmental changes.

Translational participatory research for environmental management occupies a demanding space at the interface of societal needs and academic research. Projects in this space usually face the challenge of reconciling stakeholder involvement and real-world applicability with academic career requirements such as excellence in fundamental research and the attraction of substantial research funds. Here, we share our experiences from a 12-year translational participatory research initiative on the management of invasive gobies in central Europe. We describe the project, synthesize inputs, outputs, and outcomes, and summarize conditions and practices across political, administrative, societal, institutional, team, and individual levels that we found important and beneficial in our attempts to produce both academic and applied outcomes. Our impression is that an interaction of factors across these levels created windows of opportunity, and that the team constellation and setting allowed us to seize these opportunities for the sake of both scientific progress and societal impact. By reflecting from the perspective of a multidisciplinary group of natural scientists directly engaged in such a project, we aim to contribute a personal account to social science frameworks on translational, participatory, inter- and transdisciplinary research. Our retrospective potentially can inform policy makers, funders, and institutions who seek to create enabling environments for interface research, and is helpful to fellow natural scientists who want to prepare the ground for their own translational participatory research initiatives.