Swiss Federal Institute of Aquatic Science and Technology

Species distribution models (SDMs) relate species observations to mapped environmental variables to estimate the realized niche of species and predict their distribution. SDMs are key tools for projecting the impact of climate change on species and have been used in many biodiversity assessments. However, when fitted within spatial extents that do not encompass the whole species range (i.e. subrange), the estimated realized environmental niche can be truncated, which can lead to wrong or inaccurate predictions. A simple solution to this niche truncation consists in fitting SDMs at a spatial extent that encompasses the whole species range, but this often implies using a spatial resolution too coarse for local conservation assessments. To keep a fine resolution, a solution is to fit spatially nested SDMs (N‐SDMs), where a whole range, coarse‐grain SDM is combined with a subrange, fine‐grain SDM. N‐SDMs have demonstrated superior performance to subrange (truncated) SDMs in projecting species distributions under climate change and have accordingly regained considerable interest. Here, we review developments, applications and effectiveness of N‐SDMs. We present and discuss existing methods and tools to fit N‐SDMs, and assess when N‐SDMs are not needed. We highlight strengths and weaknesses of N‐SDMs, underline their importance in reducing niche truncation, and identify remaining challenges and future perspectives. Our review highlights that subrange SDMs most often lead to niche truncation and thus to incorrect spatial projections, a problem that can be overcome by using N‐SDMs. We show that the various N‐SDM methods come with their strengths and weaknesses and should be selected depending on the intended goal of the study. Synthesis. N‐SDMs are key tools to develop untruncated regional climate change forecasts of species distributions at fine resolution over restricted extent. While several N‐SDM approaches were proposed, there is currently no universal solution suggesting that further developments and testing are crucial if we are to derive robust future projections of species distributions, at least until SDMs can be applied for most species at high resolution over large geographic extents.

Urban temperatures are rising, and urban trees can help mitigate the consequences of heat stress. However, the influence of water availability on the evaporative cooling efficiency of trees across diverse urban settings remains insufficiently understood. We modelled how varying soil moisture, built environment and tree amounts affect human thermal comfort. Our results show that increasing tree cover and maintaining high soil moisture through irrigation can generate areas of ‘no thermal stress’ in Zurich during an average summer day, primarily via direct soil evaporation and in less dense Local Climate Zones. In denser built environments and without enough soil moisture, achieving such thermal comfort proved more challenging. On extreme summer days, however, even extensive tree planting and full irrigation were insufficient to alleviate heat stress, indicating the need for additional adaptation strategies. Our study underscores the critical but limited role of tree planting and water management in mitigating urban heat, offering practical recommendations for green infrastructure managers.

Social partners frequently resemble each other. These correlations between the phenotypes of interacting individuals (e.g. social partners, group members, etc.) can be caused by multiple processes. These processes include joint plasticity in response to shared environments, plasticity in response to partner phenotype, and genetic similarity arising from non-random assortment due to clustered relatives, spatiotemporal stratification, and partner choice. Although social plasticity and non-random assortment can influence evolutionary dynamics, these two processes have most often been studied separately and disentangling the causes of partner resemblance in observational datasets can be challenging. Furthermore, standard statistical models of social plasticity do not allow for potential social feedback between partners’ phenotypes and estimating joint plasticity to shared environmental effects requires environmental data that is rarely available. In this study, we investigated the performance of various statistical models to estimate non-random assortment and social plasticity in observational datasets. We simulated data for a socially monogamous species in which non-random mating, social plasticity (with or without feedback) and joint plastic responses to unknown environmental factors occurred alone or simultaneously. Commonly used ‘variance-partitioning approaches’ retrieved biased estimates except when the process they aimed to estimate occurred on its own. By contrast, a recently proposed statistical model explicitly including social plasticity as a dynamic process generating feedback between partners’ phenotypes (the so-called social animal model) performed best even in scenarios with multiple co-occurring processes. While we recommend empiricists use this latter approach, we also highlight the importance of appropriate sampling designs given the study question and system, and using simulations to assess model performance in realistic scenarios.

Large‐scale biodiversity assessments and conservation applications require integrated and up‐to‐date datasets across regions. In the oceans, monitoring is fragmented, which affects knowledge exchange and usage. Among existing monitoring programs, scientific bottom‐trawl surveys (SBTS) are long‐term, rich, and well‐maintained data sources at the scale of each sampled region, but these data are under‐utilized in biodiversity applications, especially across regions. This is hampered by the lack of an international community and database maintained through time. To address this, we created FISHGLOB, an infrastructure gathering SBTS and experts. In 5 years, we developed an integrated database of SBTS and a consortium gathering more than 100 experts and users. Here, we are sharing the project history, achievements, challenges, and outlooks. In particular, we reflect on the infrastructure‐building social and technical processes which will guide the development of similar infrastructures. The FISHGLOB project takes ocean monitoring one step forward in working as a unified community across disciplines and regions of the world.

The rate of technological innovation within aquatic sciences outpaces the collective ability of individual scientists within the field to make appropriate use of those technologies. The process of in situ lake sampling remains the primary choice to comprehensively understand an aquatic ecosystem at local scales; however, the impact of climate change on lakes necessitates the rapid advancement of understanding and the incorporation of lakes on both landscape and global scales. Three fields driving innovation within winter limnology that we address here are autonomous real‐time in situ monitoring, remote sensing, and modeling. The recent progress in low‐power in situ sensing and data telemetry allows continuous tracing of under‐ice processes in selected lakes as well as the development of global lake observational networks. Remote sensing offers consistent monitoring of numerous systems, allowing limnologists to ask certain questions across large scales. Models are advancing and historically come in different types (process‐based or statistical data‐driven), with the recent technological advancements and integration of machine learning and hybrid process‐based/statistical models. Lake ice modeling enhances our understanding of lake dynamics and allows for projections under future climate warming scenarios. To encourage the merging of technological innovation within limnological research of the less‐studied winter period, we have accumulated both essential details on the history and uses of contemporary sampling, remote sensing, and modeling techniques. We crafted 100 questions in the field of winter limnology that aim to facilitate the cross‐pollination of intensive and extensive modes of study to broaden knowledge of the winter period.

The Arctic is warming several times faster than the rest of the globe. Such Arctic amplification rapidly changes hydrometeorological conditions with consequences for the structuring of cold-adapted terrestrial and aquatic ecosystems. Arctic ecosystems, which have a relatively small buffering capacity, are particularly susceptible to hydrometeorological regime shifts thus frequently undergo system-scale transitions. Abrupt ecosystem changes are often triggered by disturbances and extreme events that shift the ecosystem state beyond its buffering threshold capacity thus irreversibly changing its functioning (ecosystem tipping). The tipping depends on spatial and temporal scales. At the local scale, feedback between soil organic matter and soil physics could lead to multiple steady states and a tipping from high to low soil carbon storages. On the continental scale, local tipping is smoothed and the changes are rather gradual (no clear tipping threshold). However, due to the centennial timescale of soil carbon and vegetation dynamics, Arctic ecosystems are not in equilibrium with the changing climate, so a tipping could occur at a later time. Earth Observation (EO) is useful for monitoring ongoing changes in permafrost and freshwater systems, in particular extreme events and disturbances, as indicators of a possible tipping point. Lake change observations support gradual rather than abrupt transitions in different permafrost regions until a hydrological tipping point where lake areas start to decline leading to regional drying. Due to floodplain abundance, floodplains should be considered separately when using satellite-derived water extent records to analyse potential tipping behaviour associated with lakes. Reduction in surface water extent, increasing autocorrelation of water level of larger lakes and the impact of extreme events on ground ice can all be observed with satellite data across the Arctic. The analysis of Earth System simulations suggests significant impacts of changes in permafrost hydrology on hydroclimate in the tropics and subtropics, but there is no clear threshold in global temperature for these shifts in hydroclimate.

Phage-based biocontrol has shown notable advantages in protecting plants against pathogenic bacteria in agricultural settings compared to chemical-based bactericides. However, the efficiency and scope of phage biocontrol of pathogenic bacteria are limited by the intrinsic properties of phages. Here, we investigated pathogen biofilm eradication in the phyllosphere using the phoresy system of hitchhiking phages onto carrier biocontrol bacteria. The phoresy system efficiently removed the pathogen biofilm in the soybean phyllosphere, reducing the total biomass by 58% and phytopathogens by 82% compared to the untreated control. Biofilm eradication tests demonstrated a significant combined beneficial effect (Bliss independence model, CI < 1) as phages improved carrier bacteria colonization by 1.2-fold and carrier bacteria facilitated phage infection by 1.4-fold. Transcriptomic analysis showed that phoresy significantly enhanced motility (e.g., fliC and pilD genes) and energy metabolism (e.g., pgm and pgk genes) of carrier bacteria and suppressed the defense system (e.g., MSH3 and FLS2 genes) and energy metabolism (e.g., petB and petC genes) of pathogens. Metabolomics analysis revealed that the phoresy system stimulated the secretion of beneficial metabolites (e.g., flavonoid and tropane alkaloid) that could enhance stress response and phyllosphere protection in soybeans. Overall, the phoresy of phages hitchhiking on biocontrol bacteria offers a novel and effective strategy for phyllosphere microbiome manipulation and bacterial disease control.

Adaptive radiations, where a lineage diversifies into multiple species exploiting different niches, are key drivers of biodiversity. It is therefore important to understand the factors that drive such radiations and how changing environmental conditions affect their persistence. Using a size‐structured model, I study how changing environmental conditions impact the persistence of a six‐species flock. At birth, individuals are constrained to feed on a shared resource. As they mature, individuals diversify into six specialized forms, each adapted to feed on specific resources. Environmental changes affecting one species can trigger a cascade, altering the size structure of the focal species and subsequently affecting resource availability for other species. Under these altered ecological conditions, coexistence of all species becomes impossible. Importantly, once species are lost, they cannot re‐establish even when environmental conditions return to their original state, resulting in irreversible biodiversity loss. These findings underscore the vulnerability of species flocks to environmental change and highlight the potential for unexpected outcomes in the face of shifting ecological conditions due to climate change.

The comprehensive evaluation of pollutant abatement during chemical oxidation processes and identification of potentially hazardous transformation products are a fundamental challenge in water and wastewater treatment. Here, we demonstrate how high-throughput computational chemistry enables the elucidation of reaction pathways via automated, quantum-chemistry-based chemical reaction network (CRN) explorations. We evaluated the predictive capabilities of this computational approach using the Software for Chemical Interaction Networks (SCINE) for studying the reactions of ozone with two olefins, ethene and tetramethylethene, in aqueous solution. Following a benchmarking of the quantum chemical methodology for structure optimization and energy calculations, we generated CRNs containing hundreds of compounds and thousands of reactions, identified reaction mechanisms, and evaluated product formation kinetics through microkinetic modeling. These CRN explorations led to the correct reproduction of experimental evidence for mechanisms and products of olefin ozonolysis for reactions of ozone and ethene based solely on defining the reactants and their initial concentrations. The study of reactions of ozone and tetramethylethene also matched experimental data for the main products but revealed consequences of limited exploration depth and shortcomings of the implicit solvation model. We envision that CRN explorations not only offer novel means for predicting pollutant transformation pathways but will also support chemical analysis and the assessment of effects on human and environmental health.

Identifying flood‐inducing processes remains a challenge in catchment hydrology due to the complex runoff dynamics, particularly in semi‐arid regions where surface and subsurface mechanisms alternatively drive streamflow across seasons. Tracer data can help identify hydrograph sources, but they are often unavailable or lack sufficient temporal resolution. To aid process identification at the event‐scale, we developed an integrated hydrological‐hydrodynamic framework and compared multiple model hypotheses informed by hydrological signatures. We systematically tested these hypotheses through falsification, meta‐evaluation, spatial validation, and posterior diagnostics, using the semi‐arid Salsola nested catchment in southern Italy as case study. While all model structures performed well on common calibration metrics, differences emerged in spatial transferability tests and alternative diagnostic assessments. Some models, despite strong performance, exhibited inconsistent representations of internal runoff mechanisms, indicating that they achieved good results for the wrong reasons. Furthermore, the choice of routing schemes significantly influenced high‐peak estimations and overall model performance, particularly when Horton‐type overland flow was considered. This underscores the need to treat routing methods as a key component in event‐scale modeling. Our findings reveal that during consecutive storm events in the study catchment, surface processes dominate the initial stages, whereas subsurface processes become more influential in later events, providing valuable insights that may be applicable to similar semi‐arid regions. Overall, we emphasize the importance of hypothesis testing in runoff process identification, which can compensate for the absence of hydrochemical data for hydrograph separation. Additionally, our results highlight the value of a landscape‐based modeling approach for distinguishing alternative runoff generation processes.

Today, few watersheds remain untouched by global change processes arising from climate warming, impoundments, channelization, water extraction, pollution, and urbanization. The need for restoration has resulted in a myriad of interventions, generally performed at small scales, which have limited measurable impact in restoring biodiversity and ecosystem functions. We propose bringing nature‐based restoration (also referred to as rewilding) principles to rivers and their watersheds to allow freshwater ecosystems to heal themselves and present a case study example for the Wolastoq, a transboundary watershed on North America's east coast. We aimed to identify key areas for the provision of the ecosystem function secondary productivity in the watershed and explored how the existing network of protected lands contributes to its conservation. We first developed species distribution models for 94 aquatic insects and 5 aerial insectivores and then considered human footprint and existing protected areas when employing spatial prioritization to meet 2 area‐based targets (17% and 30% [i.e., Aichi Biodiversity Target 11 and Canada's 30×30, respectively]) for conservation or restoration of freshwater secondary production. Current conservation protection in the watershed was predicted to be insufficient to protect either ecosystem function providers or receivers of secondary production. By considering integrated conservation strategies, restoration and conservation actions can be better allocated throughout habitat patches to ensure sustained provision of ecosystem functions across the watershed. Nature‐based restoration and conservation can help inform Canada's area‐based targets, providing a framework for incorporating ecosystem functions into conservation planning and offering practical insights for policy and restoration efforts aimed at safeguarding biodiversity.

A critical understanding of how pests interact with active ingredients is essential for the development of new insect control solutions to maintain crop quality and quantity by reducing insect damage. Absorption of insecticides into insect bodies of targeted pest species is the first critical step that confounds the efficacy of insecticides. This study investigated how different feeding behaviour of two pests, Myzus persicae and Spodoptera littoralis, affects the absorption, metabolism, and excretion (AME) of seven insecticidally inactive test compounds. A feeding contact assay for the chewing pest (Lepidopteran larvae) and an oral ingestion assay for the sucking pest (aphids) was used to investigate the AME of test compounds with agrochemical-like structural motifs. The standardized assays comprised of an exposure period with treated diet and a subsequent depuration period with untreated diet. The results showed that S. littoralis larvae differed from M. persicae in their compound quantities absorbed into the insect body and in their excretion products at the end of the exposure or depuration periods. We suggest that this is caused by their different ingestion types and rates resulting in different absorption and excretion quantities. Further, we found differences in the metabolism (timing and biotransformation pathways) of compounds between both species. Notably, certain compounds remained detectable in both pests after the depuration period, suggesting compound and species-specific metabolism and excretion. Our results highlight the complex interplay between feeding biology of insects, in particular the critical role of excretion products, and the exposure to different compounds that lead to species-specific AME.

Polyploidisation is an important evolutionary force. It drives sympatric speciation through reproductive isolation of different cytotypes, and often leads to loss of sexual reproduction in polyploid lineages. Polyploidisation and asexuality can change how other species engage in ecological interactions with the polyploid lineage and may change coevolutionary dynamics. Here, we quantified the phenotypic divergence in the freshwater oligochaete worm Lumbriculus variegatus, the California blackworm, among its co-occurring sexual diploid (Lineage II) and asexual polyploid (Lineage I) lineages. We further investigated variation in parasite communities and infection prevalence among sympatric and allopatric diploid/polyploid populations. Ten out of 18 populations showed co-existence of both lineages, with 7 populations harbouring only the polyploid lineage. Both worm lineages hosted endoparasitic nematodes, an ectoparasitic rotifer, and one potentially symbiotic gut ciliate. The parasite community similarity and overlapping size range of diploid and polyploid worms points to the ecological similarity of the worm lineages, despite the substantial ploidy and reproductive strategy differentiation. Although parasite prevalence varied independently of worm lineage, prevalence was associated with frequency of local cytotypes. Specifically, the rotifer prevalence was highest on the rare local cytotype, and nematode prevalence was highest on the common local cytotype. These results suggest the presence of both positive and negative frequency dependent parasitism, which may contribute to the co-existence in the L. variegatus species complex.

The Indian Ocean plays a crucial role in water cycle dynamics around the Indian Ocean Basin, yet the relationships between the Indian Walker Circulation (IWC) and hydroclimate variability remain poorly understood. We examine the IWC‐hydroclimate linkages throughout the Indian Ocean Basin during two study periods (instrumental era and the last millennium), using the ECHAM5‐wiso, iCESM‐iLME, and ERA5 global data products. We leverage the stable isotopic composition of precipitation (δ $\delta$¹⁸OP) as an integrative water cycle tracer to elucidate the link between large‐scale atmospheric processes and regional hydroclimate characteristics. We find a strong statistical relationship between the East African short rain δ $\delta$¹⁸OP and IWC in Eastern Africa and Horn of Africa. In Indonesia, the relationship is weaker due to the strong influence of the Pacific Walker Circulation (PWC). These patterns arise over multiple time scales and are consistent with the strong tie between the IWC and precipitation variability during the short rain season in Eastern Africa and Horn of Africa that had previously been reported in the instrumental era but not yet for the last millennium. We document strong fluctuations in the strength of the IWC during the last millennium, with periods of stronger or weaker interactions with the PWC that influenced δ $\delta$¹⁸OP variability. Finally, our study underscores the ability of δ $\delta$¹⁸OP to capture major atmospheric circulation signals, demonstrating its potential to examine the impact of interacting Walker Circulations on regional hydroclimate even during periods of low precipitation.

Monkeypox virus (MPXV) is a zoonotic pathogen that has recently caused outbreaks in non-endemic areas. Wastewater-based surveillance (WBS) offers substantial potential for monitoring MPVX clades, and it can inform population-level disease dynamics. Here, we report a four-plex digital PCR assay to detect and quantify different clades and subclades of MPXV. The assay demonstrated specificity in distinguishing and quantifying MPXV by clade, which is advantageous for application in both clinical and wastewater settings.

Plain Language Summary Making decisions on how to develop mountain regions while protecting and preserving their nature and inhabitants requires collaborations amongst many different people. Yet every person thinks of a mountain, its nature, and its people in her own way based, for instance, on professional or personal experience. These different representations are all valid but because they differ, reaching a shared understanding and making consensual decisions is difficult. Here we develop a model that describes elements of nature and society in mountains as well as their interconnections. It is conceived to guide individuals in formulating their own representations based on a defined set of attributes and help groups of people achieve a shared representation. This representation can then serve as the basis for decision‐making processes. Developing such a model in mountain regions specifically is important as they exhibit many characteristics, such as their steepness and remoteness, that make them uniquely different from other places on Earth and particularly important to manage effectively.

While measured streamflow is commonly used for hydrological model evaluation and calibration, an increasing amount of data on additional hydrological variables is available. These data have the potential to improve process consistency in hydrological modeling and consequently for predictions under change, as well as in data‐scarce or ungauged regions. Here, we show how these hydrological data beyond streamflow are currently used for model evaluation and calibration. We consider storage and flux variables, namely snow, soil moisture, groundwater level, terrestrial water storage, evapotranspiration, and altimetric water level. We aim at summarizing the state‐of‐the‐art and providing guidance for the use of additional hydrological variables for model evaluation and calibration. Based on a review of the current literature, we summarize observation methods and uncertainties of currently available data sets, challenges regarding their implementation, and benefits for model consistency. The focus is on catchment modeling studies with study areas ranging from a few km ² to ~500,000 km ² . We discuss challenges for implementing alternative variables that are related to differences in the spatio‐temporal resolution of observations and models, as well as to variable‐specific features, for example, discrepancy between observed and simulated variables. We further discuss advancements required to deal with uncertainties of the hydrological data and to integrate multiple, potentially inconsistent datasets. The increased model consistency and improvement shown by most reviewed studies regarding the additional variables often come at the cost of a slight decrease in streamflow model performance.