SystemsX.ch

Microbial communities and their functionality are affected by climate change, which consequently impacts the functionality of soil biogeochemical cycles and in turn the persistence of individual tree species. Despite their importance for forest ecosystems, few studies have investigated the impacts of multiple, concurrent elements of climate change on microbial communities under tree species with contrasting drought tolerance and different biogeographic origins.In our study, we investigated how soil microbial communities of different native and non-native tree species responded to warming and warming associated with drought. The experiment was located in Switzerland and included three forest sites with different climatic and environmental characteristics where temperature and precipitation have been manipulated since 2022. Soil microbial communities were assessed using DNA metabarcoding, and extracellular enzyme activities were assessed alongside environmental variables and soil nutrient availability.Preliminary results showed that strong differences across sites shape microbial community composition and modulate their responses to the experimental climate treatments. The strongest effects of climate manipulations were found at the warmest and driest site. Soil microbial community composition responses to the different climate change treatments further among the tree species. In addition to microbial community composition, microbial functioning, as assessed via enzymatic activities, also differed across sites and generally decreased with the climate treatments, suggesting that biogeochemical cycles are likely to change in the future.Our research aimed to clarify the possible consequences of warming and drought on forest microbiomes and consequently soil biogeochemical cycles under global change. This will support the development of climate change mitigation strategies to maintain forest ecosystem functionality and to choose future tree species able to resist climatic stresses.

Similar to human settlements, soil bacteria are distributed into numerous cell clusters whose sizes encode their function and environmental context. We show that bacterial cell cluster size distributions follow log-normal patterns, predicted by proportionate growth (Gibrat’s law). This log-normal distribution of cell cluster sizes is robust across biomes spanning a wide range of resource availabilities. Importantly, we show how characteristic cluster sizes vary with soil carrying capacity and transport limitations. In soils with high bulk cell density, cell cluster size distribution gives rise to rare but disproportionately large, ‘mega’ communities, that, in turn, disproportionately drive metabolism leading to anoxic microsites in largely oxic soils. A cursory evaluation of the statistical features of soil bacterial microgeography suggests that standard bulk soil sampling conflates many small, endemic clusters with a few dominant mega clusters. Consequently, accurate assessment of diversity and composition requires “unmixing” of genetic information across the likely original distributions and bacterial cluster size spectrum. We outline an analytical and modeling framework that translates soil carrying capacity into expected community size heterogeneity based on the observed cell cluster size distributions with heavy tails. We combine global soil and microbiome data sets to model putative community size structures across different ecosystems. Our approach reframes soil microbiomes as size-structured meta-communities and provides testable predictions for diversity-function relationships under changing moisture and carbon regimes.

Xolography is a novel linear volumetric manufacturing technique that offers unparalleled precision and speed. Yet, its application to bioprinting remains limited due to insufficient understanding of biocompatibility constraints. Here, this work establishes fundamental design principles for cell‐compatible Xolography bioinks by dissecting the effects of extracellular pH, osmolality, and lysosomotropic stress on cell viability and function. By systematically studying the tolerances for these parameters, this work defines a framework for bioink formulations that enables fast, support‐free fabrication of complex designs with maintained cell viability and function as validated in different murine and human cell lines, primary human cells and induced pluripotent stem cell (iPSC)‐derived cells. These results show that, unlike triethanolamine, BisTris indeed can function as a fully biocompatible co‐initiator enabling cell viability beyond 90% as well as uncompromised metabolic activity and differentiation performance when used in a tightly controlled formulation, contrasting previous reports. This work showcases the biomedical potential of the formulation by achieving fibroblast‐driven extracellular matrix (ECM) formation, endothelial sprouting from pre‐vascularized spheroids, and maintenance of an iPSC‐derived hepatocyte differentiation phenotype within Xolography‐printed constructs. These advancements transform Xolography into a powerful and foremost reliable bioprinting platform for fabrication of complex, cell‐laden structures for versatile applications in tissue engineering, organ‐on‐a‐chip models, and regenerative medicine.

Dynamic locomotion of legged robots is a critical yet challenging topic in expanding the operational range of mobile robots. It requires precise planning when possible footholds are sparse, robustness against uncertainties and disturbances, and generalizability across diverse terrains. Although traditional model-based controllers excel at planning on complex terrains, they struggle with real-world uncertainties. Learning-based controllers offer robustness to such uncertainties but often lack precision on terrains with sparse steppable areas. Hybrid methods achieve enhanced robustness on sparse terrains by combining both methods but are computationally demanding and constrained by the inherent limitations of model-based planners. To achieve generalized legged locomotion on diverse terrains while preserving the robustness of learning-based controllers, this paper proposes an attention-based map encoding conditioned on robot proprioception, which is trained as part of the controller using reinforcement learning. We show that the network learns to focus on steppable areas for future footholds when the robot dynamically navigates diverse and challenging terrains. We synthesized behaviors that exhibited robustness against uncertainties while enabling precise and agile traversal of sparse terrains. In addition, our method offers a way to interpret the topographical perception of a neural network. We have trained two controllers for a 12-degrees-of-freedom quadrupedal robot and a 23-degrees-of-freedom humanoid robot and tested the resulting controllers in the real world under various challenging indoor and outdoor scenarios, including ones unseen during training.

In this paper, survey evidence is used to examine the food security impacts of the 2022 Russian invasion of Ukraine. We focus on both residents of Ukraine and those fleeing to one of the wealthiest countries in Europe, Switzerland. Our questionnaire was sent to both Ukrainian residents and migrants to Switzerland between October 2022 and February 2023. 80% of respondents (n = 1267) indicated that they faced some form of food insecurity, most commonly an inability to eat balanced meals and/or running out of food without being able to buy more. Yet the incidence of more severe forms of food insecurity, including cutting and skipping meals for multiple months, eating less than needed, and feeling hungry without eating, affected more than 20% of the surveyed populations in both countries. Food insecurity for both residents of Ukraine and refugees in Switzerland is significantly more severe for households who perceive themselves to have below average income. In Ukraine higher food insecurity is identified in the conflict’s frontline regions and among larger households with less domestic food production. In Switzerland, women report lower access to many coping mechanisms (producing, trading, or borrowing food). This study underscores the urgent need for improved food programs in conflict zones as well as countries that host refugees, particularly where domestic food prices are very high and language barriers reduce income opportunities.

Abstract. We still lack substantial understanding on how landscape characteristics shape the storage and release of water at the catchment scale. Here we use 13 years of fortnightly precipitation and streamflow δ18O measurements together with hydrometeorological data from 12 nested catchments (0.5 to 247.5 km2) in the Alzette River basin (Luxembourg) to study bedrock geology and landcover controls on streamflow generation. Streamflow responses to precipitation were highly variable. Runoff coefficients were typically higher in catchments dominated by less permeable bedrock (i.e. marls and claystones, Rc = 0.43 to 0.52) than in catchments with a high fraction of permeable bedrock (i.e. sandstones and conglomerates, Rc = 0.19 to 0.40). The fraction of new water (Fnew, water younger than ~16 days in this study) determined via ensemble hydrograph separation was strongly related to differences in bedrock geology. Fnew was highest in impermeable bedrock catchments (i.e. with a dominance of marls and claystone, Fnew = 4.5 to 11.9 %), increasing with higher specific daily streamflow (Fnew up to 45 % in one catchment). In catchments with an important fraction of permeable sandstone and conglomerates, high Fnew variability with specific streamflow (Fnew rising to 25 % in one catchment) was also found, despite a damped and delayed hydrograph response to precipitation and low Fnew (means of 1.3 to 2.7 %). In the weathered bedrock catchments (i.e. dominated by schists and quartzites), rapid infiltration led to large fractions of water that was older than 12 weeks (~80 %) and very small fractions of water younger than two weeks (~3.5 %). Fnew variability with streamflow was near zero, contrasting with the rapid response of the hydrograph to precipitation events. At high specific streamflow, Fnew was also correlated with bedrock geology and certain land use types. The extensive data set of streamflow δ18O enabled us to link water storage and release to bedrock geology. Such information is key for a better anticipation of water storage and release functions under changing climate conditions, i.e. long dry spells and high-intensity precipitation events.

The bull shark (Carcharhinus leucas) is an apex predator with a wide distribution in tropical and warm temperate waters. This species is known to utilise freshwater systems and estuaries as nursery grounds. During a wider bull shark tagging survey in the Rewa River, Fiji, in 2017 and 2018, 27 neonate bull sharks with red eye pupils were recorded. This opportunistic observation prompted an examination of water quality parameters in the Rewa River to collect preliminary data on the potential cause of pollution. Water samples were analysed for faecal indicator bacteria (Escherichia coli), ammonia, total nitrogen, and various metals. Results indicated high levels of E. coli contamination, as well as elevated ammonia and total nitrogen concentrations. However, due to the limited sample size and the likelihood of additional underlying causes, a definitive causal relationship could not be established. Hence, this finding stands as an opportunistic observation, detailed here for documentation and stimulation of discourse.

Recent methodological advancements in determining the nonexchangeable hydrogen isotopic composition (δ2 Hne ) of plant carbohydrates make it possible to disentangle the drivers of hydrogen isotope (2 H) fractionation processes in plants. Here, we investigated the influence of phylogeny on the δ2 Hne of twig xylem cellulose and xylem water, as well as leaf sugars and leaf water, across 73 Northern Hemisphere tree and shrub species growing in a common garden. 2 H fractionation in plant carbohydrates followed distinct phylogenetic patterns, with phylogeny reflected more in the δ2 Hne of leaf sugars than in that of twig xylem cellulose. Phylogeny had no detectable influence on the δ2 Hne of twig or leaf water, showing that biochemistry, not isotopic differences in plant water, caused the observed phylogenetic pattern in carbohydrates. Angiosperms were more 2 H-enriched than gymnosperms, but substantial δ2 Hne variations also occurred at the order, family, and species levels within both clades. Differences in the strength of the phylogenetic signals in δ2 Hne of leaf sugars and twig xylem cellulose suggest that the original phylogenetic signal of autotrophic processes was altered by subsequent species-specific metabolism. Our results will help improve 2 H fractionation models for plant carbohydrates and have important consequences for dendrochronological and ecophysiological studies.

Abstract To fulfil fisheries management objectives that often include implementing the precautionary and ecosystem‐based approaches, multispecies fisheries data need to be analysed. Amongst the different methods dealing with these multidimensional data, self‐organizing maps (SOMs) remain rarely used, although they are highly flexible in data input and offer visualization possibilities particularly suited to summarize complex datasets. Here, we propose to combine SOMs with a clustering approach to break down data complexity and produce simple geographic maps showing catch hotspots, which can indicate sensitive zones in terms of fishery management. To promote this approach, we tested it first on simulated datasets and then on the open‐access ICCAT commercial catch database of the tropical tuna fisheries of the Atlantic Ocean. We aimed to detect drifting fish aggregating devices (dFADs) catch hotspots of juveniles of two tuna species, bigeye and yellowfin tunas and of the silky shark, a commonly bycaught vulnerable shark species, in tropical tuna purse seine fisheries. Simulations on datasets increasing in complexity (in number, geographic and duration extent of the hotspots and number of species in the analysis) informed us about the method's sensitivity and limits. Our findings showed that, in the context of multi‐specific fisheries, the detection of the hotspot is dependent on a certain level of catch within the hotspot and that adding species to the analysis tended to mask small and short‐duration hotspots. Applied to tropical tuna fisheries' data, the method confirmed the empirical knowledge on which first time‐area closures were based and provided scientifical support. All in all, the visual support provided by the method, its interpretability and its potential transferability to other fisheries' systems constitute its main strengths and imply a possible implementation in management decisions; specifically, as a tool to reach agreement between stakeholders in the definition of regulated areas for protecting juveniles of tunas and vulnerable associated species to dFAD practices.

<p>Forest demographic processes - growth, recruitment and mortality - are being altered by global change. The changing balance between growth and mortality strongly influences forest dynamics and the carbon balance. Elevated atmospheric carbon dioxide (eCO<sub>2</sub>) has been reported to enhance photosynthesis and tree growth rates by increasing both light-use efficiency (LUE) and water-use efficiency (WUE). Tree growth enhancement could be translated into an increase in biomass stocks or could be associated with a reduction in the longevity of trees, thus reducing the ability of forest ecosystems to act as carbon sinks over long timescales. These links between growth and mortality, and the implications for forest stand density and self-thinning relationships are still debated. Scarce empirical evidence exists for how changing drivers affect tree mortality due to existing data and modelling limitations. Understanding the causes of observed mortality trends and the mechanisms underlying these processes is critical for accurate projections of global terrestrial carbon storage and its feedbacks to anthropogenic climate change.</p><p>Here, we combine a mechanistic model with empirical forest data to better understand the causes of changes in tree mortality and the implications for past and future trends in forest tree density. Specifically, we test the Grow-Fast-Die-Young hypothesis to investigate if a leaf-level CO<sub>2</sub> fertilization effect may lead to an increase in the biomass stock in forest stands. We use a novel vegetation demography model (LM3-PPA) which includes vegetation dynamics with biogeochemical processes allowing for explicit representation of individuals and a mechanistic treatment of tree mortality. The key links between leaf-level assimilation and stand dynamics depend on the carbon turnover time. In this sense, we investigate alternative mortality assumptions about the functional dependence of mortality on tree size, tree carbon balance or growth rate. These formulations represent typical approaches to simulate mortality in mechanistic forest models. Model simulations show that increasing photosynthetic LUE leads to higher biomass stocks, with contrasting behavior among mortality assumptions. Empirical data from Swiss forest inventories support the results from the model simulations showing a shift upwards in the self-thinning relationships, with denser stands and bigger trees. This data-supported mortality-modelling helps to identify links between forest responses and environmental changes at the leaf, tree and stand levels and yields new insight into the causes of currently observed terrestrial carbon sinks and future responses.</p>