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At least 235 records · Page 13

Drivers and ecological impacts of a wildfire outbreak in the southern Appalachian Mountains after decades of fire exclusion

During one of the warmest and driest droughts of the last century, the southern Appalachian Mountains experienced a regional outbreak of over a dozen large wildfires in late fall of 2016. We provide a synthesis of long-term forest changes leading up to the 2016 wildfires, examine the climatic setting and patterns of burn severity in relationship to topography, and discuss the ecological and management implications of these and future fires. During the pre- and post-European settlement periods, frequent low- and mixed-severity wildfires interacted with complex topographic gradients and maintained heterogenous landscapes dominated by several species of oak (Quercus spp.), pine (Pinus spp.), and the American chestnut (Castanea dentata). Land-use changes associated with European settlement, loss of the American chestnut, and 20th century fire exclusion resulted in large scale shifts towards mesic, fire-intolerant species (i.e. mesophication). Wildfire activity began increasing in the early 1980s, but most fires in the region are small (<1,000 ha). In Fall of 2016, deciduous tree leaf fall occurred concurrently with a period of anomalously dry and warm weather, creating ideal conditions for fire ignition and spread. Thousands of ignitions across the region strained suppression resources and eight fires grew to greater than 5,000 ha. The 2016 fires were larger and burned more area than in the previous three decades combined. In one unique landscape setting, the Chimney Tops 2 Fire, a synoptic wind event drove extreme fire behavior and burned large, high-severity patches resulting in devastating effects in the wildland urban interface. However, immediate post-fire burn severity mosaics for other fires were composed primarily of low- (73 %) and moderate-severity (21 %) fire effects. High-severity fire comprised only 6 % of the area burned, and occurred mostly on steep upper slopes and ridges on south-facing aspects, reflecting the importance of bottom-up topographic drivers in this region. Although the fires will likely enhance biodiversity by restoring fire-dependent species and creating early seral habitat, invasions of non-native plant species, delayed mortality of mature pines and oaks, and rapid re-sprouting of pyrophyllic shrubs pose significant management challenges. Although similar large fire outbreaks may become more common under future climatic conditions, they are unlikely to reverse the effects of mesophication and significantly alter forest dynamics at broad spatial scales. Furthermore, the 2016 fires exposed the vulnerability of the region to wildfire during acute fall drought and demonstrate the potential ecological effects of future wildfires in mixed pine-hardwood landscapes of the southern Appalachians.

54 ENVIRONMENTAL SCIENCES↗

Ecological Forecasting in Chesapeake Bay: Using a Mechanistic-Empirical Modelling Approach

The Chesapeake Bay Ecological Prediction System (CBEPS) automatically generates daily nowcasts and three-day forecasts of several environmental variables, such as sea-surface temperature and salinity, the concentrations of chlorophyll, nitrate, and dissolved oxygen, and the likelihood of encountering several noxious species, including harmful algal blooms and water-borne pathogens, for the purpose of monitoring the Bay's ecosystem. While the physical and biogeochemical variables are forecast mechanistically using the Regional Ocean Modeling System configured for the Chesapeake Bay, the species predictions are generated using a novel mechanistic empirical approach, whereby real-time output from the coupled physical biogeochemical model drives multivariate empirical habitat models of the target species. The predictions, in the form of digital images, are available via the World Wide Web to interested groups to guide recreational, management, and research activities. Though full validation of the integrated forecasts for all species is still a work in progress, we argue that the mechanistic–empirical approach can be used to generate a wide variety of short-term ecological forecasts, and that it can be applied in any marine system where sufficient data exist to develop empirical habitat models. This paper provides an overview of this system, its predictions, and the approach taken.

Brown, C. W.↗

An ecologically-constrained deep learning model for tropical leaf phenology monitoring using PlanetScope satellites

In tropical forests, leaf phenology signals leaf-on/off status and exhibits considerable variability across scales from a single tree-crown to the entire forest ecosystem. Such phenology signals importantly regulate large-scale biogeochemical cycles and regional climate. PlanetScope CubeSats data with a 3-m resolution and near-daily global coverage provide an unprecedented opportunity to monitor both fine- and ecosystem-scale phenology variability along large environmental gradients. However, a scalable method that accurately characterizes leaf phenology from PlanetScope with biophysically meaningful metrics remains lacking. Here we developed an index-guided, ecologically constrained autoencoder (IG-ECAE) method to automatically derive a deciduousness metric (i.e. percentage of tree canopies with leaf-off status within an image pixel) from PlanetScope. The IG-ECAE first estimated the reflectance spectra of leafy/leafless canopies based on their spectral indices characteristics, then used the derived reflectance spectra to guide an autoencoder deep learning method with additional ecological constraints to refine the reflectance spectra, and finally used linear spectral unmixing to estimate the relative abundance of leafless canopies (or deciduousness) per PlanetScope image pixel. We tested the IG-ECAE method at 16 tropical forest sites spanning multiple continents and a large precipitation gradient (1470-2819 mm year -1 ). Among these sites, we evaluated the PlanetScope-derived deciduousness with corresponding measures derived from WorldView-2 (n=9 sites) and local phenocams (n=9 sites). Our results show that PlanetScope-derived deciduousness agrees: 1) with that derived from WorldView-2 at the patch level (90m×90m) with r 2 =0.89 across all sites; and 2) with that derived from phenocams to quantify ecosystem-scale seasonality with r 2 ranging from 0.62-0.96. These results demonstrate the effectiveness and scalability of IG-ECAE in characterizing the wide variability in deciduousness across scales from pixels to forest ecosystems, and from a single date to the full annual cycle, indicating the potential for using high-resolution satellites to track the large-scale phenological patterns and response of tropical forests to climate change.

54 ENVIRONMENTAL SCIENCES↗

Tropical Cyclone Ecology: A Scale-Link Perspective

Tropical cyclones are increasing in intensity and size and, thus, are poised to increase in importance as disturbance agents. Our understanding of cyclone ecology is biased towards the North Atlantic Basin, because cyclone effects do differ across oceanic basins. Cyclones have both short and long-term effects across the levels of biological organization, but we lack a scale-perspective of cyclone ecology. Effects on individual trees, such as defoliation or branch stripping and uprooting, are mechanistically linked to effects at the community and ecosystem levels, including forest productivity and stand regeneration time. Forest dwarfing via the gradual removal of taller trees by cyclones over many generations illustrates that cyclones shape forest structure through the accumulation of short-term effects over longer timescales.

54 ENVIRONMENTAL SCIENCES↗

Enabling microbial electrolysis cell scale-up via electrochemistry-, hydrodynamic-, and microbial ecology-informed framework

Microbial electrolysis cells (MECs) can produce green hydrogen while removing organic contaminants from liquid waste streams by leveraging the metabolic activity of electroactive microorganisms. Despite their potential in a sustainable, circular economy, large-scale MECs that can treat relevant volumes of wastewater have failed to deliver performance proportional to their lab-scale counterparts. The reason behind this lower performance at scale remains unclear. Here, in this study, we developed a combined electrochemistry-, hydrodynamic-, and microbial ecology-informed framework to analyze and optimize MEC performance during scale-up, enabling accurate quantification of major limitations and the identification of strategies to overcome them, ultimately facilitating equivalent performance at scale. Applying this framework to the scale-up of a zero-gap MEC from 9 cm 2 electrode area to 100 cm 2 electrode area, resulted in similar maximum current densities in a 100 cm 2 MEC (21.7 ± 1.1 A/m 2 ) compared to a 9 cm 2 system (25.1 ± 2.7 A/m 2 ), as well as equivalent hydrogen production rates of 69.3 L/L-d (100 cm 2 ) and 67.7 ± 2.4 L/L-d (9 cm 2 ). COMSOL flow dynamics simulations were used to scale up the reactor configuration without negatively affecting electrolyte velocity and distribution in the cell, minimizing the increase in internal resistances during scale-up (11.7 ± 0.5 mΩm 2 at 9 cm 2 ; 19.7 ± 1.3 mΩm 2 at 100 cm 2 ). Microbial community structures were assessed at both scales using high-throughput sequencing, highlighting the differences of populations across electrode dimensions and operational parameters. The framework presented here accelerates the development of effective strategies toward the scale-up of MECs by furthering the understanding of how electrochemical, hydrodynamic, and microbial ecology parameters change as the reactor dimension is increased. Ultimately, this approach contributes to advancing electrochemical biotechnology toward practical deployment in energy-efficient wastewater treatment systems.

Flow path↗

Phylogenomic insights into the taxonomy, ecology, and mating systems of the lorchel family Discinaceae (Pezizales, Ascomycota)

Lorchels, also known as false morels (Gyromitra sensu lato), are iconic due to their brain-shaped mushrooms and production of gyromitrin, a deadly mycotoxin. Molecular phylogenetic studies have hitherto failed to resolve deep-branching relationships in the lorchel family, Discinaceae, hampering our ability to settle longstanding taxonomic debates and to reconstruct the evolution of toxin production. We generated 75 draft genomes from cultures and ascomata (some collected as early as 1960), conducted phylogenomic analyses using 1542 single-copy orthologs to infer the early evolutionary history of lorchels, and identified genomic signatures of trophic mode and mating-type loci to better understand lorchel ecology and reproductive biology. Our phylogenomic tree was supported by high gene tree concordance, facilitating taxonomic revisions in Discinaceae. We recognized 10 genera across two tribes: tribe Discineae (Discina, Maublancomyces, Neogyromitra, Piscidiscina, and Pseudodiscina) and tribe Gyromitreae (Gyromitra, Hydnotrya, Paragyromitra, Pseudorhizina, and Pseudoverpa); Piscidiscina was newly erected and 26 new combinations were formalized. Paradiscina melaleuca and Marcelleina donadinii formed their own family-level clade sister to Morchellaceae, which merits further taxonomic study. Genome size and CAZyme content were consistent with a mycorrhizal lifestyle for the truffle species (Hydnotrya spp.), whereas the other Discinaceae genera possessed genomic properties of a saprotrophic habit. Lorchels were found to be predominantly heterothallic-either MAT1-1 or MAT1-2-but a single occurrence of colocalized mating-type idiomorphs indicative of homothallism was observed in Gyromitra esculenta strain CBS101906 and requires additional confirmation and follow-up study. Lastly, we confirmed that gyromitrin has a phylogenetically discontinuous distribution, having been detected exclusively in two distantly related genera (Gyromitra and Piscidiscina) belonging to separate tribes. Our genomic dataset will facilitate further investigations into the gyromitrin biosynthesis genes and their evolutionary history. With additional sampling of Geomoriaceae and Helvellaceae-two closely related families with no publicly available genomes-these data will enable comprehensive studies on the independent evolution of truffles and ecological diversification in an economically important group of pezizalean fungi.

Dirks, Alden C↗

Ecological Traits of Fish for Mercury Biomonitoring: Insights from Compound-Specific Nitrogen and Stable Mercury Isotopes

Here we coupled compound-specific isotopic analyses of nitrogen (N) in amino acids (δ 15 N Glu , δ 15 N Phe ) and mercury stable isotopes (δ 202 Hg, Δ 199 Hg) to quantify ecological traits governing the concentration, variability, and source of Hg in largemouth bass (LB) and pike gudgeon (PG) across four rivers, South Korea. PG displayed uniform Hg concentration (56–137 ng/g), trophic position (TP corrected ; 2.6–3.0, n = 9), and N isotopes in the source amino acid (δ 15 N Phe ; 7–13‰), consistent with their specialist feeding on benthic insects. LB showed wide ranges in Hg concentration (45–693 ng/g), TP corrected (2.8–3.8, n = 14), and δ 15 N Phe (1.3–16‰), reflecting their opportunistic feeding behavior. Hg sources assessed using Hg isotopes reveal low and uniform Δ 199 Hg in PG (0.20–0.49‰), similar to Δ 199 Hg reported in sediments. LB displayed site-specific δ 202 Hg (-0.61 to -0.04‰) and Δ 199 Hg (0.53–1.09‰). At the Yeongsan River, LB displayed elevated Δ 199 Hg and low δ 15 N Phe , consistent with Hg and N sourced from the atmosphere. LB at the Geum River displayed low Δ 199 Hg and high δ 15 N Phe , both similar to the isotope values of anthropogenic sources. Our results suggest that a specialist fish (PG) with consistent ecological traits and Hg concentration is an effective bioindicator species for Hg. When accounting for Hg sources, however, LB better captures site-specific Hg sources.

59 BASIC BIOLOGICAL SCIENCES↗

Aquatic Carbon-Nutrient Dynamics as Emergent Properties of Hydrological, Biogeochemical, and Ecological Interactions: Scientific Advances

Carbon and nutrient dynamics in aquatic systems often emerge as the result of hydrological, biogeochemical, and ecological interactions. Due to the multiscale and multidisciplinary nature of these process interactions, research into aquatic carbon and nutrient dynamics is becoming increasingly interdisciplinary. The motivation for this special issue came from an international workshop titled "Hydro-Biogeochemical Processes: Mechanisms, Coupling, and Impact, " which took place from 27 to 31 October 2015 at China University of Geosciences, Wuhan, China. During this workshop, scientists from various countries and disciplines met to discuss current work and future advances on topics such as the hydro-biogeochemistry of Earth's critical zone, stream-groundwater interaction zones, aquatic ecosystem processes, and dynamics at land-atmosphere, land-ocean, and human-natural interfaces. Contributions to this special issue on "Emergent aquatic carbon-nutrient dynamics as products of hydrological, biogeochemical, and ecological interactions" include papers from authors who attended the workshop and from those who responded to the open solicitation for papers. Finally, our aim in organizing this special issue is to stimulate continued discussion and collaboration across disciplinary boundaries in order to further our collective understanding of aquatic carbon-nutrient dynamics.

54 ENVIRONMENTAL SCIENCES↗

Key Environmental and Ecological Variables of Wetland CH 4 and CO 2 Fluxes Change With Warming

Wetlands are important ecosystems for the global carbon cycle, impacting regional and global methane (CH 4 ) and carbon dioxide (CO 2 ) budgets. This study examines how environmental and ecological variables impact wetland CH 4 flux and net ecosystem exchange of CO 2 (NEE) across 17 sites globally. We also quantified the importance of variables for each wetland type and site at monthly scale under normal and warm temperatures using dominance analysis. We identified soil and air temperature (TS, TA, respectively) as key variables influencing wetland CH4, and latent heat (LE) and shortwave radiation (SW) for NEE under normal and warm conditions. However, the importance of some variables shifted with warming. For predicting the variability of wetland CH4 flux under warming, gross primary productivity (GPP) and LE, replacing wind direction (WD), were dominant variables for tropical swamps, while NEE was important for high-latitude fens and bogs under warm temperatures. For wetland NEE, the role of TA and TS decreased across all wetland types with warming, while vapor pressure deficit (VPD) became more important for mid and high-latitude wetlands. Our results reveal the complex responses of wetland carbon flux to environmental and ecological variables with warming and provide new insights into improving wetland models by incorporating additional variables and accounting for the changing roles of variables in carbon flux under warming.

54 ENVIRONMENTAL SCIENCES↗

Ecological roles of dominant and rare prokaryotes in acid mine drainage revealed by metagenomics and metatranscriptomics

Here we report that high-throughput sequencing is expanding our knowledge of microbial diversity in the environment. Still, understanding the metabolic potentials and ecological roles of rare and uncultured microbes in natural communities remains a major challenge. To this end, we applied a ‘divide and conquer’ strategy that partitioned a massive metagenomic data set (>100 Gbp) into subsets based on K-mer frequency in sequence assembly to a low-diversity acid mine drainage (AMD) microbial community and, by integrating with an additional metatranscriptomic assembly, successfully obtained 11 draft genomes most of which represent yet uncultured and/or rare taxa (relative abundance <1%). We report the first genome of a naturally occurring Ferrovum population (relative abundance >90%) and its metabolic potentials and gene expression profile, providing initial molecular insights into the ecological role of these lesser known, but potentially important, microorganisms in the AMD environment. Gene transcriptional analysis of the active taxa revealed major metabolic capabilities executed in situ, including carbon- and nitrogen-related metabolisms associated with syntrophic interactions, iron and sulfur oxidation, which are key in energy conservation and AMD generation, and the mechanisms of adaptation and response to the environmental stresses (heavy metals, low pH and oxidative stress). Remarkably, nitrogen fixation and sulfur oxidation were performed by the rare taxa, indicating their critical roles in the overall functioning and assembly of the AMD community. Finally, our study demonstrates the potential of the ‘divide and conquer’ strategy in high-throughput sequencing data assembly for genome reconstruction and functional partitioning analysis of both dominant and rare species in natural microbial assemblages.

59 BASIC BIOLOGICAL SCIENCES↗

Influences of organic carbon speciation on hyporheic corridor biogeochemistry and microbial ecology

The hyporheic corridor (HC) is a critical component of riverine ecosystems that encompasses the river-11 groundwater continuum. The mixing of groundwater (GW) with river water (RW) in the HC can 12 stimulate biogeochemical activity, and here we (i) propose a novel thermodynamic mechanism 13 underlying this phenomenon, and (ii) reveal broader impacts on dissolved organic carbon (DOC) 14 biogeochemistry and microbial ecology. We show that thermodynamically-favorable DOC 15 accumulates in GW despite decreases in DOC concentration along subsurface flow paths, and that RW 16 contains less thermodynamically-favorable DOC, but at higher concentrations. This indicates that DOC 17 in GW is protected from microbial oxidation by low total energy contained within the DOC pool, while 18 RW DOC is protected by lower thermodynamic favorability of carbon species. We propose that GW-19 RW mixing overcomes these protection mechanisms and stimulates respiration. Mixing models 20 coupled with time-lapse electrical resistance tomography revealed that stimulated respiration leads 21 to tipping points in spatiotemporal dynamics of DOC across the HC. Further, shifts in DOC speciation 22 and biochemical pathways were associated with shifts in microbiome composition, highlighting 23 feedbacks among hydrology, DOC biochemistry, and microbial ecology. These results reveal that 24 previously unrecognized thermodynamic-based mechanisms regulated by GW-RW mixing can strongly 25 influence biogeochemical and microbial dynamics in riverine ecosystems.

54 ENVIRONMENTAL SCIENCES↗

Root traits explain plant species distributions along climatic gradients yet challenge the nature of ecological trade-offs

Ecological theory is built on trade-offs, where trait differences among species evolved as adaptations to different environments. Trade-offs are often assumed to be bidirectional, where opposite ends of a gradient in trait values confer advantages in different environments. However, unidirectional benefits could be widespread if extreme trait values confer advantages at one end of an environmental gradient, whereas a wide range of trait values are equally beneficial at the other end. Here, we show that root traits explain species occurrences along broad gradients of temperature and water availability, but model predictions only resembled trade-offs in two out of 24 models. Forest species with low specific root length and high root tissue density (RTD) were more likely to occur in warm climates but species with high specific root length and low RTD were more likely to occur in cold climates. Unidirectional benefits were more prevalent than trade-offs: for example, species with large-diameter roots and high RTD were more commonly associated with dry climates, but species with the opposite trait values were not associated with wet climates. Directional selection for traits consistently occurred in cold or dry climates, whereas a diversity of root trait values were equally viable in warm or wet climates. Explicit integration of unidirectional benefits into ecological theory is needed to advance our understanding of the consequences of trait variation on species responses to environmental change.

54 ENVIRONMENTAL SCIENCES↗

Phenogenomics reveals the ecology and evolution of Trichoderma fungi for sustainable agriculture

Trichoderma fungi support sustainable agriculture by suppressing plant diseases and improving crop performance. However, emerging pathogenicity of Trichoderma warrants further ecological and genetic characterization. Here we used machine learning to correlate genomic data from 37 Trichoderma strains with over 140 phenotypic traits, spanning metabolic versatility, biotic interactions, stress tolerance and reproductive strategies. We determined Trichoderma to be an ancient, genetically cohesive and physiologically diverse genus with spores capable of germination in water and dispersal via air and water droplets. Metabolic preferences indicate universal adaptation to mycoparasitism and to niches like arboreal microbial mats, alongside broader saprotrophic versatility. Our analyses are consistent with character displacement among close relatives and convergent evolution in distant lineages, with both processes shaping ecological plasticity and traits including dispersal modes, terrestrialization or endophytism. Our findings reveal that while some Trichoderma species show traits of biosafety concern, its vast ecophysiological diversity enables the development of safe, targeted bioeffectors.

Steindorff, Andrei S. [USDOE Joint Genome Institut↗

Historical ecology reveals landscape transformation coincident with cultural development in central Italy since the Roman Period

Knowledge of the direct role humans have had in changing the landscape requires the perspective of historical and archaeological sources, as well as climatic and ecologic processes, when interpreting paleoecological records. People directly impact land at the local scale and land use decisions are strongly influenced by local sociopolitical priorities that change through time. A complete picture of the potential drivers of past environmental change must include a detailed and integrated analysis of evolving sociopolitical priorities, climatic change and ecological processes. However, there are surprisingly few localities that possess high-quality historical, archeological and high-resolution paleoecologic datasets. We present a high resolution 2700-year pollen record from central Italy and interpret it in relation to archival documents and archaeological data to reconstruct the relationship between changing sociopolitical conditions, and their effect on the landscape. Here, we found that: (1) abrupt environmental change was more closely linked to sociopolitical and demographic transformation than climate change; (2) landscape changes reflected the new sociopolitical priorities and persisted until the sociopolitical conditions shifted; (3) reorganization of new plant communities was very rapid, on the order of decades not centuries; and (4) legacies of forest management adopted by earlier societies continue to influence ecosystem services today.

54 ENVIRONMENTAL SCIENCES↗

Ecological Insights from Transferable Plant Biomass Mapping across the Arctic using High-resolution Structure-from-Motion and LiDAR Data

Warmer temperatures, permafrost thaw, and increased wildfire activity are driving rapid ecological change across the Arctic, significantly altering plant productivity and aboveground biomass (AGB). These rapid changes highlight the urgent need to improve monitoring of vegetation dynamics in the Earth’s northern ecosystems, where high spatiotemporal heterogeneity occurs at scales finer than those captured by traditional satellite observations. The growing use of Unoccupied Aerial Systems (UASs) presents an opportunity to overcome this limitation. Yet, the diversity of UAS platforms, sensors, and data collection and processing workflows presents challenges for developing standardized, generalizable approaches. To address this challenge, we compiled 672 AGB plots co-located with 183 UAS-based Structure-from-Motion (SfM) or Light Detection and Ranging (LiDAR) surveys collected across the Arctic. Here, we: (1) evaluated the generalizability of UAS-derived canopy structure derived from high-resolution SfM and LiDAR for estimating AGB, (2) assessed scaling errors and their sources in two recent satellite-based AGB products derived from Landsat and MODIS, and (3) demonstrated the use of high-resolution AGB maps to quantify biomass variation across tundra plant functional types (PFTs) and to monitor post-fire recovery. Our results show that both SfM and LiDAR accurately captured AGB and its variability across tundra PFTs using a Random Forest (RF) model (overall RMSE: 0.336 kg/m2), with mapping performance varying slightly by region and data source. Using UAS-derived AGB maps as a benchmark, we identified systematic biases in satellite-derived AGB products, largely attributable to the magnitude of AGB and structural heterogeneity within coarse-resolution pixels. Applying our model to repeat UAS surveys following a tundra fire on Seward Peninsula, we observed rapid AGB recovery in non-shrub patches, with biomass recovering to pre-fire levels within 2 years. In contrast, shrub patches recovered more slowly, with AGB gains continuing over 2–4 years through both in-patch growth and lateral expansion (via dispersal) into remaining burned areas. Overall, these findings demonstrate the generalizability of UAS-based SfM and LiDAR data for estimating tundra AGB and highlight the potential of our approach to be broadly applied to generate high-quality AGB data for ecological monitoring and model benchmarking across the Arctic.

Yang, Daryl [ORNL] (ORCID:0000000317057823)↗

The microbial rare biosphere: current concepts, methods and ecological principles

ABSTRACT Our ability to describe the highly diverse pool of low abundance populations present in natural microbial communities is increasing at an unprecedented pace. Yet we currently lack an integrative view of the key taxa, functions and metabolic activity which make-up this communal pool, usually referred to as the ‘rare biosphere’, across the domains of life. In this context, this review examines the microbial rare biosphere in its broader sense, providing an historical perspective on representative studies which enabled to bridge the concept from macroecology to microbial ecology. It then addresses our current knowledge of the prokaryotic rare biosphere, and covers emerging insights into the ecology, taxonomy and evolution of low abundance microeukaryotic, viral and host-associated communities. We also review recent methodological advances and provide a synthetic overview on how the rare biosphere fits into different conceptual models used to explain microbial community assembly mechanisms, composition and function.

Pascoal, Francisco↗

Bacterial–fungal interactions: ecology, mechanisms and challenges

Fungi and bacteria are found living together in a wide variety of environments. Their interactions are significant drivers of many ecosystem functions and are important for the health of plants and animals. A large number of fungal and bacterial families engage in complex interactions that lead to critical behavioural shifts of the microorganisms ranging from mutualism to antagonism. The importance of bacterial–fungal interactions (BFI) in environmental science, medicine and biotechnology has led to the emergence of a dynamic and multidisciplinary research field that combines highly diverse approaches including molecular biology, genomics, geochemistry, chemical and microbial ecology, biophysics and ecological modelling. In this review, we discuss recent advances that underscore the roles of BFI across relevant habitats and ecosystems. A particular focus is placed on the understanding of BFI within complex microbial communities and in regard of the metaorganism concept. We also discuss recent discoveries that clarify the (molecular) mechanisms involved in bacterial–fungal relationships, and the contribution of new technologies to decipher generic principles of BFI in terms of physical associations and molecular dialogues. Lastly, we discuss future directions for research in order to stimulate synergy within the BFI research area and to resolve outstanding questions.

59 BASIC BIOLOGICAL SCIENCES↗

Weak-form inference for hybrid dynamical systems in ecology

Species subject to predation and environmental threats commonly exhibit variable periods of population boom and bust over long timescales. Understanding and predicting such behaviour, especially given the inherent heterogeneity and stochasticity of exogenous driving factors over short timescales, is an ongoing challenge. A modelling paradigm gaining popularity in the ecological sciences for such multi-scale effects is to couple short-term continuous dynamics to long-term discrete updates. We develop a data-driven method utilizing weak-form equation learning to extract such hybrid governing equations for population dynamics and to estimate the requisite parameters using sparse intermittent measurements of the discrete and continuous variables. The method produces a set of short-term continuous dynamical system equations parametrized by long-term variables, and long-term discrete equations parametrized by short-term variables, allowing direct assessment of interdependencies between the two timescales. We demonstrate the utility of the method on a variety of ecological scenarios and provide extensive tests using models previously derived for epizootics experienced by the North American spongy moth ( Lymantria dispar dispar ).

54 ENVIRONMENTAL SCIENCES↗