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Quantifying the temperature sensitivity of methane (CH4) production is crucial for predicting how wetland ecosystems will respond to climate warming. Typically, the temperature sensitivity (often quantified as a Q10 value) is derived from laboratory incubation studies and then used in biogeochemical models. However, studies report wide variation in incubation-inferred Q10 values, with a large portion of this variation remaining unexplained. Here we applied observations in a thawing permafrost peatland (Stordalen Mire) and a well-tested process-rich model (ecosys) to interpret incubation observations and investigate controls on inferred CH4 production temperature sensitivity. We developed a field-storage-incubation modeling approach to mimic the full incubation sequence, including field sampling at a particular time in the growing season, refrigerated storage, and laboratory incubation, followed by model evaluation. We found that CH4 production rates during incubation are regulated by substrate availability and active microbial biomass of key microbial functional groups, which are affected by soil storage duration and temperature. Seasonal variation in substrate availability and active microbial biomass of key microbial functional groups led to strong time-of-sampling impacts on CH4 production. CH4 production is higher with less perturbation post-sampling, i.e. shorter storage duration and lower storage temperature. We found a wide range of inferred Q10 values (1.2-3.5), which we attribute to incubation temperatures, incubation duration, storage duration, and sampling time. We also show that Q10 values of CH4 production are controlled by interacting biological, biochemical, and physical processes, which cause the inferred Q10 values to differ substantially from those of the component processes. Terrestrial ecosystem models that use a constant Q10 value to represent temperature responses may therefore predict biased soil carbon cycling under future climate scenarios.

Marsh and mangrove forest habitats are productive at capturing and storing carbon, thus actions to protect and create coastal blue carbon sinks could help mitigate global warming. Dredged material is often used to create coastal habitats and evaluating the carbon impact of placement alternatives (PA) could help inform restoration and climate policies. Output from a Delft3D‐FM morphodynamics and hydrodynamics model informed a Coastal Wetlands Carbon Model at years 2020, 2025, 2030, and 2050. Three model simulations were used and included (1) no restoration (PA1), (2) restoration dominated with mangroves (PA2), and (3) restoration dominated with marshes (PA3) at a different location. Habitats of brackish marsh, saline marsh, mangrove forest, and saline open water that surround Port Fourchon, Louisiana, U.S.A., were evaluated to estimate the net greenhouse gas (GHG) flux of the study area with and without restoration. In years 2020 and 2025, the study area was estimated to be a net GHG sink (−1.1 ± 0.2 MMT CO2e) with or without mangrove and marsh‐dominated restoration. At years 2030 and 2050, even with habitat loss due to sea‐level rise, the study area for all simulations was projected to remain a net GHG sink. At year 2050, +0.1 ± 0.04 MMT CO2e could be avoided with restoration. At the restoration project scale, mangrove‐dominated restoration (PA2) had net GHG sinks (−0.07 to −0.09 MMT CO2e) near the marsh‐dominated restoration (PA3, −0.09 to −0.13 MMT CO2e). Thus, these modeled results could help inform future restoration planning and climate policies. [ABSTRACT FROM AUTHOR]

Our understanding of the similarity in trajectories of ecosystem changes during different directions of environmental change is limited. For example, do the dominant organisms exhibit the same responses to different directions of environmental change, that is, do they exhibit symmetric responses? Here, we explore whether such response symmetry is determined and controlled by the symmetry in the features of the underlying biological system (i.e., system symmetry), such as in the network and strength of biotic and abiotic processes, and in symmetry of the environmental change (i.e., environmental symmetry). For this exploration, we developed and used a simple mathematical model of a microbial ecosystem driven by mutual inhibition in which we could vary the amount of system and environmental symmetry. Our results show that perfect system and environmental symmetry indeed produce perfect response symmetry. Moreover, introducing asymmetry in biological systems or in the environment proportionally increases response asymmetry. These findings suggest using symmetries in ecosystem structure and interaction strength to better understand and predict similarities in degradation and restoration phases of environmental change. [ABSTRACT FROM AUTHOR]

Abstract Our understanding of the similarity in trajectories of ecosystem changes during different directions of environmental change is limited. For example, do the dominant organisms exhibit the same responses to different directions of environmental change, that is, do they exhibit symmetric responses? Here, we explore whether such response symmetry is determined and controlled by the symmetry in the features of the underlying biological system (i.e., system symmetry), such as in the network and strength of biotic and abiotic processes, and in symmetry of the environmental change (i.e., environmental symmetry). For this exploration, we developed and used a simple mathematical model of a microbial ecosystem driven by mutual inhibition in which we could vary the amount of system and environmental symmetry. Our results show that perfect system and environmental symmetry indeed produce perfect response symmetry. Moreover, introducing asymmetry in biological systems or in the environment proportionally increases response asymmetry. These findings suggest using symmetries in ecosystem structure and interaction strength to better understand and predict similarities in degradation and restoration phases of environmental change.

Objective: The Gulf of Mexico hosts some of the most productive fisheries in the United States, whereas the same region is known to experience environmental stressors, such as summer hypoxia. Ecosystem models have been developed for the Gulf of Mexico to determine how hypoxia affects living marine resources, but these models and their output are not always easy to access or interpret by managers, thereby decreasing their implementation in a management setting. To help alleviate the gap between ecosystem model development and management utility, the current study focuses on co‐produced, user‐friendly tools that describe the effects of nutrient and hypoxia reductions on marine living resources. Methods: Two decisions were made prior to the ecosystem model development to facilitate the transfer of model output: (1) to engage and consult fisheries and restoration managers throughout ecosystem model development to ensure that the output would provide relevant information; and (2) to provide an accessible visualization tool for making ecosystem model output readily available to support the needs of decision makers. Result: Results from an advisory panel survey instrument and advisory panel meetings guided ecosystem model development and launched the development of a decision support tool. The iterative process of building a decision support tool incorporating feedback from survey instrument respondents resulted in an ESRI ArcGIS Dashboard that allows end‐users to identify the effects of hypoxia and respondent‐specified nutrient and hypoxia reduction goals on the biomass and distribution of fisheries species. Conclusion: The intent is to aid managers who are actively working to address hypoxia in the Gulf of Mexico with easy‐to‐access information on the effects of planned actions and to encourage future modelers to apply action science principles to best address the needs of decision makers. Impact statementIn this study we worked directly and iteratively with managers, who are actively working to address hypoxia in the Gulf of Mexico, to co‐produce an easy‐to‐access tool that visualizes the effects of nutrient load reduction goals on important fisheries species in the Gulf of Mexico. [ABSTRACT FROM AUTHOR]

Model Intercomparison Projects (MIPs) are fundamental to our understanding of how the land surface responds to changes in climate. However, MIPs are challenging to conduct, requiring the organization of multiple, decentralized modeling teams throughout the world running common protocols. We explored centralizing these models on a single supercomputing system. We ran nine offline terrestrial biosphere models through the Terrestrial Biosphere Model Farm: CABLE, CENTURY, HyLand, ISAM, JULES, LPJ-GUESS, ORCHIDEE, SiB-3, and SiB-CASA. All models were wrapped in a software framework driven with common forcing data, spin-up, and run protocols specified by the Multi-scale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP) for years 1901-2100. We ran more than a dozen model experiments. We identify three major benefits and three major challenges. The benefits include: (a) processing multiple models through a MIP is relatively straightforward, (b) MIP protocols are run consistently across models, which may reduce some model output variability, and (c) unique multimodel experiments can provide novel output for analysis. The challenges are: (a) technological demand is large, particularly for data and output storage and transfer; (b) model versions lag those from the core model development teams; and (c) there is still a need for intellectual input from the core model development teams for insight into model results. A merger with the open-source, cloud-based Predictive Ecosystem Analyzer (PEcAn) ecoinformatics system may be a path forward to overcoming these challenges.

Climate change is a global problem that causes severe local changes to marine biota, ecosystem functioning, and ecosystem services. The Limfjorden is a shallow, eutrophic estuary influenced by episodic summer hypoxia with an important mussel fishery and suspended mussel culture industry. Three future climate change scenarios ranging from low greenhouse gas emissions (SSP1-2.6), to intermediate (SSP2-4.5) and very high emissions (SSP5-8.5) were combined with nutrient load reductions according to the National Water Plans to investigate potential impacts on natural benthic mussel populations and suspended mussel culture for the two periods 2051–2060 and 2090–2099, relative to a reference period from 2009 to 2018. The FlexSem model combined 3D hydrodynamics with a pelagic biogeochemical model, a sediment-benthos model, and a dynamic energy budget - farm scale model for mussel culture. Model results showed that the Limfjorden was sensitive to climate change impacts with the strongest responses of physics and water quality in the worst case SSP5-8.5 scenario with no nutrient reductions. In the two low emissions scenarios, expected improvements of bottom oxygen and Chlorophyll a concentrations due to reduced nutrient loads were counteracted by climate change impacts on water physics (warming, freshening, stronger stratification). Hence, higher nutrient reductions in the Water Plans would be needed to reach a good ecological status under the influence of climate change. Suspended mussel culture was intensified in all scenarios showing a high potential harvest, whereas the benthic mussels suffered from reduced food supply and hypoxia. Provided the environmental changes and trends in social demands, in the future, it is likely that suspended mussel cultivation will become the primary source of mussels for the industry. Model scenarios can be used to inform managers, mussel farmers, fishermen, and the local population on potential future changes in bivalve harvesting and ecosystem health, and to find solutions to mitigate climate change impacts.

Changes in the thermal structure of lake ecosystems have been documented as a response to climate change, but the dynamics of biomass distribution, which fundamentally determines species conservation, has been less studied. An interdisciplinary approach was used to demonstrate the influence of climate‐driven changes on the environmental DNA (eDNA) distribution of two species (Gymnogobius isaza and Palaemon paucidens) in Lake Biwa, the largest monomictic lake in Japan. In field surveys in 2016–2017 (full water circulation) and 2019 (partial water circulation), eDNA concentrations of these species were measured for 43 and 47 samples, respectively, collected from the lake bottom. The correlative relationship was investigated between species' eDNA concentrations and environmental variables. The species–environment relationship was then applied to species' eDNA distributions under existing and future environments calculated by a lake ecosystem model. Based on differences in the estimated eDNA distributions, we suggest that different species respond differently to climate change. The distribution of G. isaza will expand in the future if full water circulation occurs, although it appears to be independent of water circulation at present. Partial water circulation enlarges the distribution area of P. paucidens, but its eDNA concentrations will be low in the future, regardless of the extent of water circulation. These results indicate that species such as P. paucidens, which is now abundant but vulnerable to climate change, require special attention. Furthermore, our study emphasizes the potential application of interdisciplinary methodologies for improved species conservation. [ABSTRACT FROM AUTHOR]

Abstract Changes in the thermal structure of lake ecosystems have been documented as a response to climate change, but the dynamics of biomass distribution, which fundamentally determines species conservation, has been less studied. An interdisciplinary approach was used to demonstrate the influence of climate‐driven changes on the environmental DNA (eDNA) distribution of two species (Gymnogobius isaza and Palaemon paucidens) in Lake Biwa, the largest monomictic lake in Japan. In field surveys in 2016–2017 (full water circulation) and 2019 (partial water circulation), eDNA concentrations of these species were measured for 43 and 47 samples, respectively, collected from the lake bottom. The correlative relationship was investigated between species' eDNA concentrations and environmental variables. The species–environment relationship was then applied to species' eDNA distributions under existing and future environments calculated by a lake ecosystem model. Based on differences in the estimated eDNA distributions, we suggest that different species respond differently to climate change. The distribution of G. isaza will expand in the future if full water circulation occurs, although it appears to be independent of water circulation at present. Partial water circulation enlarges the distribution area of P. paucidens, but its eDNA concentrations will be low in the future, regardless of the extent of water circulation. These results indicate that species such as P. paucidens, which is now abundant but vulnerable to climate change, require special attention. Furthermore, our study emphasizes the potential application of interdisciplinary methodologies for improved species conservation.

Shallow lakes are known for sudden shifts between a desired clear and an undesired turbid state despite only incremental changes in the underlying drivers. Such sudden shifts are a major challenge for lake managers who can be confronted with abrupt losses of desired ecosystem services without easily observable warning signals. Predictive tools for the loss of ecosystem resilience are vital to respond with timely mitigation measures and avert a shift to the undesired state. Early-warning indicators (EWIs) have faithfully preceded critical transitions in minimal models but have proven more elusive in real-world data, suggesting a mismatch between measurement strategy and the detectability of EWIs. Here, we capitalize on data simulated using the aquatic ecosystem model PCLake+ which represents real systems more closely than reductionistic models and which allows the generation of critical transitions in response to gradual changes in phosphorus load. We tested the effect of different sampling intervals (daily to yearly) on the detection of three often-used EWIs across a range of food web and nutrient-related variables. Moreover, we included one integrated sampling interval (yearly average of daily measurements) to represent time-integrated measurements. EWIs generally performed better at shorter intervals (daily, weekly) but integrated measurements over the year also proved suitable to detect oncoming state shifts. We propose that lake managers should aim for high-frequency measurements of variables that can be easily and cheaply measured (e.g. oxygen, Secchi) or, alternatively, focus on integrated approaches using passive samplers or sedimented material.

Marine phytoplankton biomass dynamics are affected by eutrophication, ocean warming, and ocean acidification. These changing abiotic conditions may impact phytoplankton biomass and its spatiotemporal dynamics. In this study, we used a nutrient–phytoplankton–zooplankton (NPZ) model to quantify the relative importance of the bottom-up and top-down determinants of phytoplankton biomass dynamics in the Belgian part of the North Sea (BPNS). Using four years (2014–2017) of monthly observations of nutrients, solar irradiance, sea surface temperature, chlorophyll-a, and zooplankton biomass at ten locations, we disentangled the monthly, seasonal, and yearly variation in phytoplankton biomass dynamics. To quantify how the relative importance of determinants changed along a near–offshore gradient, the analysis was performed for three spatial regions, i.e., the nearshore region (<10 km to the coastline), the midshore region (10–30 km), and the offshore region (>30 km). We found that, from year 2014 to 2017, the phytoplankton biomass dynamics ranged from 1.4 to 23.1 mg Chla m−3. Phytoplankton biomass dynamics follow a general seasonal cycle, as is the case in other temperate regional seas, with a distinct spring bloom (5.3–23.1 mg Chla m−3) and a modest autumn bloom (2.9–5.4 mg Chla m−3). This classic bimodal bloom pattern was not observed between 2003 and 2010 in the BPNS. The seasonal pattern was most expressed in the nearshore region. The relative contribution of factors determining phytoplankton biomass dynamics varied spatially and temporally. Throughout a calendar year, solar irradiance and zooplankton grazing were the most influential determinants in all regions, i.e., they jointly explained 38–65% of the variation in the offshore region, 45–71% in the midshore region, and 56–77% in the nearshore region. In the near- and midshore regions, nutrients were the greatest limit on phytoplankton production in the month following the spring bloom (44–55%). Nutrients were a determinant throughout the year in the offshore region (27–62%). During winter, sea surface temperature was a determinant in all regions (15–17%). By the high-resolution spatiotemporal analysis of the relative contributions of different determinants, this study contributes to a better mechanistic understanding of the spatiotemporal dynamics of phytoplankton biomass in the southern North Sea. This detailed understanding is anticipated to contribute to the definition of targeted management strategies for the BPNS and to support sustainable development in Belgium's blue economy. [ABSTRACT FROM AUTHOR]

Projecting the dynamics and functioning of the biosphere requires a holistic consideration of whole‐ecosystem processes. However, biases toward leaf, canopy, and soil modeling since the 1970s have constantly left fine‐root systems being rudimentarily treated. As accelerated empirical advances in the last two decades establish clearly functional differentiation conferred by the hierarchical structure of fine‐root orders and associations with mycorrhizal fungi, a need emerges to embrace this complexity to bridge the data‐model gap in still extremely uncertain models. Here, we propose a three‐pool structure comprising transport and absorptive fine roots with mycorrhizal fungi (TAM) to model vertically resolved fine‐root systems across organizational and spatial–temporal scales. Emerging from a conceptual shift away from arbitrary homogenization, TAM builds upon theoretical and empirical foundations as an effective and efficient approximation that balances realism and simplicity. A proof‐of‐concept demonstration of TAM in a big‐leaf model both conservatively and radically shows robust impacts of differentiation within fine‐root systems on simulating carbon cycling in temperate forests. Theoretical and quantitative support warrants exploiting its rich potentials across ecosystems and models to confront uncertainties and challenges for a predictive understanding of the biosphere. Echoing a broad trend of embracing ecological complexity in integrative ecosystem modeling, TAM may offer a consistent framework where modelers and empiricists can work together toward this grand goal. [ABSTRACT FROM AUTHOR]

Ecosystem management in the face of global change requires understanding how co‐occurring threats affect species and communities. Such an understanding allows for effective management strategies to be identified and implemented. An important component of this is differentiating between factors that are within (e.g. invasive predators) or outside (e.g. drought, large wildfires) of a local manager's control. In the global biodiversity hotspot of south‐western Australia, small‐ and medium‐sized mammal species are severely affected by anthropogenic threats and environmental disturbances, including invasive predators, fire, and declining rainfall. However, the relative importance of different drivers has not been quantified. We used data from a long‐term monitoring program to fit Bayesian state‐space models that estimated spatial and temporal changes in the relative abundance of four threatened mammal species: the woylie (Bettongia penicillata), chuditch (Dasyurus geoffroii), koomal (Trichosurus vulpecula) and quenda (Isoodon fusciventor). We then use Bayesian structural equation modelling to identify the direct and indirect drivers of population changes, and scenario analysis to forecast population responses to future environmental change. We found that habitat loss or conversion and reduced primary productivity (caused by rainfall declines) had greater effects on species' spatial and temporal population change than the range of fire and invasive predator (the red fox Vulpes vulpes) management actions observed in the study area. Scenario analysis revealed that a greater extent of severe fire and further rainfall declines predicted under climate change, operating in concert are likely to further reduce the abundance of these species, but may be mitigated partially by invasive predator control. Considering both historical and future drivers of population change is necessary to identify the factors that risk species recovery. Given that both anthropogenic pressures and environmental disturbances can undermine conservation efforts, managers must consider how the relative benefit of conservation actions will be shaped by ongoing global change. [ABSTRACT FROM AUTHOR]

Abstract Using outputs from an ecosystem model embedded in an eddy-resolving ocean general circulation model that can realistically simulate decadal modulations of the Kuroshio Extension (KE) between stable and unstable states, decadal variations of phytoplankton concentration in the upstream KE region are investigated. During stable states of the KE, surface phytoplankton concentrations are anomalously suppressed to the south of the KE front, while those to the north are anomalously enhanced. Although the surface phytoplankton concentration anomalies are prominent only during winter to spring, significant subsurface anomalies centered around 60 m depth persist even in summer and autumn. Anomalies persist throughout the year in phytoplankton biomass integrated over the upper 100 m despite the strong surface anomalies during the spring bloom season. An analysis of nitrogen concentration anomalies suggests that the vertical movement of the isopycnal surfaces, vertical mixing of nutrients, and meridional shifts in the KE jet contribute to the anomalous phytoplankton biomass.

Balanced harvest (BH) proposes moderate fishing mortality rates across all species or sizes in proportion to productivity, serving as a possible strategy for ecosystem-based fisheries management. Fishing patterns in some developing countries (e.g. China, the largest producer of seafood) closely resemble BH, where catches have been highly diversified by unselective gears due to market demand for almost all species. In this study, we employed an OSMOSE ecosystem model developed for the Yellow Sea in China to investigate the potential occurrences and advantages of BH in this region with highly exploited multispecies fisheries. Simulations were carried out under four types of fishing scenarios, where various levels of fishing mortality rates for all species or specific functional groups were implemented. Results indicated that the occurrences of BH depended on fishing pressure and targeted functional groups, and that size-level BH was significantly correlated with biomass and yield for most species. In particular, varying fishing pressure for certain functional groups resulted in BH, which produced a high yield for specific species and ensured their biomass sustainability. We concluded that the benefits of BH could be potentially achieved by adjusting fishing pressure for certain functional groups based on the existing fishing pattern in over-exploited ecosystems. [ABSTRACT FROM AUTHOR]

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The complexities of ecosystem-based management require stepwise approaches, ideally involving stakeholders, to scope key processes, pressures, and impact in relation to sustainability and management objectives. Use of qualitative methods like Fuzzy Cognitive Mapping (FCM) with a lower skill and data threshold than traditional quantitative models afford opportunity for even untrained stakeholders to evaluate the present and future status of the marine ecosystems under varying impacts. Here, we present the results applying FCM models for subregions of the North Sea. Models for the southern North Sea, Skagerrak, Kattegat, and the Norwegian Trench were developed with varying level of stakeholder involvement. Future scenarios of increased and decreased fishing, and increased seal biomass in the Kattegat, were compared with similar scenarios run on two quantitative ecosystem model. Correspondence in response by the models to the same scenarios was lowest in the southern North Sea, which had the simplest FCM model, and highest in Norwegian Trench. The results show the potential of combining FCM and quantitative modelling approaches in integrated ecosystem assessments (IEAs) and in future ecosystem-based management advice, but to facilitate such comparisons and allow them to complement and enhance our IEAs, it is important that their components are aligned and comparable. [ABSTRACT FROM AUTHOR]

Understanding the spatiotemporal dynamics of trophic structures, or trophodynamics, is important for assessing the overall condition and function of estuarine ecosystems. We examined spatial and seasonal trophodynamics of nekton assemblages across the seascape of a subtropical estuary (Charlotte Harbor, FL, USA) using historical nekton data from an ongoing monitoring program. We also examined relationships between trophodynamics and the spatial distribution of vegetated habitats, such as salt marshes, mangroves, and seagrass beds, as well as their absence along hardened shorelines (seawalls or riprap) using seascape metrics (area and edge density of habitats within several search radii of sample locations). We found that nekton assemblages in shallow waters (from the shoreline to a depth of ≤ 1.5 m) transitioned from mainly planktivores in the lower Peace and Myakka Rivers to mainly benthivores (those feeding on benthic infauna, epifauna, or seagrass) in the middle and lower portions of Charlotte Harbor. Overall nekton assemblages throughout the estuary appeared to be largely sustained through benthic pathways in areas with abundant seagrass and nearby mangrove habitat, particularly during the cool-dry winter when planktivore densities were seasonally low. The dramatic seasonal decline in planktivore densities we found in the lower rivers may be related to low freshwater inflow and increased predation resulting from seasonal recruitment pulses of several omnivorous species. Trophodynamics linked with seascape metrics of estuarine habitat structure described here may be used as a spatially explicit baseline of the estuarine seascape to monitor ecosystem health as well as parameterize spatial ecosystem models used in fisheries management in Charlotte Harbor and similar subtropical estuaries. [ABSTRACT FROM AUTHOR]

Quantifying the temperature sensitivity of methane (CH _4 ) production is crucial for predicting how wetland ecosystems will respond to climate warming. Typically, the temperature sensitivity (often quantified as a Q _10 value) is derived from laboratory incubation studies and then used in biogeochemical models. However, studies report wide variation in incubation-inferred Q _10 values, with a large portion of this variation remaining unexplained. Here we applied observations in a thawing permafrost peatland (Stordalen Mire) and a well-tested process-rich model ( ecosys ) to interpret incubation observations and investigate controls on inferred CH _4 production temperature sensitivity. We developed a field-storage-incubation modeling approach to mimic the full incubation sequence, including field sampling at a particular time in the growing season, refrigerated storage, and laboratory incubation, followed by model evaluation. We found that CH _4 production rates during incubation are regulated by substrate availability and active microbial biomass of key microbial functional groups, which are affected by soil storage duration and temperature. Seasonal variation in substrate availability and active microbial biomass of key microbial functional groups led to strong time-of-sampling impacts on CH _4 production. CH _4 production is higher with less perturbation post-sampling, i.e. shorter storage duration and lower storage temperature. We found a wide range of inferred Q _10 values (1.2–3.5), which we attribute to incubation temperatures, incubation duration, storage duration, and sampling time. We also show that Q _10 values of CH _4 production are controlled by interacting biological, biochemical, and physical processes, which cause the inferred Q _10 values to differ substantially from those of the component processes. Terrestrial ecosystem models that use a constant Q _10 value to represent temperature responses may therefore predict biased soil carbon cycling under future climate scenarios.

We used extensive ecological and biogeochemical measurements obtained from quasi-Lagrangian experiments during two California Current Ecosystem Long-Term Ecosystem Research cruises to analyze carbon fluxes between the epipelagic and mesopelagic zones using a linear inverse ecosystem model (LIEM). Measurement constraints on the model include 14C primary productivity, dilution-based microzooplankton grazing rates, gut pigment-based mesozooplankton grazing rates (on multiple zooplankton size classes), 234Th:238U disequilibrium and sediment trap measured carbon export, and metabolic requirements of micronekton, zooplankton, and bacteria. A likelihood approach (Markov Chain Monte Carlo) was used to estimate the resulting flow uncertainties from a sample of potential flux networks. Results highlight the importance of mesozooplankton active transport (i.e., diel vertical migration) in supplying the carbon demand of mesopelagic organisms and sequestering carbon dioxide from the atmosphere. In nine water parcels ranging from a coastal bloom to offshore oligotrophic conditions, mesozooplankton active transport accounted for 18–84% (median: 42%) of the total carbon transfer to the mesopelagic, with gravitational settling of POC (12–55%; median: 37%), and subduction (2–32%; median: 14%) providing the majority of the remainder. Vertically migrating zooplankton contributed to downward carbon flux through respiration and excretion at depth and via mortality losses to predatory zooplankton and mesopelagic fish (e.g., myctophids and gonostomatids). Sensitivity analyses showed that the results of the LIEM were robust to changes in nekton metabolic demand, rates of bacterial production, and mesozooplankton gross growth efficiency. This analysis suggests that prior estimates of zooplankton active transport based on conservative estimates of standard (rather than active) metabolism are likely too low.

We used extensive ecological and biogeochemical measurements obtained from quasi-Lagrangian experiments during two California Current Ecosystem Long-Term Ecosystem Research cruises to analyze carbon fluxes between the epipelagic and mesopelagic zones using a linear inverse ecosystem model (LIEM). Measurement constraints on the model include 14C primary productivity, dilution-based microzooplankton grazing rates, gut pigment-based mesozooplankton grazing rates (on multiple zooplankton size classes), 234Th:238U disequilibrium and sediment trap measured carbon export, and metabolic requirements of micronekton, zooplankton, and bacteria. A likelihood approach (Markov Chain Monte Carlo) was used to estimate the resulting flow uncertainties from a sample of potential flux networks. Results highlight the importance of mesozooplankton active transport (i.e., diel vertical migration) in supplying the carbon demand of mesopelagic organisms and sequestering carbon dioxide from the atmosphere. In nine water parcels ranging from a coastal bloom to offshore oligotrophic conditions, mesozooplankton active transport accounted for 18–84% (median: 42%) of the total carbon transfer to the mesopelagic, with gravitational settling of POC (12–55%; median: 37%), and subduction (2–32%; median: 14%) providing the majority of the remainder. Vertically migrating zooplankton contributed to downward carbon flux through respiration and excretion at depth and via mortality losses to predatory zooplankton and mesopelagic fish (e.g., myctophids and gonostomatids). Sensitivity analyses showed that the results of the LIEM were robust to changes in nekton metabolic demand, rates of bacterial production, and mesozooplankton gross growth efficiency. This analysis suggests that prior estimates of zooplankton active transport based on conservative estimates of standard (rather than active) metabolism are likely too low.

Marine ecosystems are exposed to multiple stressors, mainly fisheries that, whenever mismanaged, may cause irreversible damages to whole food webs. Ecosystem models have been applied to forecast fisheries impact on fish stocks and marine food webs. These impacts have been studied through the use of multiple indicators that help to understand ecosystem responses to stressors. This study focused on a category of ecological indicators derived from the network theory to quantify energy flows inside the food web. These indicators were computed using two ecosystem models applied to the Eastern English Channel (i.e. Atlantis and OSMOSE). This work aimed at investigating how several ecological network indicators respond to different levels of fishing pressure and evaluating their robustness to model structure and fishing strategies. We applied a gradient of fishing mortality using two ecosystem models and carried out ecological network analysis to obtain network-derived indicators. The results revealed that the indicators response is highly driven by the food web structure, although the model assumptions buffered some results. The indicators computed from OSMOSE outputs were more sensitive to changes in fishing pressure than those from Atlantis. However, once the food web from Atlantis was simplified to mimic the structure of OSMOSE model, the indicators of the modified Atlantis became more sensitive to the intensity of fishing pressure. The indicators related to amount of energy flow and to the organization of the flows in the food web were sensitive to the increase of fishing mortality for all fishing strategies. These indicators suggested that increasing fishing mortality jeopardizes the amount of energy mobilized by the food webs and simplifies the ecological interactions, which has implications for the resilience of marine ecosystems. The study shed light on the trophic networks structure and functioning of the ecosystems whenever exposed to disturbances. Furthermore, these indicators might be adequate for whole ecosystem assessments of health and contribute to ecosystem management.

Background and objectives: Primary Gross Productivity (GPP) is a crucial factor in the carbon cycle of ecosystems. With the increasing occurrence of droughts due to global warming and the unique response of plant cover ages to these changes, it is necessary to identify and quantify the relationship between climate data and ecosystem's primary gross productivity. This research aims to determine the plant cover's response to drought by analyzing the region's primary gross productivity in the Bordekhun region in southwest Iran. This study introduces a new ecosystem model, focusing on two objectives: (1) simulating primary gross productivity through ecosystem modeling and (2) examining the response of primary gross productivity to drought during the growth season, evaluating the effectiveness of this model in an arid region. Methodology: The research was conducted in three stages, including determining meteorological drought conditions over a 16-year period using the Standardized Precipitation Index (SPI), simulating primary gross productivity (GPP) using the new ecosystem model BGC-MAN (Bio-Geo-Chemistry Management Model), and validating it with MODIS satellite images. The quantification of the ecosystem's response to drought during the vegetation growth season was performed for the period from 2000 to 2015. The relationship between GPP and SPI was analyzed using the Pearson correlation coefficient, and the model was validated using the MODIS GPP product. The evaluation focused on the response of various grass and shrub vegetation forms to drought, with the percentage of coverage for each vegetation form utilized in 29 sampling points. Results: The statistical analysis revealed a significant correlation coefficient (p < 0.05, R2 = 0.14) between the modeled GPP and the GPP estimated from MODIS satellite images on a monthly scale. The temporal analysis of drought conditions over the 16-year period indicated consecutive droughts with varying severity, and the spatial distribution of drought severity showed that 48.79% and 51.21% of the study area were in normal and moderate drought states, respectively. The temporal analysis of changes in primary gross productivity during the growth season demonstrated a decreasing trend in most months except for December, with notable variations. The correlation analysis between primary gross productivity and drought showed a significant positive correlation in grass forms during the months of January, February, and March, while for shrub forms, a significant positive correlation was observed only in the month of March. Conclusion: The results indicated that grass showed the highest correlation in the middle of the growing season (December and January) (R = 0.29), while shrubs showed the highest correlation at the end of the growing season (February and March) (R = 0.28), indicating their different sensitivity to water scarcity during the growth season. The study also revealed that ecosystem modeling could be an alternative approach to estimating GPP with the potential to simulate spatial GPP in arid regions. However, the proposed model's performance in other regions still requires further verification. [ABSTRACT FROM AUTHOR]

Simple Summary: We investigated the ecological role of the squat lobster (Munida gregaria) and the Fuegian sprat (Sprattus fuegensis) in the food web of the Francisco Coloane Marine Area in the Magellan Strait, Chile. We analyzed the ecosystem impacts of biomass changes in the squat lobster and Fuegian sprat. Food web indicators and simulations were estimated using the Ecopath with Ecosim software. Both species were located in the second trophic level. The squat lobster was preyed upon by 12 functional groups, which highlighted its role as an important prey in the ecosystem and its positive impacts on predators such as red cod, whales, and penguins. As prey, the Fuegian sprat presented a direct interaction with 10 functional groups, which exerted positive impacts on predators such as penguins, seabirds and whales. In summary, the Francisco Coloane Area is an immature ecosystem with productivity and energy flows values within those reported for productive ecosystems; the role of the squat lobster seems to be related to the structure of the food web, while the Fuegian sprat plays a role in the energy transfer to top predators. Although the study area is currently a Marine Protected Area, monitoring squat lobster and Fuegian sprat populations might ensure the conservation of this ecosystem. The structure and functioning of the food web of the Francisco Coloane Marine Area in the Magellan Strait, Chile, was quantified, with an emphasis on identifying the ecological role of the squat lobster (Munida gregaria) and the Fuegian sprat (Sprattus fuegensis). Food web indicators, the trophic level, and centrality indices were estimated using Ecopath with Ecosim. Dynamic simulations were carried out to evaluate the ecosystem impacts of biomass changes in squat lobster and Fuegian sprat. The model calculated a total ecosystem biomass of 71.7 t km−2 and a total primary production of 2450.9 t km−2 year−1. Squat lobster and Fuegian sprat were located in specific trophic levels of 2.3 and 2.7, respectively. Squat lobster reduction produced a decrease in the biomass of red cod (42–56%) and humpback whales (25–28%) and Fuegian sprat reduction a decrease in penguins (15–37%) and seabirds (11–34%). The Francisco Coloane Area is an immature ecosystem with productivity and energy flows values within those reported for productive ecosystems; the role of the squat lobster seems to be related to the structure of the food web, and the role of the Fuegian sprat seems to be related to the functioning of the ecosystem and to the energy transfer to top predators. [ABSTRACT FROM AUTHOR]

This article surveys the field of leadership studies from its inception as 'Great Man' historical analysis strongly influenced by Thomas Carlyle and by Max Weber's classic work on the concept of charisma in his theorizing of 'authority' within the modern bureaucratic state. Both approaches require careful deconstruction. The Weberian approach is still of relevance to the consideration of underlying political theories of leadership. The article surveys and reviews the formation of the field by reference to trait studies and leadership development and education before mentioning 'School Leadership For Social Justice, Equity and Diversity'. The next section of the paper focuses on the contemporary paradigm of transformational leadership and the attendant notion of 'the policy context' of New Public Management and the Creative Economy as the defining context for creative leadership. The next two sections introduce the feminist critique of leadership studies and what has become known as 'critical leadership studies'. Finally, the paper considers leadership in the twentyfirst century by reference to three moments: (i) multipolarity and the production of global public goods; (ii) the biodigital future; and, (iii) the ecological-systems model of leadership. A brief postscript considers crisis leadership for post-apocalyptic survival. [ABSTRACT FROM AUTHOR]

Using outputs from an ecosystem model embedded in an eddy-resolving ocean general circulation model that can realistically simulate decadal modulations of the Kuroshio Extension (KE) between stable and unstable states, decadal variations of phytoplankton concentration in the upstream KE region are investigated. During stable states of the KE, surface phytoplankton concentrations are anomalously suppressed to the south of the KE front, while those to the north are anomalously enhanced. Although the surface phytoplankton concentration anomalies are prominent only during winter to spring, significant subsurface anomalies centered around 60 m depth persist even in summer and autumn. Anomalies persist throughout the year in phytoplankton biomass integrated over the upper 100 m despite the strong surface anomalies during the spring bloom season. An analysis of nitrogen concentration anomalies suggests that the vertical movement of the isopycnal surfaces, vertical mixing of nutrients, and meridional shifts in the KE jet contribute to the anomalous phytoplankton biomass. [ABSTRACT FROM AUTHOR]

Indicators to predict ecosystem state change are urgently needed to cope with the degradation of ecosystem services caused by global change. With the development of new technologies for measuring ecosystem function with fine spatiotemporal resolution over broad areas, we are in the era of 'big data'. However, it is unclear how large, emerging datasets can be used to anticipate ecosystem state change. We propose the construction of indicators based on functional variables (flows) and state variables (pools) to predict future ecosystem state changes. The indicators identified here may be useful signals for doing so. In addition, functional indicators have explicit ecological meanings that can identify the ecological mechanism that is causing state changes, and can thus be used to improve ecosystem models. Global climate changes and human activities are exerting great pressures on ecosystems, and may cause catastrophic collapse of ecosystem states and services. However, the indicators that can be used to detect ecosystem state change remain a key question. Although emerging evidence suggests the feasibility of using functional indicators to detect ecosystem state changes, state-based indicators derived from mathematical theory are conventionally used. The increasingly availability of long-term datasets of ecosystem functions at high spatiotemporal resolution provides us with novel opportunities to detect ecosystem state changes. Ecosystem models simulate ecosystem biogeochemical cycles. Functional indicators enable us to identify the mechanisms causing state changes, and can be used to diagnose and improve ecosystem models for predicting long-term changes in ecosystem functioning as a consequence of state changes. [ABSTRACT FROM AUTHOR]

Leaf dry mass per unit area (LMA), carboxylation capacity (Vcmax) and leaf nitrogen per unit area (Narea) and mass (Nmass) are key traits for plant functional ecology and ecosystem modelling. There is however no consensus about how these traits are regulated, or how they should be modelled. Here we confirm that observed leaf nitrogen across species and sites can be estimated well from observed LMA and Vcmax at 25°C (Vcmax25). We then test the hypothesis that global variations of both quantities depend on climate variables in specific ways that are predicted by leaf‐level optimality theory, thus allowing both Narea to be predicted as functions of the growth environment.A new global compilation of field measurements was used to quantify the empirical relationships of leaf N to Vcmax25 and LMA. Relationships of observed Vcmax25 and LMA to climate variables were estimated, and compared to independent theoretical predictions of these relationships. Soil effects were assessed by analysing biases in the theoretical predictions.LMA was the most important predictor of Narea (increasing) and Nmass (decreasing). About 60% of global variation across species and sites in observed Narea, and 31% in Nmass, could be explained by observed LMA and Vcmax25. These traits, in turn, were quantitatively related to climate variables, with significant partial relationships similar or indistinguishable from those predicted by optimality theory. Predicted trait values explained 21% of global variation in observed site‐mean Vcmax25, 43% in LMA and 31% in Narea. Predicted Vcmax25 was biased low on clay‐rich soils but predicted LMA was biased high, with compensating effects on Narea. Narea was overpredicted on organic soils.Synthesis. Global patterns of variation in observed site‐mean Narea can be explained by climate‐induced variations in optimal Vcmax25 and LMA. Leaf nitrogen should accordingly be modelled as a consequence (not a cause) of Vcmax25 and LMA, both being optimized to the environment. Nitrogen limitation of plant growth would then be modelled principally via whole‐plant carbon allocation, rather than via leaf‐level traits. Further research is required to better understand and model the terrestrial nitrogen and carbon cycles and their coupling. [ABSTRACT FROM AUTHOR]

Carbon use efficiency (CUE) represents the proficiency of plants in transforming carbon dioxide (CO2) into carbon stock in terrestrial ecosystems. CUE extremes represent ecosystems' extreme proficiency in carbon transformation. Studying CUE extremes and their forming climate conditions is critical for enhancing ecosystem carbon storage. However, the study of CUE extremes and their forming climate conditions on the global scale is still lacking. In this study, we used the results from the daily Boreal Ecosystem Productivity Simulator (BEPS) model to detect the positive and negative CUE extremes and analyze their forming climatic conditions on a global scale. We found grasslands have the largest potential in changing global CUE, with the contribution being approximately 32.4% to positive extremes and 30.2% to negative extremes. Spring in the Northern Hemisphere (MAM) contributed the most (30.5%) to positive CUE extremes, and summer (JJA) contributed the most (29.7%) to negative CUE extremes. The probabilities of gross primary production (GPP) extremes resulted in CUE extremes (>25.0%) being larger than autotrophic respiration (Ra), indicating CUE extremes were mainly controlled by GPP rather than Ra extremes. Positive temperature anomalies (0~1.0 °C) often accompanied negative CUE extreme events, and positive CUE extreme events attended negative temperature anomalies (−1.0~0 °C). Moreover, positive (0~20.0 mm) and negative precipitation (−20.0~0 mm) anomalies often accompanied positive and negative CUE extremes, respectively. These results suggest that cooler and wetter climate conditions could be beneficial to enhance carbon absorptions of terrestrial ecosystems. The study provides new knowledge on proficiency in carbon transformation by terrestrial ecosystems. [ABSTRACT FROM AUTHOR]

Marine phytoplankton biomass dynamics are affected by eutrophication, ocean warming, and ocean acidification. These changing abiotic conditions may impact phytoplankton biomass and its spatiotemporal dynamics. In this study, we used a nutrient–phytoplankton–zooplankton (NPZ) model to quantify the relative importance of the bottom-up and top-down determinants of phytoplankton biomass dynamics in the Belgian part of the North Sea (BPNS). Using four years (2014–2017) of monthly observations of nutrients, solar irradiance, sea surface temperature, chlorophyll-a, and zooplankton biomass at ten locations, we disentangled the monthly, seasonal, and yearly variation in phytoplankton biomass dynamics. To quantify how the relative importance of determinants changed along a near–offshore gradient, the analysis was performed for three spatial regions, i.e., the nearshore region (30 km). We found that, from year 2014 to 2017, the phytoplankton biomass dynamics ranged from 1.4 to 23.1 mg Chla m−3. Phytoplankton biomass dynamics follow a general seasonal cycle, as is the case in other temperate regional seas, with a distinct spring bloom (5.3–23.1 mg Chla m−3) and a modest autumn bloom (2.9–5.4 mg Chla m−3). This classic bimodal bloom pattern was not observed between 2003 and 2010 in the BPNS. The seasonal pattern was most expressed in the nearshore region. The relative contribution of factors determining phytoplankton biomass dynamics varied spatially and temporally. Throughout a calendar year, solar irradiance and zooplankton grazing were the most influential determinants in all regions, i.e., they jointly explained 38–65% of the variation in the offshore region, 45–71% in the midshore region, and 56–77% in the nearshore region. In the near- and midshore regions, nutrients were the greatest limit on phytoplankton production in the month following the spring bloom (44–55%). Nutrients were a determinant throughout the year in the offshore region (27–62%). During winter, sea surface temperature was a determinant in all regions (15–17%). By the high-resolution spatiotemporal analysis of the relative contributions of different determinants, this study contributes to a better mechanistic understanding of the spatiotemporal dynamics of phytoplankton biomass in the southern North Sea. This detailed understanding is anticipated to contribute to the definition of targeted management strategies for the BPNS and to support sustainable development in Belgium’s blue economy.

The Arctic may be particularly vulnerable to the consequences of both ocean acidification (OA) and global warming, given the faster pace of these processes in comparison with global average speeds. Here, we use the Atlantis ecosystem model to assess how the trophic network of marine fishes and invertebrates in the Icelandic waters is responding to the combined pressures of OA and warming. We develop an approach where we first identify species by their economic (catch value), social (number of participants in fisheries), or ecological (keystone species) importance. We then use literature-determined ranges of sensitivity to OA and warming for different species and functional groups in the Icelandic waters to parametrize model runs for different scenarios of warming and OA. We found divergent species responses to warming and acidification levels; (mainly) planktonic groups and forage fish benefited while (mainly) benthic groups and predatory fish decreased under warming and acidification scenarios. Assuming conservative harvest rates for the largest catch-value species, Atlantic cod, we see that the population is projected to remain stable under even the harshest acidification and warming scenario. Further, for the scenarios where the model projects reductions in biomass of Atlantic cod, other species in the ecosystem increase, likely due to a reduction in competition and predation. These results highlight the interdependencies of multiple global change drivers and their cascading effects on trophic organization, and the continued high abundance of an important species from a socio-economic perspective in the Icelandic fisheries. [ABSTRACT FROM AUTHOR]

Building on the Salamanca Statement from 1994, the United Nations Sustainability Development Goals 2030 embraces inclusion for children in early childhood education. The European Agency for Special Needs and Inclusive Education in 2015–2017 completed a project on inclusive early childhood education, focusing on structures, processes, and outcomes that ensure a systemic approach to high-quality Inclusive Early Childhood Education (IECE). An ecosystem model of IECE was developed with a self-reflection tool for improving inclusion. This study's aim was to investigate practitioners' perspective on the inclusive processes and supportive structures defined in the ecosystem model, to contribute to a deeper understanding of how inclusive practice might be enabled and how barriers for inclusion can be removed. The self-reflection tool was administered in a heterogeneous municipality in Sweden, where inclusive settings are standard. Documentation from approximately 70 teachers on 27 teams was received. The documentation was analysed with qualitative content analysis based on the ecosystem model. The results showed a strong emphasis on group-related processes, whereas data on individual-related processes were scarce. This one-sided focus on the group level might endanger the inclusive processes and outcomes concerning the individual child. [ABSTRACT FROM AUTHOR]

Brazil has become one of the largest consumers of pesticides in the world. However, there are still few studies evaluating pesticide toxicity integrating local aquatic and terrestrial environments. In addition, there is growing concern about the influence of temperature conditions related with climate change on contaminants toxicity. The aim of the present study was to evaluate the elutriate toxicity of the insecticide Kraft® 36 EC (a.i. abamectin), the fungicide Score® 250 EC (a.i. difenoconazole) and their mixture to the cladocerans Ceriodaphnia silvestrii and Daphnia similis, using model ecosystems (mesocosms). To this end, mesocosms were filled with natural soil and subjected to the following treatments: Control (Milli-Q water), Kraft (10.8 g abamectin ha−1), Score (20 g difenoconazole ha−1), and Kraft + Score (10.8 g abamectin ha−1 + 20 g difenoconazole ha−1). The experiment lasted 18 days, and the applications were made on days 1, 8, and 15; the occurrence of rainfall was simulated on days 1, 8, and 15 after applications and only rainfall simulation on days 4, 11, and 18. The experiment was conducted under two different temperatures: 23 °C and 33 °C. At 23 °C, single Kraft treatment and in combination with Score showed high toxicity to both cladocerans. At 33 °C, elutriate of the Kraft® and mixture treatments were highly toxic to D. similis but not to C. silvestrii. The results indicate that while Kraft had higher toxicity than Score to both cladocerans, this toxicity was counteracted at 33 °C only for the exotic species, D. similis. The results portray the complexity of pesticide toxicity when considering realistic experimental settings including different organisms and temperature treatments. [ABSTRACT FROM AUTHOR]

In this study, high-quality soil moisture data derived from the Soil Moisture Active Passive (SMAP) satellite measurements are evaluated from a perspective of improving the estimation of the global gross primary production (GPP) using a process-based ecosystem model, namely, the Boreal Ecosystem Productivity Simulator (BEPS). The SMAP soil moisture data are assimilated into BEPS using an ensemble Kalman filter. The correlation coefficient (r) between simulated GPP from the sunlit leaves and Sun-induced chlorophyll fluorescence (SIF) measured by Global Ozone Monitoring Experiment-2 is used as an indicator to evaluate the performance of the GPP simulation. Areas with SMAP data in low quality (i.e., forests), or with SIF in low magnitude (e.g., deserts), or both are excluded from the analysis. With the assimilated SMAP data, the r value is enhanced for Africa, Asia, and North America by 0.016, 0.013, and 0.013, respectively (p

Lipid-storing copepods are fundamental to the functioning of marine ecosystems, transferring energy from primary producers to higher trophic levels and sequestering atmospheric carbon (C) in the deep ocean. Quantifying trophic transfer and biogeochemical cycling by copepods requires improved understanding of copepod metabolic rates in both surface waters and during lipid-fueled metabolism over winter. Here we present new biomass turnover rates of C and nitrogen (N) in Calanoides acutus, Calanoides natalis, Calanus glacialis and Calanus hyperboreus alongside published data for Calanus finmarchicus and Calanus pacificus. Turnover rates in metabolically active animals, normalised to 10°C, ranged between 0.007 – 0.105 d-1 and 0.004 – 0.065 d-1 for C and N, respectively. Turnover rates of C were typically faster than those for N, supporting the understanding that non-protein C, e.g. lipid, is catabolised faster than protein. Re-analysis of published data indicates that inactive, overwintering C. finmarchicus turn over wax ester lipids at a rate of 0.0016 d-1. These and other basal rate data will facilitate the mechanistic representation of copepod physiology in global biogeochemical models, thereby reducing uncertainties in our predictions of future ocean ecosystem functioning and C sequestration.

Grazing lands play a significant role in global carbon (C) dynamics, holding substantial soil organic carbon (SOC) stocks. However, historical mismanagement (e.g., overgrazing and land-use change) has led to substantial SOC losses. Regenerative practices, such as adaptive multi-paddock (AMP) grazing, offer a promising avenue to improve soil health and help combat climate change by increasing SOC accrual, both in its particulate (POC) and mineral-associated (MAOC) organic C components. Because adaptive grazing patterns emerge from the combination of different levers such as frequency, intensity, and timing of grazing, studying AMP grazing management in experimental trials and representing it in models remains challenging. Existing ecosystem models lack the capacity to predict how different adaptive grazing levers affect SOC storage and its distribution between POC and MAOC and along the soil profile accurately. Therefore, they cannot adequately assist decision-makers in effectively optimizing adaptive practices based on SOC outcomes. Here, we address this critical gap by developing version 2.34 of the MEMS 2 model. This version advances the previous by incorporating perennial grass growth and grazing submodules to simulate grass green-up and dormancy, reserve organ dynamics, the influence of standing dead plant mass on new plant growth, grass and supplemental feed consumption by animals, and their feces and urine input to soil. Using data from grazing experiments in the southeastern United States and experimental SOC data from two conventional and three AMP grazing sites in Mississippi, we tested the capacity of MEMS 2.34 to simulate grass forage production, total SOC, POC, and MAOC dynamics to 1-m depth. Further, we manipulated grazing management levers, i.e., timing, intensity, and frequency, to do a sensitivity analysis of their effects on SOC dynamics in the long term. Our findings indicate that the model can represent bahiagrass forage production (BIAS = 9.51 g C m−2, RRMSE = 0.27, RMSE = 65.57 g C m−2, R2 = 0.72) and accurately captured the dynamics of SOC fractions across sites and depths (0–15 cm: RRMSE = 0.05; 15–100 cm: RRMSE = 1.08–2.07), aligning with patterns observed in the measured data. The model best captured SOC and MAOC stocks across AMP sites in the 0–15 cm layer, while POC was best predicted at-depth. Otherwise, the model tended to overestimate SOC and MAOC below 15 cm, and POC in the topsoil. Our simulations indicate that grazing frequency and intensity were key levers for enhancing SOC stocks compared to the current management baseline, with decreasing grazing intensity yielding the highest SOC after 50 years (63.7–65.9 Mg C ha−1). By enhancing our understanding of the effects of adaptive grazing management on SOC pools in the southeastern U.S., MEMS 2.34 offers a valuable tool for researchers, producers, and policymakers to make AMP grazing management decisions based on potential SOC outcomes. • MEMS 2.34 simulated with good accuracy bahiagrass productivity in Southeast US pastures. • It can simulate AMP management effects on SOC, POC, and MAOC to 1 m depth. • MEMS 2.34 forecasted AMP grazing to increase SOC stocks in the Southeast US. • Optimizing intensity and frequency can enhance AMP grazing benefit on SOC outcomes. [ABSTRACT FROM AUTHOR]

Despite their size and contribution to the global carbon cycle, we have limited understanding of tropical savannas and their current trajectory with climate change and anthropogenic pressures. Here we examined interannual variability and externally forced long‐term changes in carbon and water exchange from a high rainfall savanna site in the seasonal tropics of north Australia. We used an 18‐year flux data time series (2001–2019) to detect trends and drivers of fluxes of carbon and water. Significant positive trends in gross primary productivity (GPP, 15.4 g C m2 year−2), ecosystem respiration (Reco, 8.0 g C m2 year−2), net ecosystem productivity (NEE, 7.4 g C m2 year−2) and ecosystem water use efficiency (WUE, 0.0077 g C kg H2O−1 year−1) were computed. There was a weaker, non‐significant trend in latent energy exchange (LE, 0.34 W m−2 year−1). Rainfall from a nearby site increased statistically over a 45‐year period during the observation period. To examine the dominant drivers of changes in GPP and WUE, we used a random forest approach and a terrestrial biosphere model to conduct an attribution experiment. Radiant energy was the dominant driver of wet season fluxes, whereas soil water content dominated dry season fluxes. The model attribution suggested that [CO2], precipitation and Tair accounting for 90% of the modelled trend in GPP and WUE. Positive trends in fluxes were largest in the dry season implying tree components were a larger contributor than the grassy understorey. Fluxes and environmental drivers were not significant during the wet season, the period when grasses are active. The site is potentially still recovering from a cyclone 45 years ago and regrowth from this event may also be contributing to the observed trends in sequestration, highlighting the need to understand fluxes and their drivers from sub‐diurnal to decadal scales. [ABSTRACT FROM AUTHOR]

China's contribution to global greening is regulated by increasing atmospheric CO2 concentrations, climate change, and land use. Based on TRENDY project data, this study identified that the shifts in China's contribution to the global leaf area index (LAI) trend strongly reduced during the warming hiatus, translating from 13.42 ± 26.45% during 1982–1998 into 7.91 ± 25.45% during 1999–2012. First, significant negative sensitivities of LAI to enhanced vapor pressure deficit (VPD), when only considering the climate effect derived from TRENDY models in China, were found to have shifted substantially after the late 1990s. However, globally, LAI had positive rather than negative responses to enhanced VPD. These opposing shifts in the response of LAI to enhanced VPD reduced the national contribution to global vegetation greening. Second, shifts in land-use change and their effects on the LAI trends in the two periods in China were accompanied by major changes in land cover and land management intensity, including forestry. Consequently, the contribution of land use in China reduced by −47.68% during the warming hiatus period, as compared with the warming period. Such a shift in the impact of land-use change on LAI simulated by ecosystem models might result from the models' lack of consideration of conserving and expanding forests with the goal of mitigating climate change for China. Our results highlight the need for ecosystem models to reproduce the enhanced negative impact on global LAI and consider the shifts in man-made adaptation policies (e.g., forest management) to improve terrestrial ecosystem models in the future. [ABSTRACT FROM AUTHOR]

In this paper, we present a novel implementation of an ecosystem simulation. In our previous work, we implemented a 3D environment based on a predator–prey model, but we found that in most cases, regardless of the choice of starting parameters, the simulation quickly led to extinctions. We wanted to achieve system stabilization, long-term operation, and better simulation of reality by incorporating genetic evolution. Therefore we applied the predator–prey model with an evolutional approach. Using the Unity game engine we created and managed a closed 3D ecosystem environment defined by an artificial or real uploaded map. We present some demonstrative runs while gathering data, observing interesting events (such as extinction, sustainability, and behavior of swarms), and analyzing possible effects on the initial parameters of the system. We found that incorporating genetic evolution into the simulation slightly stabilized the system, thus reducing the likelihood of extinction of different types of objects. The simulation of ecosystems and the analysis of the data generated during the simulations can also be a starting point for further research, especially in relation to sustainability. Our system is publicly available, so anyone can customize and upload their own parameters, maps, objects, and biological species, as well as inheritance and behavioral habits, so they can test their own hypotheses from the data generated during its operation. The goal of this article was not to create and validate a model but to create an IT tool for evolutionary researchers who want to test their own models and to present them, for example, as animated conference presentations. The use of 3D simulation is primarily useful for educational purposes, such as to engage students and to increase their interest in biology. Students can learn in a playful way while observing in the graphical scenery how the ecosystem behaves, how natural selection helps the adaptability and survival of species, and what effects overpopulation and competition can have. [ABSTRACT FROM AUTHOR]

With ongoing manmade climate change, it is important to understand its impact on regional ecosystems. Furthermore, it is known that the North Sea light climate is subject to ongoing change. The combined effects of climate change and coastal darkening are investigated in this work. We used a three-dimensional ecosystem model, forced with data from a climate model, to project three plausible biogeochemical states for the years 2050–2054, following three representative concentration and shared socioeconomic pathways (RCP2.6-SSP1, RCP4.5-SSP2 and RCP8.5-SSP5). We also performed a historic experiment for the years 1950–1954 and 2000–2004 for comparison. Our results suggest significant reductions of phytoplankton biomass as a consequence of sinking nutrient levels for all future scenarios. Additionally, a modelling study was carried out, in which we raised background SPM levels by 40% to reflect potential changes in the future. This revealed that for RCP2.6-SSP1, the ecosystem is more sensitive to changes in the light climate than for the other scenarios, due to higher nutrient availability.

Results from a fully coupled end-to-end ecosystem model for the California Current Large Marine Ecosystem are used to describe the impact of environmental variability and prey availability on the foraging ecology of its most abundant apex predator, the California sea lion Zalophus californianus. The ecosystem model consists of a biogeochemical submodel embedded in a regional ocean circulation submodel, both coupled with a multi-species individual-based submodel for forage fish (sardine and anchovy) and California sea lions. Sardine and anchovy are explicitly represented in the model as they are commonly found in the diet of sea lions and exhibit significant interannual and decadal variability in population abundances that reflect variations in their environment and lower trophic level prey. Output from a 20 yr run (1989-2008) of the model demonstrates how different physical and biological processes control habitat utilization and foraging success of California sea lions on interannual time scales, with the dominant modes of variability linked to sardine abundance and coastal upwelling intensity. The results also illustrate how variability in environmental conditions, forage fish distribution, and prey assemblage affect sea lion feeding success. While specifically focusing on the foraging ecology of sea lions, the modeling framework has the ability to provide a more complete understanding of the physical and biological mechanisms impacting trophic interactions in the California Current, or other regions where similar fully coupled ecosystem models may be implemented.