Global Changes Jeopardize the Trophic Carrying Capacity and Functioning of Estuarine Ecosystems

Structure and assembly process of fungal communities in the Yangtze River Estuary

Marine fungi are essential for the ecological function of estuarine ecosystems. However, limited studies have reported on the structure and assembly pattern of the fungal communities in estuaries. The purpose of this study is to reveal the structure and the ecological process of the fungal community in the Yangtze River Estuary (YRE) by using the amplicon sequencing method. Phyla of Ascomycota, Basidiomycota, and Chytridiomycota were dominant in the seawater and sediment samples from YRE. The null model analysis, community-neutral community model (NCM), and phylogenetic normalized stochasticity ratio (pNST) showed that the stochastic process dominated the assembly of fungal communities in YRE. Drift and homogeneous dispersal were the predominant stochastic processes for the fungal community assembly in seawater and sediment samples, respectively. The co-occurrence network analysis showed that fungal communities were more complex and closely connected in the sediment than in the seawater samples. Phyla Ascomycota, Basidiomycota, and Mucoromycota were the potential keystone taxa in the network. These findings demonstrated the importance of stochastic processes for the fungal community assembly, thereby widening our knowledge of the community structure and dynamics of fungi for future study and utilization in the YRE ecosystem.

Exploring multiple stressor effects with Ecopath, Ecosim, and Ecospace: Research designs, modeling techniques, and future directions

Understanding the cumulative effects of multiple stressors is a research priority in environmental science. Ecological models are a key component of tackling this challenge because they can simulate interactions between the components of an ecosystem. Here, we ask, how has the popular modeling platform Ecopath with Ecosim (EwE) been used to model human impacts related to climate change, land and sea use, pollution, and invasive species? We conducted a literature review encompassing 166 studies covering stressors other than fishing mostly in aquatic ecosystems. The most modeled stressors were physical climate change (60 studies), species introductions (22), habitat loss (21), and eutrophication (20), using a range of modeling techniques. Despite this comprehensive coverage, we identified four gaps that must be filled to harness the potential of EwE for studying multiple stressor effects. First, only 12% of studies investigated three or more stressors, with most studies focusing on single stressors. Furthermore, many studies modeled only one of many pathways through which each stressor is known to affect ecosystems. Second, various methods have been applied to define environmental response functions representing the effects of single stressors on species groups. These functions can have a large effect on the simulated ecological changes, but best practices for deriving them are yet to emerge. Third, human dimensions of environmental change - except for fisheries - were rarely considered. Fourth, only 3% of studies used statistical research designs that allow attribution of simulated ecosystem changes to stressors' direct effects and interactions, such as factorial (computational) experiments. None made full use of the statistical possibilities that arise when simulations can be repeated many times with controlled changes to the inputs. We argue that all four gaps are feasibly filled by integrating ecological modeling with advances in other subfields of environmental science and in computational statistics.

Influences of Climate Change and Variability on Estuarine Ecosystems: An Impact Study in Selected European, South American and Asian Countries

It is well-known that climate change significantly impacts ecosystems (at the macro-level) and individual species (at the micro-level). Among the former, estuaries are the most vulnerable and affected ecosystems. However, despite the strong relations between climate change and estuaries, there is a gap in the literature regarding international studies across different regions investigating the impacts of climate change and variability on estuaries in different geographical zones. This paper addresses this need and reviews the impacts of climate change, variability and extreme weather on estuaries. It emphasises the following: (i) a set of climate parameters governing estuarine hydrology and processes; and (ii) a sample of countries in Asia (Bangladesh), Europe (Portugal) and South America (Uruguay). We reviewed the influences of the climatic drivers of the estuarine hydrology, ecological processes and specific species in estuarine communities across the selected geographical regions, along with an analysis of their long-term implications. The key results from the three estuaries are as following: (i) Hilsa fish, of which the catches contribute to 10% of the total earnings of the fishery sector (1% of GDP), are affected by climate-forced hydrological and productivity changes in the Meghna; (ii) extreme droughts and short-term severe precipitation have driven the long-term abundance and spatial distribution of both fish larvae and juveniles/adults in the Mondego; and (iii) the river inflow and fluctuations increases since the early 1970s have contributed to variations in the salinity, the stratification, the oxygen, nutrient and trophic levels and the spatial pattern for the life stages of planktonic species, fish biomass and captures in the Rio de la Plata. The results suggested that immediate action is needed to reduce the vulnerability of estuaries to climate stressors, mainly the changing river flows, storms and sea-level rise. As a contribution to addressing current problems, we described a set of adaptation strategies to foster climate resilience and adaptive capacity (e.g., early-warning systems, dam management to prevent overflows and adaptive fisheries management). The implications of this paper are two-fold. Firstly, it showcases a variety of problems that estuaries face from changing climate conditions. Secondly, the paper outlines the need for suitable adaptive management strategies to safeguard the integrity of such vital ecosystems.

From winter to summer and back: Lessons from the parameterization of a seasonal food web model for the Białowieża forest

Dynamic food web models describe how species abundances change over time as a function of trophic and life-history parameters. They are essential to predicting the response of ecosystems to perturbations. However, they are notoriously difficult to parameterize, so that most models rely heavily either on allometric scaling of parameters or inverse estimation of biomass flows. The allometric approach makes species of comparable body mass have near-identical parameters which can generate extinctions within a trophic level. The biomass flow approach is more precise, but is restricted to steady-states, which is not appropriate for time-varying environments. Adequately parameterizing large food webs of temperate and arctic environments requires dealing both with many species of similar sizes and a strongly seasonal environment. Inspired by the rich empirical knowledge on the vertebrate food web of the Białowieża forest, we parameterize a bipartite food web model comprising 21 predators and 124 prey species. Our model is a non-autonomous coupled ordinary differential equations system that allows for seasonality in life-history and predation parameters. Birth and death rates, seasonal descriptions of diet for each species, food requirements and biomass information are combined into a seasonal parameterization of a dynamic food web model. Food web seasonality is implemented with time-varying intrinsic growth rate and interaction parameters, while predation is modelled with both type I and type II functional responses. All our model variants allow for >80% persistence in spite of massive apparent competition, and a quantitative match to observed (seasonal) biomasses. We also identify trade-offs between maximizing persistence, reproducing observed biomasses, and ensuring model robustness to sampling errors. Although multi-annual cycles are expected with type II functional responses, they are here prevented by a strong predator self-regulation. We discuss these results and possible improvements on the model. We provide a general workflow to parameterize dynamic food web models in seasonal environments, based on a real case study. This may help to better predict how biodiverse food webs respond to changing environments.