Fishes are the most diverse group of vertebrates, play key functional roles in aquatic ecosystems, and provide protein for a billion people, especially in the developing world. Those functions are compromised by mounting pressures on marine biodiversity and ecosystems. Because of its economic and food value, fish biomass production provides an unusually direct link from biodiversity to critical ecosystem services. We used the Reef Life Survey’s global database of 4,556 standardized fish surveys to test the importance of biodiversity to fish production relative to 25 environmental drivers. Temperature, biodiversity, and human influence together explained 47% of the global variation in reef fish biomass among sites. Fish species richness and functional diversity were among the strongest predictors of fish biomass, particularly for the large-bodied species and carnivores preferred by fishers, and these biodiversity effects were robust to potentially confounding influences of sample abundance, scale, and environmental correlations. Warmer temperatures increased biomass directly, presumably by raising metabolism, and indirectly by increasing diversity, whereas temperature variability reduced biomass. Importantly, diversity and climate interact, with biomass of diverse communities less affected by rising and variable temperatures than species-poor communities. Biodiversity thus buffers global fish biomass from climate change, and conservation of marine biodiversity can stabilize fish production in a changing ocean.
Marine and coastal ecosystems provide multiple benefits that are fundamental to human wellbeing, but human actions are disrupting and impacting the Earth's ecosystems at an alarming rate. The Ecopath approach was designed to understand the impact of the wide range of anthropogenic pressures that are exerted on the oceans, and of management options for countering these, and it has over the last thirty years grown into a complex and capable modelling framework: “Ecopath with Ecosim” – with Ecospace added on. Exciting new developments of the approach are contributing to address critical and complex issues related to the health of marine ecosystems such as invasion of species, illegal fishing activities, climate change and the development of new activities (e.g., aquaculture and infrastructure development) in coastal areas.
This Special Issue presents new findings from selected case studies around the world using advanced features of Ecopath with Ecosim that were presented at the International Conference “Ecopath 30 Years-Modelling ecosystem dynamics: beyond boundaries with EwE” (November 2014, Barcelona, Spain). These contributions showcase new capabilities and findings of Ecopath with Ecosim models applications. Together these papers show that a range of diverse ecological, economic, social and governance drivers are often interacting at dynamic and temporal scales to modify marine resources, which underlines that managing marine ecosystems needs a continuous effort to integrate multiple processes.
For wave energy to become a commercially viable source of energy, a complete understanding of the wave resource characterisation is needed. In this context, the IEC (International Electrotechnical Commission) has developed a technical specification for the assessment of the wave resource, IEC-TS 62600-101: Marine energy-Wave, tidal and other water current converters-Part 101: Wave energy resource assessment and characterisation (IEC-62600-101), which presents a series of recommendations for standardising wave resource characterisation. The IEC-62600-101 classifies resource assessment studies into three different classes: reconnaissance, feasibility and design. The model setup requirements (mesh resolution, boundary conditions) and the effort (validation process, computational times) vary considerably from one class to the other. On these grounds, the objective of this work is to explore this methodology using the Irish West Coast as a case study. Overall, it was found that the methodology proposed performs well, offering a detailed characterisation of the resource; however, with the aim of making the technical specification more manageable, some aspects related to the seasonality of the wave resource and the validation and model setup procedures may be revisited for future editions.
Explicit and integrated inclusion of ecosystem services (ESs) and their interrelationships can improve the quality of strategic plans and decision-making processes. However, there is little systematic analysis of how ES interrelationships are framed in policy language, particularly in coastal planning discourse. The objective of this paper is therefore to present a four-step method, based on content analysis, to assess ES interrelationships in coastal strategic planning documents. The method consists of: 1) selecting strategic plans; 2) identifying ESs; 3) identifying drivers, ESs and their effects; and 4) constructing relational diagrams. The four-step method is applied to a case of Jiaozhou Bay in China, demonstrating its capacity of identifying which drivers and ES trade-offs and synergies are formulated in coastal strategic plans. The method is helpful to identify overlooked ES interrelationships, inform temporal and spatial issues, and assess the continuity of plans' attention to interrelationships. The main methodological contributions are discussed by emphasizing its broad scope of drivers and ESs and an explicit distinction among the cause of relationships. The developed method also has the potential of cross-fertilizing other kinds of approaches and facilitating practical planning processes.
Aquaculture is an increasingly important economic activity in coastal waters. The fluid environment means spatial management is an important tool for protecting fish health. Scottish aquaculture (largely Atlantic salmon) uses a range of different types of area to group farms for different management or reporting purposes related to fish health. Farm Management Areas are defined by local knowledge and used by industry for co-operation among groups of farms, including in the management of sea lice. Disease Management Areas, defined using a simple but robust model, are used by the Scottish Government for control of notifiable diseases. Particle dispersal models are used to assess areas affected by treatment residue around farms, and to manage maximum allowable area biomass for environmental protection. Sophisticated models of sea lice transport have been developed to help inform management of this key parasite. Large regional areas are used for a variety of purposes, such as a policy presumption against new farms covering the entire east and north coasts of Scotland, and five reporting areas for official production statistics. Scottish aquatic environments are shared by many interest groups and spatial management is proving essential for sustainable development by aquaculture and other users.
It is generally acknowledged that willingness-to-pay (WTP) estimates for environmental goods exhibit some degree of spatial variation. In a policy context, spatial variation in threatened and endangered species values is important to understand, as the benefit stream from policies affecting threatened and endangered species may vary locally, regionally, or among certain population segments. In this paper we present WTP estimates for eight different threatened and endangered marine species estimated from a stated preference choice experiment. WTP is estimated at two different spatial scales: (a) a random sample of over 5000 U.S. households and (b) geographically embedded samples (relative to the U.S. household sample) of nine U.S. Census regions. We conduct region-to-region and region-to-nation statistical comparisons to determine whether species values differ among regions and between each region and the entire U.S. Our results show limited spatial variation between national values and values estimated from regionally embedded samples, and differences are only found for three of the eight species. More variation exists between regions, and for all species there is a significant difference in at least one region-to-region comparison. Given that policy analyses involving threatened and endangered marine species can often be regional in scope (e.g., ecosystem management) or may disparately affect different regions, our results should be of high interest to the marine management community.
We explore how alternative hypotheses on the degree of mixing among local subpopulations affect statistical inferences on the dynamics and stock assessment of a harvested flatfish population, namely, the common sole population in the Eastern Channel (ICES area VIId). The current paradigm considers a single, well-mixed, spatially homogeneous population with juveniles from all coastal nursery grounds along the French and UK coasts that contribute to a single adult population and one pool of eggs. Based on the available data and ecological knowledge, we developed a spatial Bayesian integrated life-cycle model that consists of three subpopulations (one near the UK coast and two near the French coast, denoted UK, West FR and East FR, respectively) supported by their respective local nurseries, with the connectivity among the three components limited to low exchanges during larval drift. Considering the population dynamics among three subpopulations (instead of a single homogeneous one) drastically changes our inferences on the productivity of nursery sectors and their relative contribution to total recruitment. Estimates of the East FR subpopulation’s contribution to total recruitment increase (29% in the single population model; 48% in the three subpopulation model), balanced by a decrease in the UK subpopulation’s contribution (53%; 34%). Whereas an assessment based on the hypothesis of a single spatially homogeneous population in the EC indicates exploitation far above MSY (current F/FMSY = 1.8), an assessment that considers a metapopulation with three loosely connected subpopulations revealed a different status, with the UK and East FR subpopulations being exploited above MSY (current F/FMSY = 1.9 and 2, respectively) and the West FR subpopulation approaching full exploitation (current F/FMSY = 1.05). This approach contributes to the quantitative assessment of spatial fishery and coastal habitat management plans.
A variety of disciplines examine human-environment interactions, identifying factors that affect environmental outcomes important for human well-being. A central challenge for these disciplines is integrating an ever-increasing number of findings into a coherent body of theory. Without a repository for this theory, researchers cannot adequately leverage this knowledge to guide future empirical work. Comparability across field sites, study areas and scientific fields is hampered, as is the progress of sustainability science.
To address this challenge we constructed the first repository of theoretical statements linking social and ecological variables to environmental outcomes. Stored in a relational database that is accessible via a website, this repository includes systematically formalized theories produced from researchers studying resilience, environmental conservation, common-pool resource governance, environmental and resource economics and political ecology. Theories are explicitly linked together in the database to form the first coherent expression of the types of human-environment interactions that affect outcomes for natural resources and, by extension, the people who use them.
Analysis of this repository shows that a variety of types of theories exist, from the simple to the complex, and that theories tend to thematically cluster by scientific field, although the theories of every field were related in at least some way to theories from other fields. Thus there is much potential for increased interaction across these fields, hopefully with the help of resources such as this repository. The theories and variables employed to express their arguments are publicly viewable in a wiki-like format, as a resource for the scientific community.
Understanding climate change impacts on species is vital for correctly estimating their extinction risk and choosing appropriate conservation actions. We perceive four common challenges that hamper conservation planning for species affected by climate change: (i) only considering climate exposure in assessments of vulnerability to climate change, ignoring the two other components of vulnerability (sensitivity and adaptive capacity); (ii) treating climate change as a long-term, gradual threat without recognising that it will change the frequency and magnitude of climate extremes; (iii) treating climate change as a future threat, disregarding current impacts of existing change; and, (iv) focusing on direct impacts of climate change, ignoring its interactions with other threats. We describe the implications of these challenges and urge that establishing management objectives in relation to species' vulnerability is crucial for choosing effective and efficient conservation action.
Oceanic shelf sea fronts have significant effects on local dynamics, ecology and climate. An assessment of the impact of climate change on frontal positions and frontal gradients requires reliable reference data and the possibility to monitor oceanic fronts. Therefore, the development of algorithms which automatically detect frontal positions from Earth Observation (EO) data is an important tool to analyse long EO time series, i.e. to process big data volumes. The development of GRADHIST was driven by the need to generate a climatology for North Sea fronts. GRADHIST is a new algorithm for the detection and mapping of oceanic fronts, which is based on a combination and refinement of the gradient algorithm of Canny (1986) and the histogram algorithm of Cayula and Cornillon (1992). GRADHIST preserves the main principles of both algorithms and can be applied to various ocean parameters as well as to different sensors with very little effort. GRADHIST was validated and tested using both synthetic and real data and applied to sea surface temperature and ocean colour parameters retrieved from satellite data; i.e. data from MODIS (Moderate Resolution Imaging Spectroradiometer), MERIS (MEdium Resolution Imaging Spectrometer), AVHRR (Advanced Very High Resolution Radiometer) and AATSR (Advanced Along-Track Scanning Radiometer). Selected results and statistical analysis of a new North Sea climatology for oceanic fronts are presented and discussed.