Johanna J. Heymans

Network analysis of the South Florida Everglades graminoid marshes and comparison with nearby cypress ecosystems

Network analysis (NA) is used to compare two ecosystems with different spatial extents to understand the different patterns and dynamics that arise. NA allows one to study the system at different scales: At the level of bilateral interactions, input-output structure matrices are calculated to look at the direct and indirect effects that one flow has on another; at the functional level, the food web is mapped into a concatenated trophic chain, and all simple, directed biogeochemical cycles are identified and separated from the supporting dissipative flows; and at the systems level global variables describe the state of development of the total network. The systems in question are the Everglades graminoid marsh and the adjacent cypress swamp. The graminoid marsh is essentially a two-dimensional system, with reduced diversity of primary producers, and a more focussed dependency of higher trophic levels on one particular primary producer, the periphyton. Although the cypress swamp system contains most of the same flora and fauna as the graminoids, it extends into a third dimension, and contains additional forms of terrestrial vegetation that increase the diversity of primary production, and thereby the resilience of the ecosystem. The importance of detritus to both systems is marked, although recycling within detritus is far more important in the graminoids than in the cypress. The linkages to higher trophic levels are relatively fewer in the graminoids, and the diversity of interactions between the detritus and higher trophic levels is much higher in the cypress. Overall, the presence of a third dimension imparts diversity and resilience to the cypress system, although the faster turnover rates of the graminoids make them more productive.

A carbon flow model and network analysis of the northern Benguela upwelling system, Namibia

Abstract A carbon flow model was constructed of the northern Benguela upwelling ecosystem. The model consists of 22 living and two non-living compartments, depicting the biomass of each compartment and the rates of exchange between them. The only primary producer in this system is phytoplankton, whilst bacteria, heterotrophic microflagellates and microzooplankton form part of the microbial loop. Primary consumers include mesozooplankton, macrozooplankton and jellyfish, while the fish community consists of anchovy, pilchard, lanternfish, gobies, horse mackerel, hake, snoek, benthic feeding fish and other carnivorous fish. The top consumers are seabirds and seals. The primary production–zooplankton–pelagic fish–demersal fish energy flow pathway appears to dominate in this system, with jellyfish, pilchard and horse mackerel being the most important planktivores. Jellyfish appears to be an important component in the system due to its high biomass and consumption of about 10% of the primary production. Hake is the most important secondary consumer. The carbon flow model was analyzed by means of network analysis, and the results show a total system throughput of about 88897 mg C m −2 day −1 , a development capacity of 38 041 mg C m −2 day −1 , an ascendancy value of 17 313 mg C m −2 day −1 , that about 7% of the total system throughput is recycled on a daily basis, and that the internal relative ascendancy is about 44%. These results were compared to similar data from other systems such as the southern Benguela and the Peruvian upwelling systems.

Global Patterns in Ecological Indicators of Marine Food Webs: A Modelling Approach

Background Ecological attributes estimated from food web models have the potential to be indicators of good environmental status given their capabilities to describe redundancy, food web changes, and sensitivity to fishing. They can be used as a baseline to show how they might be modified in the future with human impacts such as climate change, acidification, eutrophication, or overfishing. Methodology In this study ecological network analysis indicators of 105 marine food web models were tested for variation with traits such as ecosystem type, latitude, ocean basin, depth, size, time period, and exploitation state, whilst also considering structural properties of the models such as number of linkages, number of living functional groups or total number of functional groups as covariate factors. Principal findings Eight indicators were robust to model construction: relative ascendency; relative overhead; redundancy; total systems throughput (TST); primary production/TST; consumption/TST; export/TST; and total biomass of the community. Large-scale differences were seen in the ecosystems of the Atlantic and Pacific Oceans, with the Western Atlantic being more complex with an increased ability to mitigate impacts, while the Eastern Atlantic showed lower internal complexity. In addition, the Eastern Pacific was less organised than the Eastern Atlantic although both of these systems had increased primary production as eastern boundary current systems. Differences by ecosystem type highlighted coral reefs as having the largest energy flow and total biomass per unit of surface, while lagoons, estuaries, and bays had lower transfer efficiencies and higher recycling. These differences prevailed over time, although some traits changed with fishing intensity. Keystone groups were mainly higher trophic level species with mostly top-down effects, while structural/dominant groups were mainly lower trophic level groups (benthic primary producers such as seagrass and macroalgae, and invertebrates). Keystone groups were prevalent in estuarine or small/shallow systems, and in systems with reduced fishing pressure. Changes to the abundance of key functional groups might have significant implications for the functioning of ecosystems and should be avoided through management. Conclusion/significance Our results provide additional understanding of patterns of structural and functional indicators in different ecosystems. Ecosystem traits such as type, size, depth, and location need to be accounted for when setting reference levels as these affect absolute values of ecological indicators. Therefore, establishing absolute reference values for ecosystem indicators may not be suitable to the ecosystem-based, precautionary approach. Reference levels for ecosystem indicators should be developed for individual ecosystems or ecosystems with the same typologies (similar location, ecosystem type, etc.) and not benchmarked against all other ecosystems.

Network analysis of the northern Benguela ecosystem by means of netwrk and ecopath

Abstract Two software packages are available to analyze ecosystems and to compute ecosystem variables: netwrk 4.2a and ecopath 4.0. A flow model of the northern Benguela ecosystem was used to compare the outputs from these two packages. The northern Benguela ecosystem is a sub-system of the Benguela upwelling ecosystem off the coast of Southern Africa. The food web used in this study consists of 24 compartments, of which 22 were living and two were non-living compartments. netwrk is a DOS-based package constructed in ‘FORTRAN’ by R.E. Ulanowicz, University of Maryland, in the late 1980s (updated in 1999 — version 4.2a), while ecopath is a Windows-based package written in ‘Visual Basic’ that uses the same methodologies as netwrk but whose algorithms have been programmed based on the original descriptions with some differences in interpretation. There are fundamental differences between the input methodologies of the two packages, which leads to differences in their output. netwrk takes the respiration of primary producers into consideration, while ecopath does not. This leads to various discrepancies in the calculation of throughput and all the parameters related to it, such as the ascendency and development capacity. In most cases, the differences are small enough that the interpretation of the results would bring the modeler to the same qualitative conclusion using ecopath or netwrk . However, the mixed trophic impacts, Lindeman spine, primary production required and Finn Cycling Index, are markedly different for the two models. It is concluded that consolidating these models would be of enormous value to ecosystem analysis.

Evaluating Network Analysis Indicators of Ecosystem Status in the Gulf of Alaska

This is the first study on the emergent properties for empirical ecosystem models that have been validated by time series information. Ecosystem models of the western and central Aleutian Islands and Southeast Alaska were used to examine indices of ecosystem status generated from network analysis and incorporated into Ecopath with Ecosim. Dynamic simulations of the two ecosystems over the past 40 years were employed to examine if these indices reflect the dissimilar changes that occurred in the ecosystems. The results showed that the total systems throughput (TST) and ascendancy (A) followed the climate change signature (Pacific decadal oscillation, PDO) in both ecosystems, whereas the redundancy (R) followed the inverse trend. The different trajectories for important species such as Steller sea lions (Eumetopias jubatus), Atka mackerel (Pleurogrammus monopterygius), pollock (Theragra chalcograma), herring (Clupea pallasii), Pacific cod (Gadus macrocephalus) and halibut (Hippoglossus stenolepis) were noticeable in the Finn cycling index (FCI), entropy (H) and average mutual information (AMI): not showing large change during the time that the Stellers sea lions, herring, Pacific cod, halibut and arrowtooth flounder (Atheresthes stomias) increased in Southeast Alaska, but showing large declines during the decline of Steller sea lions, sharks, Atka mackerel and arrowtooth flounder in the Aleutians. On the whole, there was a change in the emergent properties of the Aleutians around 1976 that was not seen in Southeast Alaska. Conversely, the emergent properties of both systems showed a change around 1988, which indicated that both systems were unstable after 1988.

Ecological Network Indicators of Ecosystem Status and Change in the Baltic Sea

Several marine ecosystems under anthropogenic pressure have experienced shifts from one ecological state to another. In the central Baltic Sea, the regime shift of the 1980s has been associated with food-web reorganization and redirection of energy flow pathways. These long-term dynamics from 1974 to 2006 have been simulated here using a food-web model forced by climate and fishing. Ecological network analysis was performed to calculate indices of ecosystem change. The model replicated the regime shift. The analyses of indicators suggested that the system’s resilience was higher prior to 1988 and lower thereafter. The ecosystem topology also changed from a web-like structure to a linearized food-web.

Ecosystem models of Northern British Columbia for the time periods 2000, 1950, 1900 and 1750

................................................................................................................. 4 Introduction........................................................................................................... 4 Model Groups......................................................................................................... 4 1) Sea Otters .............................................................................................................................. 4 2) Mysticetae ............................................................................................................................. 5 3) Odontocetae .......................................................................................................................... 5 4) Seals and sea lions ................................................................................................................ 5 5) Seabirds................................................................................................................................. 6 6) Transient (migratory) salmon............................................................................................... 6 7-8) Coho and chinook salmon ................................................................................................. 7 9-10) Juvenile and adult squid..................................................................................................8 11) Ratfish.................................................................................................................................. 9 12) Dogfish ................................................................................................................................ 9 13-14) Juvenile and adult pollock ........................................................................................... 10 15-16) Forage fish and eulachon.............................................................................................. 10 17-18) Juvenile and adult herring ............................................................................................11 19-20) Pacific ocean perch: juvenile and adult ........................................................................11 21) Inshore rockfish................................................................................................................. 12 22-23) Piscivorous rockfish: juvenile and adult ..................................................................... 12 24-25) Planktivorous rockfish: juvenile and adult.................................................................. 13 26-27) Juvenile and adult turbot (arrowtooth flounder)........................................................ 14 28-29) Juvenile and adult flatfish........................................................................................... 14 30-31) Juvenile and adult halibut ............................................................................................15 32-33) Juvenile and adult Pacific cod ......................................................................................15 34-35) Juvenile and adult sablefish ........................................................................................ 16 36-37) Juvenile and adult lingcod........................................................................................... 16 38) Shallow-water benthic fish ................................................................................................17 39) Skates .................................................................................................................................17 40-41) Large and small crabs .................................................................................................. 18 42) Commercial shrimp .......................................................................................................... 18 43-45) Epifaunal, infaunal carnivorous and detritivorous invertebrates............................... 18 46) Carnivorous jellyfish ......................................................................................................... 19 47-48) Euphausiids and copepods.......................................................................................... 19 49) Corals and sponges ...........................................................................................................20 Ecosystem Models of Northern BC, Past and Present, Page 2 50) Macrophytes ..................................................................................................................... 20 51) Phytoplankton................................................................................................................... 20 52) Discards ............................................................................................................................ 20 53) Detritus............................................................................................................................. 20 Balancing the Models ...........................................................................................20 Acknowledgements............................................................................................... 21 References............................................................................................................ 23 Appendices........................................................................................................... 24 Appendix A. Bycatch and discards ......................................................................................... 24 Appendix B. Parameter estimation..........................................................................................25 Appendix C. Parameters Used in models ............................................................................... 28 Appendix D. Diet matrices...................................................................................................... 29 Appendix E. Non-market prices ............................................................................................. 36 Appendix F. Landings..............................................................................................................37 Appendix G. Group definitions............................................................................................... 40 A Research Report from ‘Back to the Future: the Restoration of Past Ecosystems as Policy Goals for Fisheries’ Supported by the Coasts Under Stress ‘Arm 2’ Project A Major Collaborative Research Initiative of the Canadian Government 41 pages

The Impact of Subsidies on the Ecological Sustainability and Future Profits from North Sea Fisheries

Background This study examines the impact of subsidies on the profitability and ecological stability of the North Sea fisheries over the past 20 years. It shows the negative impact that subsidies can have on both the biomass of important fish species and the possible profit from fisheries. The study includes subsidies in an ecosystem model of the North Sea and examines the possible effects of eliminating fishery subsidies. Methodology/Principal Findings Hindcast analysis between 1991 and 2003 indicates that subsidies reduced the profitability of the fishery even though gross revenue might have been high for specific fisheries sectors. Simulations seeking to maximise the total revenue between 2004 and 2010 suggest that this can be achieved by increasing the effort of Nephrops trawlers, beam trawlers, and the pelagic trawl-and-seine fleet, while reducing the effort of demersal trawlers. Simulations show that ecological stability can be realised by reducing the effort of the beam trawlers, Nephrops trawlers, pelagic- and demersal trawl-and-seine fleets. This analysis also shows that when subsidies are included, effort will always be higher for all fleets, because it effectively reduces the cost of fishing. Conclusions/Significance The study found that while removing subsidies might reduce the total catch and revenue, it increases the overall profitability of the fishery and the total biomass of commercially important species. For example, cod, haddock, herring and plaice biomass increased over the simulation when optimising for profit, and when optimising for ecological stability, the biomass for cod, plaice and sole also increased. When subsidies are eliminated, the study shows that rather than forcing those involved in the fishery into the red, fisheries become more profitable, despite a decrease in total revenue due to a loss of subsidies from the government.

Ecopath Theory, Modeling, and Application to Coastal Ecosystems

Ecosystem models describe trophic interactions within the ecosystems and provide a good basis for studying the general patterns of ecological properties. Here, we review 75 Ecopath models of coastal ecosystems to describe and assess their structural and functional characteristics and to investigate the ecological roles of their main functional groups. The analysis highlights the influence of depth, latitude, and longitude on their main ecological properties; the importance of different ecosystem types in distinguishing different ecological features; and the influence of the total size of the modeled ecosystem on ecosystem properties, as bigger ecosystems include higher-trophic-level organisms such as highly mobile fish.

A risk-based approach to cumulative effect assessments for marine management

Marine ecosystems are increasingly threatened by the cumulative effects of multiple human pressures. Cumulative effect assessments (CEAs) are needed to inform environmental policy and guide ecosystem-based management. Yet, CEAs are inherently complex and seldom linked to real-world management processes. Therefore we propose entrenching CEAs in a risk management process, comprising the steps of risk identification, risk analysis and risk evaluation. We provide guidance to operationalize a risk-based approach to CEAs by describing for each step guiding principles and desired outcomes, scientific challenges and practical solutions. We reviewed the treatment of uncertainty in CEAs and the contribution of different tools and data sources to the implementation of a risk based approach to CEAs. We show that a risk-based approach to CEAs decreases complexity, allows for the transparent treatment of uncertainty and streamlines the uptake of scientific outcomes into the science-policy interface. Hence, its adoption can help bridging the gap between science and decision-making in ecosystem-based management.