A Statistical Test of Network Analysis: Can it Detect Differences in Food Web Properties?

The non-negligible contribution of foundation species to artificial reef construction revealed by Ecopath models

The seabed desertification has increasingly highlighted the importance of benthic habitat restoration. Strategically engineered artificial reefs emerges as pivotal in achieving restoration objectives. However, the significant influence of foundation species on biotic components and ecosystem attributes within diverse artificial reefs has been underrecognized. This study collated twenty Ecopath models of artificial reefs and their corresponding natural control ecosystems along the coasts of the Yellow Sea and Bohai Sea, China, categorizing them into five distinct system types predicated on the biomass and productivity of foundational species. Our results suggest that dimensionless indices, rather than actual system values, were posited to facilitate inter-comparative analysis. The comparative analysis revealed differences in biomass distribution, energy utilization, and trophic structure across the five ecosystem types. All the artificial reef systems collectively enhanced the utilization of primary production. Foundation species components formed the cornerstone of system functionality, significantly impacting ecosystem stability through modulation of energy flow dynamics. Distinct impacts were observed from shellfish and macroalgae; the former augmenting the detrital food chain, while the latter bolstering the grazing food chain. Consequently, the model-based integrated analysis enabled a robust comparison among various types of artificial reef ecosystems and confirmed that promoting the colonization of foundation species was a non-negligible factor in the design and deployment of artificial reefs.

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.