The impact of various anthropogenic activities and other drivers that influence the spatial distribution of organisms in the system can be assessed through Ecospace to understand their ecosystem-wide effects. Similarly to other impact assessment tools (e.g., Halpern et al., 2007; Halpern and Fujita, 2013; Hammar et al., 2020), formulating the representation of impacts undergoes a stepwise approach:

1. identification of a set of potentially impacting activities (e.g., windfarm construction, artificial reef placements, aquaculture settings);
2. translation of each activity into corresponding stressors, for example noise (Harvey, 2018; Serpetti et al., 2021), bottom disturbance (Steenbeek et al., 2020) or nutrients release (Piroddi et al., 2011);
3. condensation of the multiple stressors into a ‘cumulative impact’ metric; and
4. quantification of each stressor effect, or of the cumulative impact metric, on determinate species or for the whole ecosystem, in a determinate area.

In Ecospace, a straightforward approach for including spatially explicit, and time dynamic, cumulative impacts is through the HFC model (section 1.5.1). Layers of stressors, at the same spatial resolution of the model, are loaded and associated to functional groups through response curves, in the same way as environmental drivers such as depth or temperature.

When multiple stressors occur in an individual cell, the cumulative impact is represented as the product of the individual stressors (Christensen et al., 2014). Predator-prey interactions can buffer or enhance the effects of stressors: for example, in an area closed to fisheries due to another human activity (e.g. a wind farm and aquaculture site), cetaceans could be displaced by the negative effect of the stressor “noise”, but attracted due to increasing food availability driven by the fishing closure and the locally higher primary productivity (Serpetti et al., 2021). The actual emerging net effect is thus dependent on the cumulative effect of multiple stressors on the prey and on the predator, as well as on other dynamics (fishing, protection, environmental drivers), resulting in complex and in some cases counterintuitive dynamics (Wedding et al., 2022).

The application of multiple pressures can be particularly important when assessing Marine Spatial Planning options and trade-offs, and the effects of de facto MPAs driven by e.g., renewable energy installation (e.g., Alexander et al., 2016; Nogues et al., 2022, 2021; Serpetti et al., 2021; Steenbeek et al., 2020). Ecospace can provide a support platform that enables tracking the effects of impacts on each trophic group and its propagation through the food web: this is a great added value compared to other spatially explicit tools for cumulative impact assessment (Depellegrin et al., 2021), which mostly address direct effects of stressors on ecosystem components, and do not consider trophic dynamics.

It is important to note that simulation of impacts through the HFC model has the effect of changing habitat suitability, thus the feeding ability, which changes cell suitability. This, in turn, increases the chance that groups relocate to nearby areas that are more suitable. Survival is affected when groups cannot relocate fast enough to keep up with changing environmental conditions. The HFC model is less efficient in capturing direct localized mortality events such as harmful algal blooms, hypoxia, temperature extremes, pollution, or mortality associated with shipping and other destructive anthropogenic activities. In these cases, a different solution has been recently provided through direct influence of natural mortality (Section 6.6). In EwE version 6.6 mortality response curves can be included to describe the proportion of biomass killed in each grid cell as a function of the stressor value in that cell (e.g., contaminant concentration, temperature, dissolved oxygen, Vilas et al. 2020), or by knowing the probability of the occasional event occurring (e.g., co-occurrence within cetaceans and shipping tracks and the probability of a fatal collision, Harvey 2018). However, long-term impacts of e.g., persistent pollutants within the organisms might not be well captured by the habitat capacity model if the mortality associated with specific concentrations of these pollutants is not incorporated in the model.

The assessment of the ecosystem effects of cumulative human activities is a challenging scientific task. Many studies have considered the impact of fishing activities and a second or even a third factor (such as eutrophication, pollution, aquaculture, loss of habitat, climate change, or invasive species), mostly using time-dynamic modeling (Ainsworth et al., 2011; Booth and Zeller, 2005; Corrales et al., 2018; Guénette et al., 2006; Serpetti et al., 2017). The assessment of cumulative impacts using spatial-temporal dynamic modeling is growing but has thus far been limited by the original configuration of Ecospace. Recent developments in Ecospace are allowing an exponential increase in such applications (see section 6.)

Adaption

The chapter is in part adapted, with permission,  from:

De Mutsert K, Marta Coll, Jeroen Steenbeek, Cameron Ainsworth, Joe Buszowski, David Chagaris, Villy Christensen, Sheila J.J. Heymans, Kristy A. Lewis, Simone Libralato, Greig Oldford, Chiara Piroddi, Giovanni Romagnoni, Natalia Serpetti, Michael Spence, Carl Walters. 2023. Advances in spatial-temporal coastal and marine ecosystem modeling using Ecopath with Ecosim and Ecospace. Treatise on Estuarine and Coastal Science, 2nd Edition. Elsevier.