Critical points in ecosystem responses to fishing and environmental pressures

Large, Scott I.; Fay, Gavin; Friedland, Kevin D.; Link, Jason S.

doi:10.3354/meps11165

Cited by 46 publications

(53 citation statements)

References 63 publications

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“…Elucidating critical points or thresholds in ecological responses to multiple stressors is a promising area of research for managing marine resources (e.g., Large et al 2015b), as is the application of non-linear dynamic models to characterize non-linearities, identify causal drivers, and forecast ecosystem conditions (e.g., Hsieh et al 2005, Sugihara et al 2012, Glaser et al 2014, Ye et al 2015. Considering non-linearities in management decisions, given their prevalence in the environment, is critical for successfully mitigating and responding and adapting to ecosystem change.…”

Section: Discussionmentioning

confidence: 99%

Characterizing driver-response relationships in marine pelagic ecosystems for improved ocean management

Hunsicker¹,

Kappel²,

Selkoe³

et al. 2015

Ecological Applications

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Scientists and resources managers often use methods and tools that assume ecosystem components respond linearly to environmental drivers and human stressor. However, a growing body of literature demonstrates that many relationships are non-linear, where small changes in a driver prompt a disproportionately large ecological response. Here we aim to provide a comprehensive assessment of the relationships between drivers and ecosystem components to identify where and when non-linearities are likely to occur. We focus our analyses on one of the best-studied marine systems, pelagic ecosystems, which allowed us to apply robust statistical techniques on a large pool of previously published studies. In this synthesis, we (1) conduct a wide literature review on single driver-response relationships in pelagic systems, (2) use statistical models to identify the degree of non-linearity in these relationships, and (3) assess whether general patterns exist in the strengths and shapes of non-linear relationships across drivers. Overall we found that non-linearities are common in pelagic ecosystems, comprising at least 52% of all driver-response relationships. This is likely an underestimate, as papers with higher quality data and analytical approaches reported non-linear relationships at a higher frequency -on average 11% more. Consequently, in the absence of evidence for a linear relationship, it is safer to assume a relationship is non-linear. Strong non-linearities can lead to greater ecological and socio-economic consequences if they are unknown (and/or unanticipated), but if known they may provide clear thresholds to inform management targets. In pelagic systems, strongly non-linear relationships are often driven by climate and trophodynamic variables, but are also associated with local stressors such as overfishing and pollution that can be more easily controlled by managers. Even when marine resource managers cannot influence 3 ecosystem change, they can use information about threshold responses to guide how other stressors are managed and to adapt to new ocean conditions. As methods to detect and reduce uncertainty around threshold values improve, managers will be able to better understand and account for ubiquitous non-linear relationships.

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Section: Discussionmentioning

confidence: 99%

Characterizing driver-response relationships in marine pelagic ecosystems for improved ocean management

Hunsicker¹,

Kappel²,

Selkoe³

et al. 2015

Ecological Applications

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“…This range is determined to be where an anticipated ecosystem shift could occur. Detailed description of these methods can be found in Ellis et al (2012), Baker and Hollowed (2014), and Large et al (2015a).…”

Section: Gradient Forest Analysismentioning

confidence: 99%

“…DFA is a multivariate technique used to identify, detect common patterns in a set of time series (Zuur et al, 2003a,b). We considered two structures for the error covariance matrix R: (1) diagonal and equal and (2) diagonal and unequal (Zuur et al, 2003b;Large et al, 2015a). Diagonal and equal covariance matrices consider the same process variance across all-time series, while diagonal and unequal covariance matrices consider unique variance values for each time series.…”

Section: Generalized Additive Modelsmentioning

confidence: 99%

“…There is a convergence of knowledge in multiple disciplines (social sciences, economics, ecology, oceanography) in current EBM research that aims to quantify this socio-ecological "sweet spot" (Levin et al, 2009;Link, 2010;Samhouri et al, 2012). While there is a great deal of interdisciplinary work being done in marine ecosystem science, there is a relatively limited set of comparative studies of ecosystem-level trends and thresholds-based reference points (e.g., Murawski et al, 2010;Samhouri et al, 2010Samhouri et al, , 2017Large et al, 2013Large et al, , 2015aFoley et al, 2015;Link et al, 2015;Connell et al, in press) which are required to fully assess the ability of ecosystem science to effectively manage large marine ecosystems.…”

Section: Introductionmentioning

confidence: 99%

“…More recently, there has been a shift toward thresholds-based reference points as an alternative to traditionally developed baselines (Samhouri et al, 2010;Large et al, 2013Large et al, , 2015aFoley et al, 2015). Thresholds are derived from pressure-response relationships and are akin to LD 50 in toxicology studies where at some point along a pressure gradient (chemical or otherwise) organisms experience a median negative impact (Samhouri et al, 2010).…”

Section: Introductionmentioning

confidence: 99%

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Comparing Apples to Oranges: Common Trends and Thresholds in Anthropogenic and Environmental Pressures across Multiple Marine Ecosystems

et al. 2017

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Ecosystem-based management (EBM) in marine ecosystems considers impacts caused by complex interactions between environmental and anthropogenic pressures (i.e., oceanographic, climatic, socio-economic) and marine communities. EBM depends, in part, on ecological indicators that facilitate understanding of inherent properties and the dynamics of pressures within marine communities. Thresholds of ecological indicators delineate ecosystem status because they represent points at which a small increase in one or many pressure variables results in an abrupt change of ecosystem responses. The difficulty in developing appropriate thresholds and reference points for EBM lies in the multidimensionality of both the ecosystem responses and the pressures impacting the ecosystem. Here, we develop thresholds using gradient forest for a suite of ecological indicators in response to multiple pressures that convey ecosystem status for large marine ecosystems from the US Pacific, Atlantic, sub-Arctic, and Gulf of Mexico. We detected these thresholds of ecological indicators based on multiple pressures. Commercial fisheries landings above approximately 2-4.5 t km −2 and fisheries exploitation above 20-40% of the total estimated biomass (of invertebrates and fish) of the ecosystem resulted in a change in the direction of ecosystem structure and functioning in the ecosystems examined. Our comparative findings reveal common trends in ecosystem thresholds along pressure gradients and also indicate that thresholds of ecological indicators are useful tools for comparing the impacts of environmental and anthropogenic pressures across multiple ecosystems. These critical points can be used to inform the development of EBM decision criteria.

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