Prediction, precaution, and policy under global change

Schindler, Daniel E.; Hilborn, Ray

doi:10.1126/science.1261824

Cited by 235 publications

(191 citation statements)

References 22 publications

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“…If management actively suppresses this variation, then opportunities for learning are lost. Thus, management by the precautionary principle constrains variation in a narrow range and thereby suppresses learning (5,16).…”

Section: Discussionmentioning

confidence: 99%

“…Stability may be sought by constraining harvest or pollutant impacts or by establishing protected reserves that isolate ecosystems from particular types of disturbance. The precautionary principle moderates variability by limiting human actions to those that have succeeded in the past (16). A contrasting view notes that ecosystems in constant environments may be vulnerable to novel disturbances.…”

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confidence: 99%

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Allowing variance may enlarge the safe operating space for exploited ecosystems

Carpenter

Brock

Folke

et al. 2015

Proc. Natl. Acad. Sci. U.S.A.

109

106

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Variable flows of food, water, or other ecosystem services complicate planning. Management strategies that decrease variability and increase predictability may therefore be preferred. However, actions to decrease variance over short timescales (2-4 y), when applied continuously, may lead to long-term ecosystem changes with adverse consequences. We investigated the effects of managing short-term variance in three well-understood models of ecosystem services: lake eutrophication, harvest of a wild population, and yield of domestic herbivores on a rangeland. In all cases, actions to decrease variance can increase the risk of crossing critical ecosystem thresholds, resulting in less desirable ecosystem states. Managing to decrease shortterm variance creates ecosystem fragility by changing the boundaries of safe operating spaces, suppressing information needed for adaptive management, cancelling signals of declining resilience, and removing pressures that may build tolerance of stress. Thus, the management of variance interacts strongly and inseparably with the management of resilience. By allowing for variation, learning, and flexibility while observing change, managers can detect opportunities and problems as they develop while sustaining the capacity to deal with them.adaptive management | critical transition | ecosystem | resilience | variance

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Section: Discussionmentioning

confidence: 99%

mentioning

confidence: 99%

Allowing variance may enlarge the safe operating space for exploited ecosystems

Carpenter

Brock

Folke

et al. 2015

Proc. Natl. Acad. Sci. U.S.A.

109

106

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“…probabilistic ensembles to help bridge the gap between research and policymaking (25)(26)(27)(28)(29). Our work advances that goal by formally propagating model uncertainty into our ensemble predictions to allow for quantitative risk assessment and policies that are robust within realistic uncertainty ranges.…”

Section: Significancementioning

confidence: 99%

Ensemble modeling informs hypoxia management in the northern Gulf of Mexico

Scavia

Bertani

Obenour

et al. 2017

Proc. Natl. Acad. Sci. U.S.A.

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A large region of low-dissolved-oxygen bottom waters (hypoxia) forms nearly every summer in the northern Gulf of Mexico because of nutrient inputs from the Mississippi River Basin and water column stratification. Policymakers developed goals to reduce the area of hypoxic extent because of its ecological, economic, and commercial fisheries impacts. However, the goals remain elusive after 30 y of research and monitoring and 15 y of goal-setting and assessment because there has been little change in river nitrogen concentrations. An intergovernmental Task Force recently extended to 2035 the deadline for achieving the goal of a 5,000-km 2 5-y average hypoxic zone and set an interim load target of a 20% reduction of the spring nitrogen loading from the Mississippi River by 2025 as part of their adaptive management process. The Task Force has asked modelers to reassess the loading reduction required to achieve the 2035 goal and to determine the effect of the 20% interim load reduction. Here, we address both questions using a probabilistic ensemble of four substantially different hypoxia models. Our results indicate that, under typical weather conditions, a 59% reduction in Mississippi River nitrogen load is required to reduce hypoxic area to 5,000 km 2 . The interim goal of a 20% load reduction is expected to produce an 18% reduction in hypoxic area over the long term. However, due to substantial interannual variability, a 25% load reduction is required before there is 95% certainty of observing any hypoxic area reduction between consecutive 5-y assessment periods.ensemble modeling | hypoxia | Gulf of Mexico | nitrogen-loading targets A large region of low-dissolved-oxygen (DO) bottom waters (hypoxia; DO < 2 mg·L −1 ) has formed nearly every summer in the Gulf of Mexico for at least the last three decades (1-3). Hypoxia forms because of respiration of organic matter in bottom waters and a vertically stratified water column restricting reaeration (4-6). Both factors are related to the outflow of freshwater and nutrients from the Mississippi River Basin, which typically peaks in March through May. Nutrients stimulate phytoplankton production, much of which settles in early summer, and bottom water DO (BWDO) is consumed during its decomposition. River outflows create a fresher, warmer surface layer above a colder, saltier bottom layer, limiting the vertical diffusion of DO (2).Policymakers developed hypoxia reduction goals because of ecological, economic, and commercial fisheries impacts (7-10). However, the goals remain elusive after >30 y of research and monitoring (3, 11) and >15 y of assessment and goal-setting (5, 12-16). A Gulf Task Force recently agreed to retain the 5-y moving average goal of a 5,000-km 2 hypoxic zone, but extended the deadline from 2015 to 2035 (17). The timeframe was reset because the 2015 hypoxic zone was 16,760 km 2 and the most recent 5-y average was 14,024 km 2 -greater than the long-term average of 13,751 km 2 (1). Missing the goal was not unexpected because the 5-y average load of late sp...

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“…Coping with such fundamental sources of unpredictability requires alternative modelling strategies that go beyond traditional approaches [6,21]. One set of such strategies focuses on early warning signs that attempt to detect abrupt transitions based on the statistical properties of the observed time series without requiring any mechanistic model [12].…”

Section: Introductionmentioning

confidence: 99%

Elevated nonlinearity as an indicator of shifts in the dynamics of populations under stress

Dakos

Glaser

Hsieh

et al. 2017

J. R. Soc. Interface.

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Populations occasionally experience abrupt changes, such as local extinctions, strong declines in abundance or transitions from stable dynamics to strongly irregular fluctuations. Although most of these changes have important ecological and at times economic implications, they remain notoriously difficult to detect in advance. Here, we study changes in the stability of populations under stress across a variety of transitions. Using a Ricker-type model, we simulate shifts from stable point equilibrium dynamics to cyclic and irregular boom-bust oscillations as well as abrupt shifts between alternative attractors. Our aim is to infer the loss of population stability before such shifts based on changes in nonlinearity of population dynamics. We measure nonlinearity by comparing forecast performance between linear and nonlinear models fitted on reconstructed attractors directly from observed time series. We compare nonlinearity to other suggested leading indicators of instability (variance and autocorrelation). We find that nonlinearity and variance increase in a similar way prior to the shifts. By contrast, autocorrelation is strongly affected by oscillations. Finally, we test these theoretical patterns in datasets of fisheries populations. Our results suggest that elevated nonlinearity could be used as an additional indicator to infer changes in the dynamics of populations under stress.

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Prediction, precaution, and policy under global change

Abstract: Emphasize robustness, monitoring, and flexibility

Cited by 235 publications

References 22 publications

Allowing variance may enlarge the safe operating space for exploited ecosystems

Allowing variance may enlarge the safe operating space for exploited ecosystems

Ensemble modeling informs hypoxia management in the northern Gulf of Mexico

Elevated nonlinearity as an indicator of shifts in the dynamics of populations under stress

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