Patterns and driv erns and drivers o ers of r f resilience in - - PowerPoint PPT Presentation

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Patterns and driv erns and drivers o ers of r f resilience in - - PowerPoint PPT Presentation

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Patterns and driv erns and drivers o ers of r f resilience in esilience in over er-fished popula -fished populations tions Philipp Neubauer background Fisheries ecologist & modeler @ Dragonfly Science, Wellington, New Zealand

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Patterns and driv erns and drivers o ers of r f resilience in esilience in

  • ver

er-fished popula

  • fished populations

tions

Philipp Neubauer

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…background…

Fisheries ecologist & modeler @ Dragonfly Science, Wellington, New Zealand Research interest in the ecology of exploited marine populations and ecosystems Bayesian methods in ecology and fisheries

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  • 1. Of Stock declines…
  • 2. …and recoveries
  • 3. Patterns and drivers of resilience
  • 4. (Some) Limits of resilience
  • 5. Resilient fisheries
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Of stock declines…

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Some places were intensely fished by the early 1800s

  • the North Sea
  • Mediterranean
  • New England
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By the late 19th/early 20th century, some stocks were already quite heavily exploited:

  • North Sea herring
  • Atlantic Halibut & Cod
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Costello ¡et ¡al. ¡ 2012 ¡-­‑ ¡Science ¡

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1 ¡Worm ¡et ¡al ¡2009 ¡– ¡Science ¡ 2 ¡ <0.2x Target Biomass (@MSY) ¡

Where are we today?

An estimated 15% of assessed fished stocks are collapsed2 Around 2/3 of global (assessed) fisheries are below target biomass levels1 Fishing mortality (F) is declining in many parts of the world, but often still too high

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Trends

Costello ¡et ¡al. ¡ 2012 ¡-­‑ ¡Science ¡

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…and recoveries

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Many well known depletions and subsequent recoveries: e.g., North Sea Herring

Stocks can recover

ICES ¡advice ¡2013 ¡

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Many well known depletions and subsequent recoveries: e.g., North Sea Herring

Stocks can recover

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Many well known depletions and subsequent recoveries: e.g., North Sea Herring

Stocks can recover

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Elsewhere - depletions and subsequent recoveries: Western Hoki in New Zealand

Depletions and recoveries…

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A notorious depletions without recovery: North West Atlantic Cod

…but some stocks defy simple models

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…too simplistic?

Hutchings ¡2000 ¡– ¡Nature ¡ Hutchings ¡2001 ¡– ¡J.Fish.Bio ¡

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What could be missing?

Allee effects/depensation

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Cultivation/Depensation

Walters ¡& ¡Kitchell ¡2001 ¡-­‑ ¡CJFAS ¡

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Predator trap

Swain ¡& ¡Benoit ¡2015 ¡– ¡MEPS ¡

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1 ¡Jorgensen ¡et ¡al. ¡2007 ¡– ¡Science, ¡2 ¡Pinsky ¡& ¡Palumbi ¡2014– ¡Molecular ¡EvoluQon ¡

Impacts beyond just reduction in abundance Selective fishing alters the age and size structure of fished populations Fishing exerts selective pressure & reduces genetic diversity – a Darwinian debt?1,2

What could be missing?

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Resilience: Ability of populations to recover from low biomass

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How resilient are fish stocks to

  • ver-fishing?
  • r

How predictable are recoveries?

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Data

RAM Legacy Stock Assessment Database: over 360 stock assessments from around the globe

Ricard ¡et ¡al. ¡2012 ¡– ¡Fish ¡& ¡Fisheries ¡

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Data

RAM Legacy Stock Assessment Database: over 360 stock assessments from around the globe 153 stocks that had been depleted at least

  • nce to below 0.5x target (MSY)

Survival analysis of overfished stocks: Does

  • es
  • verfishing r

erfishing reduce popula educe population r tion resilience? esilience?

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Bayesian surviv survival- al-analysis analysis regression model of time-t time-to-

  • reco

ecovery: ery: Assumes tha Assumes that biomass dynamics f t biomass dynamics follow a st

  • llow a stochastic pr
  • chastic process
  • cess

Which leads t hich leads to in in

  • in inverse-Gaussian model f

erse-Gaussian model for r

  • r reco

ecovery times ery times

Overfished stocks as sick patients

c'= f (Bmin,...) ν'= f (F /Fmsy,....)

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Bayesian surviv survival- al-analysis analysis regression model of time-t time-to-

  • reco

ecovery ery. . Survival analysis: Will the patient (stock) survive the illness (collapse), how long will he take to heal (recover) and why ?

Overfished stocks as sick patients

F/FMSY ¡ B/BMSY ¡ Year ¡

1964 ¡ 2006 ¡

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Bayesian surviv survival- al-analysis analysis regression model of time-t time-to-

  • reco

ecovery ery Survival analysis: Will the patient (stock) survive the illness (collapse), how long will he take to heal (recover) and why ? Includes covariates for management, life-history and exploitation history Allowed us to estimate the effect of covariates on median recovery times and the probability of recovery within a given timeframe

Overfished stocks as sick patients

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Patterns and drivers of resilience

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Responsible and responsive management is key to building resilience and recovering

  • verfished

populations

Collapsed ¡ Depleted ¡ Adapted ¡from ¡Neubauer ¡et ¡al. ¡2013 ¡Science ¡

Drivers of resilience

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Examples

EA Bluefin Tuna Irish Sea Cod GB Halibut

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Recovery is accelerated for moderately high historical fishing regimes Negative impacts

  • f fishing only for

very long and intense fishing regimes

High ¡F ¡ Moderate ¡F ¡ Adapted ¡from ¡Neubauer ¡et ¡al. ¡2013 ¡Science ¡

Drivers of resilience

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Adapted ¡from ¡ ¡Eikeset ¡et ¡al. ¡2013 ¡– ¡PNAS, ¡

Phenotypic plasticity and fishery induced evolution can increase the productivity of fished populations

Explanations?

Age ¡& ¡Length ¡at ¡ MaturaQon ¡ Fishery ¡Induced ¡ evoluQon ¡ Phenotypic ¡ plasQcity ¡only ¡

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Time ¡ ProducQvity ¡

Phenotypic plasticity and fishery induced evolution can increase the productivity of fished populations

Age ¡& ¡Length ¡at ¡ MaturaQon ¡ Fishery ¡Induced ¡ evoluQon ¡ Phenotypic ¡ plasQcity ¡only ¡

Explanations?

Adapted ¡from ¡ ¡Eikeset ¡et ¡al. ¡2013 ¡– ¡PNAS, ¡

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(Some) Limits of resilience

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Importance of age/size structure

Shelton ¡et ¡al. ¡2010 ¡-­‑ ¡CJFAS ¡

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Adverse environments

Vert-­‑Pre ¡et ¡al. ¡2013 ¡– ¡PNAS ¡

Over-fished stocks can fall into the environmental trap

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Increases in productivity could lead to unstable (nonlinear) population dynamics

Limits of resilience

Anderson ¡et ¡al ¡2008 ¡– ¡Nature ¡

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Resilient Fisheries

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Precautionary fishing mortality rates limit ecosystem wide risks of over-fishing

Building resilience

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Adapted ¡from ¡Worm ¡et ¡al. ¡2009 ¡– ¡Science ¡

New ¡ ¡Target ¡ Old ¡ ¡Target ¡ Old ¡ ¡PracQce… ¡

Building resilience

Precautionary fishing mortality rates limit ecosystem wide risks of over-fishing

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Precautionary fishing mortality rates limit ecosystem wide risks of over-fishing Maintaining age/size structure to maintain reproductive and adaptive potential Acknowledging environmentally/climate driven variability in demographic rates, adjust management advice accordingly

Building resilience

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How resilient are ecosystems to over-fishing? How does fishing alter ecosystem responses and resilience to climate change?

Marsden Questions

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Acknowledgements ¡

NSF/NOAA ¡CAMEO ¡grant ¡ Olaf ¡Jensen, ¡Jensen ¡lab ¡group, ¡Malin ¡Pinsky ¡ Ken ¡Andersen ¡& ¡Nis ¡Jakobsen ¡ ¡