Presentation on theme: "Lecture 2 review Maximizing long term harvest can generally be achieved by following a “fixed escapement” harvest rule WHICH BRINGS STOCK TO ITS MOST PRODUCTIVE."— Presentation transcript:
Lecture 2 review Maximizing long term harvest can generally be achieved by following a “fixed escapement” harvest rule WHICH BRINGS STOCK TO ITS MOST PRODUCTIVE SIZE AS QUICKLY AS POSSIBLE THEN HOLDS STOCK AT THAT SIZE Nearly the same long term harvest can be achieved by following a “fixed exploitation rate” rule, much less damaging to fishers Tactics for regulating harvest rates involve either input (effort) or output (catch) controls Output controls are dangerous and require accurate assessments of stock size Complex management objectives and performance measures are an invitation to gridlock in decision making
Limits to compensatory responses Most populations exhibit high juvenile survival at very low densities But occasionally (5-10%?) compensation fails at low densities, leading to low equilibrium or extinction N SJ N -Allee effect (eggs don’t get fertilized, eg scallops); rare -Cultivation/depensation (competitors/predators of juveniles increase when N is low, eg bass-bluegill) -Trophic cascades (green water/clear water states) -Botsford’s effect (size dependent cannibalism) (Invasive species have to exhibit this ability)
Life history trajectories Whenever you handle a fish, ALWAYS ask yourself these questions: –How old is it? –Where was it spawned? –Where will it spawn?
Life history stanzas (partitions of the life history trajectory) The eggie Larval drift, density- independent mortality Juvenile migration First juvenile nursery area: small, strong density-dependence in mortality Spread into larger juvenile nursery area(s), mortality much lower Adult foraging areas, most often with complex seasonal migration patterns Spawning migration Fractal, complex diurnal movement
Characteristics of LHT There is typically very strong selection for behaviors that take fish back to spawn in the places where they were successfully produced (this is not just a salmon thing) Seasonal migrations become more pronounced as fish grow Time Random model Distance from tagging site Migration model Distance from tagging site Time
Characteristics of LHT Natural mortality rates vary as M=k/(body length), starting at a few percent per day and often falling to a few percent per year Body growth typically follows a vonBertalanffy length curve of the form length=L [1-e -K(a-ao) ] Sometimes there is a “kink” in the growth curve, with small juveniles either showing extra fast growth (if they seek warm microhabitats) or extra slow growth (if they face very high predation risk).
Is the Beverton-Holt invariant M/K=1.6 a valid generalization for stock assessment?
Characteristics of LHT Maturation typically occurs at 50%-70% of maximum body length, with fecundity then being proportional to body weight But some fish like these New Zealand brown trout practically stop growing at maturity, and make massive (45%) investments in eggs (Hayes et al TAFS 2000)
Representing LHT in models Age structure accounting (block trajectory by even age intervals) Stanza structure accounting (Ecosim) Individual-based models (track movement) [N 1 N 2 N 3 …] t [N 1 N 2 N 3 …] t+1 (easy in spreadsheets) X,Y positions and fates of large sample of individuals
Ways to represent space in models Total areas by habitat class, without regard to spatial arrangement (A 1,A 2,…) Irregular spatial areas (“polygons”) Regular spatial cells (“rasters”) A1A1 A2A2
Spatial Management Dealing with complex dynamics
Spatial management is not just about MPAs Dynamic organization of shrimp fisheries: lessons for assessment, cooperative management Fishing for information: using logbook data to understand spatial stock structure and opportunities for more selective fishing practices Methods for modeling spatial stock dynamics
Contrasting management regimes St. Vincent Gulf (collapsed) –Ethnic fishery –Combative participants, severe misreporting –Assessments based on simple catch-effort relationships Spencer Gulf (sustained) –Cohesive fishing communities –Neil Carrick: dogged persistence, many bar fights to develop cooperative approach –Regulatory structure based on adaptive fishing policy (time-area closures) based on repeated surveys and openings each year
Assessment modeling options Empirical approach: fishing for information to map stock distribution and abundance several times during each season, cpue-based rule for ending annual fishery before depletion of spawning stock “Mechanistic” approach: develop detailed spatial model of physical drivers (currents, temperature, salinity), predict prawn recruitment, survival, movement (The mechanistic approach led to very costly research and modeling, never worked)
Multispecies fisheries: tradeoffs caused by technical interactions so some stocks overfished at MSY Skeena River sockeye salmon example: many stocks overfished at F msy
Selective fishing practices to achieve variable F targets over species Most common: forced discarding of sensitive species (e.g. escape ramps for dolphins) Modification of gear deployment (e.g. bait types, set depths, mesh sizes, escape gaps and grids) Selective space-time openings (e.g. salmon)
Temporal selectivity: Skeena River gillnet fishery example
Spatial selectivity Use detailed logbook and survey data to map species distributions, identify areas of high overlap and/or density of sensitive species (e.g. Fishmap) Adaptive spatial closures based on the mapping (e.g. Carrick’s shrimp fishery) Also use the mapping to develop “folly- fantasy” spatial cpue indices for long-term stock assessment
Partial separations in spatial distributions, BC trawl fishery Sensitive species (longspine rockfish, Fmsy=0.05) Productive species (English sole, F msy =0.2)
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