11/11/2018 Stock Assessment Workshop 19th June -25th June 2008 SPC Headquarters Noumea New Caledonia

Day 1 Session 2 Fish and “fished” populations – basic principles 11/11/2018 Day 1 Session 2 Fish and “fished” populations – basic principles

11/11/2018 “To understand how populations will respond to exploitation, we need to appreciate how they will behave when unexploited.” Hillborn and Walters, 1992

What is a population? Does it differ from a stock? 11/11/2018 Key Definitions What is a population? Does it differ from a stock? Definition and use of terms “population” and “stock” tends to be a bit rubbery in fisheries science…..often taken to mean the same thing, however….. Population: A group of individuals of the same species living in the same area at the same time and sharing a common gene pool, with little or no immigration/emmigration Stock: 1. The part of a fish population which is under consideration from the point of view of actual or potential utilization. Ricker W.E. (1975) 2. A group of fish of one species which shares common ecological and genetic features. The stocks defined for the purposes of stock assessment and management do not necessarily coincide with self-contained population. Restrepo V. (1999)

Industrialised fishing 11/11/2018 Examples of natural variation in populations over time – non fisheries data Industrialised fishing

Session overview Fish populations 11/11/2018 Session overview Fish populations Life cycles and life history strategies Basic population dynamic – recruitment, natural mortality and growth Simple population models Movement, physiology and the environment Fished populations Adding “fishing mortality” to the population dynamics equation Natural variability v fishing based impacts Behaviour of exploited stocks Stability, instability, cyclicity, resilience, Boundaries and regime shifts Overfishing Growth overfishing Recruitment overfishing 5. “Fished” population models

Tuna Life cycle Adults Eggs Larvae Juvenile stages 11/11/2018 Tuna Life cycle Adults Spawning and fertilisation Maturation Eggs Hatching Larvae Juvenile stages

Variations in fish life cycles 11/11/2018 Variations in fish life cycles Within this basic strategy there is some variation, even across large pelagic species taken by tuna fisheries. Two well known species groups with very contrasting life histories are the tunas and sharks. Big implications for population dynamics and for resilience to fishing. 107 Sharks (generalised) Tuna (generalised) 106 Eggs/Larvae 105 Juveniles Adults Numbers 104 103 102 101 Days Months Years

Basic population dynamics 11/11/2018 Basic population dynamics We’ve seen that life history strategies vary between species, but within species, what are the processes that drive population fluctuations? Closed animal population (no immigration or emmigration) Population Size (numbers of individuals) Births Deaths (Natural mortality) Nt+1 = Number of animals in one year, Nt = Current Number of animals; B= Births after one year M = Deaths after one year. Nt+1=Nt+B-M

Basic population dynamics 11/11/2018 Basic population dynamics Biomass model Closed population (no immigration or emmigration) with no fishing Recruitment Death (Natural mortality) Biomass Growth

Basic population dynamics 11/11/2018 Basic population dynamics Bt+1=Bt+R+G-M Bt+1 = Biomass of fish in one year, Bt = Current biomass; R= Biomass of new recruits in one years time, G= Additional biomass due to growth of current fish M = Biomass of fish from current population that died. Each of the processes of recruitment, growth and mortality, are effected by numerous factors, both endogenous (relating to the fishes genetics, physiology and behaviour) and exogenous (determined by the fishes environment and external influencing factors) We need to understand these factors to create realistic population models

11/11/2018 Bt+1=Bt+R+G-M Recruitment (R) Recruitment is a bit of a rubbery concept….the point at which one considers a fish “recruited” is often determined by the point at which individuals can be detected ie counted or estimated Recruitment definitions: 1. For demographic purposes recruitment refers to the maturing of individuals into the adult age classes (Valiela, 1995) 2. In fishery publications, recruitment is defined as the appearance of a cohort into the catch due to it becoming of a size vulnerable to the fishery.” (Valiela, 1995) 3. The population still alive at any specified time after the egg stage (Haddon, 1997) 4. The number of fish [of a cohort] alive in a population at any arbitrarily defined point in time after the subsidence of initial high mortality (Rothschild, 1987)

Spawning and fertilisation 11/11/2018 Bt+1=Bt+R+G-M Recruitment (R) What are the processes that effect recruitment? Firstly, we need to remind ourselves of the stages leading from when an adult population spawns, to individuals from that spawning event/year entering (recruiting to) the adult population. What factors influence the production of eggs, and the probability of progression through each of the subsequent stages?? Adult production of gametes Spawning and fertilisation Larval development within eggs Hatching Larval stage Metamorphosis Juvenile stage Maturation Adult phase

Spawning and fertilisation 11/11/2018 Bt+1=Bt+R+G-M Recruitment (R) Processes that effect larval and juvenile survival Biotic (e.g.) Starvation/Competition Predation/Cannabalism Disease Abiotic (e.g.) Temperature Salinity Oxygen Small variations in survival = big variations in recruitment *Age to maturity also important for total egg production rate by population Adult production of gametes Spawning and fertilisation Larval development within eggs Hatching Larval stage Metamorphosis Juvenile stage Maturation Adult phase

Spawning and fertilisation 11/11/2018 Bt+1=Bt+R+G-M Recruitment (R) Processes that effect egg production, condition and survival Fecundity Adult condition Environment Adult production of gametes Spawning and fertilisation Larval development within eggs Hatching Larval stage Metamorphosis Juvenile stage Maturation Adult phase

Recruitment (R) In summary… 11/11/2018 Bt+1=Bt+R+G-M Recruitment (R) In summary… Many different factors can impact the survival of marine fish at any of the different stages in the recruitment process…. So…. How do we measure recruitment? Sampling regimes targeted at juveniles. Size specific indices of abundance from catch/effort data. Assume a relationship with adult stock size Where information pertaining to 1 and 2 above aren’t available, scientists require a predictive relationship that is based on other available data. The most commonly used, and debated, of these, is the stock-recruitment relationship.

Recruitment (R) The Stock-Recruitment Relationship Two theories 11/11/2018 Bt+1=Bt+R+G-M Recruitment (R) The Stock-Recruitment Relationship Two theories 1. Recruitment is density dependant, i.e. is dependant on the stock size. 2. Recruitment is density independant, i.e. is independant of the stock size The latter theory was once very popular due to a lack of correlation in plotted relationships (and previously discussed impacting factors) Bigeye tuna Yellowfin tuna

Recruitment (R) Stock-Recruitment Curves – Basic Properties 11/11/2018 Bt+1=Bt+R+G-M Recruitment (R) Stock-Recruitment Curves – Basic Properties Key point – SRR can vary depending on species. Density Independance Compensation Depensation Recruitment Recruitment Recruitment Stock Stock Stock Density Dependance Overcompensation Recruitment Recruitment Stock Stock

Recruitment (R) The Stock-Recruitment Relationship However…. 11/11/2018 Bt+1=Bt+R+G-M Recruitment (R) The Stock-Recruitment Relationship However…. These results could be due in part to measurement error Significant evidence that recruitment is reduced in overfished stocks We also know if there is zero stock, there is zero recruitment! Many examples where there is reasonable evidence for a stock-recruitment relationship

What is natural mortality (M)? 11/11/2018 Is the process of mortality (death) of fish due to natural causes such as predation, disease, etc. Think of it as the removal of fish from a population Typically we are referring to mortality post recruitment (as mortality in early stages is dealt with in recruitment estimation) Expressed as a rate (i.e. natural mortality rate). Rate is usually in proportions of the size/age class that suffer natural mortality per time period Natural mortality rates are critical in understanding of the relative impacts of fishing (e.g. compare natural v fishing mortality rates) Permits some understanding of the “resilience” of a stock to fishing (*More on this tommorow)

Natural mortality (M) [e.g. Hampton 2000] 11/11/2018 M tends to decrease with age [Fish ‘out-grow’ predators] May increase again in older fish [‘Stress’ associated with reproduction] BET SKJ YFT

Why does M fluctuate? 11/11/2018 Natural mortality varies throughout the life-cycle of a species Size/age – fish may “out-grow” predators (e.g. range of predators of larval v juvenile v adult marlin) Senescence processes and Reproductive stresses Movement away from areas of high mortality Behavioural changes (e.g. formation of schools) Changes in ecosystem status (e.g. prey availability, habitat availability) Changes in abundance (e.g. density-dependence influences, like cannibalism, prey limitations) More on this later in the week!!

Growth All fish (organisms) grow 11/11/2018 All fish (organisms) grow Critical to fish as growth will influence a range of biological characteristics (e.g. mortality, maturity etc) Critical to stocks as adds to biomass and influences reproductive potential of a stock Critical to fisheries as influences catches (selectivity) Critical to management as influence sustainability and reference points

Fish growth 11/11/2018 Typically fish show a deterministic, asymptotic growth schedule Overall, Each species has a characteristic size-at-age path There is individual variability in size-at-age Each species can only attain a species-specific maximum size Deterministic means outcome that can be easily, accurately predicted.

Fish growth Length – several periods (phases) of growth 11/11/2018 Length – several periods (phases) of growth Onset of maturity Reduced growth of adults Rapid growth of young fish

Growth Thus, there are several factors in describing fish growth 11/11/2018 Thus, there are several factors in describing fish growth Maximum size that the species can obtain The rate of growth A starting size (e.g. hatching size) More on this later in the week!!

Basic population models 11/11/2018 Basic population models So far we have considered the processes that contribute to change in population size over time, being: 1. Recruitment 2. Growth 3. Mortality And placed them in a simple “model”: Bt+1 = Bt + R + G – M However, this is not a form of model that is typically used for anything other than explaining the concept. We will now discuss some simple population models commonly used in studying population dynamics of many organisms. Understanding these will lay the foundation for understanding the more complex models we will spend a lot of time discussing later in the workshop

Basic Population Models 11/11/2018 Basic Population Models Population growth models Expontential growth model: The simplest growth model Growth rate proportional to population size! c. Expressed as: Nt = N0ert Where r is the the intrinsic rate of increase (or, rate of natural increase, or, population growth rate). r = birth rate (recruit rate for fish) – death rate (mortality) d. However, we know that most populations have limited resources!

Basic Population Models 11/11/2018 Basic Population Models 2. Logistic growth model: Populations might show expontential growth pattern until resources become limited and individuals compete for food….thus growth rate slows until the upper limit, carrying capacity (K) is reach (zero growth) dB/dt = rB(1-Bt/k)

**Excel Based Examples** 11/11/2018 Basic Population Models **Excel Based Examples**

Other factors to consider in population dynamics 11/11/2018 Other factors to consider in population dynamics Movements! Which are in large part dictated by their …. 1. Physiology 2. Interactions with physical environment Population model may often look at a population by sub area and as such considering movement is important to understand exchange between those parts.

Movement = Immigration – Emigration 11/11/2018 Movement Bt+1=Bt+R+G-M-C Influences estimates of biomass etc at time, depending on the balance of; Movement = Immigration – Emigration These estimates may vary with size/age, time of year, etc Critical in understanding dynamics, especially for HMS In stock assessment we are typically assuming no movement in or out of the total stock and therefore consideration of movement mainly pertains to within stock movement for spatially structured models

Why do fish move? Biology 11/11/2018 Biology Maintain preferred habitat, oxygen flow, follow prey, counter negative buoyancy Ecology Migration to spawning areas (e.g. SBT), ontogenetic change in locations (e.g. albacore), response to seasonal (e.g. albacore) or long term changes (e.g. skipjack) in environmental/oceanographic conditions

Why are movement estimates important? 11/11/2018 Effects the distribution of biomass Movement is simply estimating the balance between immigration and emigration of fish between model regions in order to estimate biomass within an area or model region

How is movement monitored? 11/11/2018 Size –frequency analyses CPUE analyses Tagging analyses

11/11/2018 Summary “To understand how populations will respond to exploitation, we need to appreciate how they will behave when unexploited.” Hillborn and Walters, 1992 Fish populations have natural variability, and depending on their life history characteristics (fecundity, growth rates, natural mortality) and the impacts of environment and stock on these, can vary from extremely variable to showing relatively small fluctuations in population size. ….you just cant escape the biology of the species! We’ll see in tommorow mornings session just how critical species biology is to their vulnerability to overfishing

11/11/2018 Fished Populations

Accounting for fishing mortality in population dynamics 11/11/2018 Accounting for fishing mortality in population dynamics Bt+1=Bt+R+G-M -C Death (Natural mortality) Recruitment Whole population (+) (-) Catch (Fishing mortality) (-) Growth (+)

Fishing and the “balance of nature” myth 11/11/2018 Fishing and the “balance of nature” myth The idea that nature (ecosystems and their living populations) is in balance is a myth: Ecosystems and the interactions between there components are variable, and the range of variability itself varies depending on the system and the component The degree of variability very much depends on the time scale we are considering a population over:

Fishing and the “balance of nature” myth 11/11/2018 Fishing and the “balance of nature” myth Bigeye tuna – fishery impacts analyses of estimated biomass with and without the impacts of fishing (SC2 – SA WP-2, 2006) Sardine and Anchovy – Study of Scale deposition in marine sediments Environmental impacts on recruitment tend to be significant drivers of population variability for pelagic species

Fishing impacts: Nature v Man 11/11/2018 Fishing impacts: Nature v Man The relative impacts of natural factors versus fishing on fish stocks has been debated for many decades: Four key points: It is dangerous to automatically ascribe changes in fishing success to fishing itself…. …….there are many factors that can influence either stock size, or the indicators used to track stock size, that are not directly related to fishing e.g. Case of South Pacific albacore) that are not related to fishing. Bt+1=Bt+R+G-M-C

Fishing impacts: Nature v Man 11/11/2018 Fishing impacts: Nature v Man It is equally dangerous to assume that natural variability is the key factor. One might then miss an opportunity to implement changes to the fishery that might ensure sustainability of catches and stock recovery 3. The fact is, changes in populations over time are likely to be influence by both fishing and by environment/other factors e.g. Sardine in the Eastern Pacific Ocean

Fishing impacts: Nature v Man 11/11/2018 Fishing impacts: Nature v Man It is the job of stock assessment to determine which factors are having the highest impact (or at least, the impact of fishing). The relative impacts of man will be dependant on many different factors, which we will now discuss……. A population’s response to its environment may in fact be changed by the impacts of fishing so the two processes are interrelated e.g Increased growth and reproduction from reduced competition for resources)

Population “states” Stability versus instability of fished populations 11/11/2018 Population “states” Stability versus instability of fished populations Stability Instability Time Time Population size Fishing catch Skipjack

Population “states” Resilience 11/11/2018 Population “states” Resilience “Natural systems are not stable but do exhibit changes within certain bounds or regions of stability. A system with a large region of desirable behaviour is called resilient”. (Hilborn and Walters, 1991) If a population has shown a capacity to regularly recover from low population levels then it can be thought of as resilient. If a population naturally varies within a fairly narrow population range then reduceing the population below its lower “boundary” (e.g. by introducing fishing) carries high risk….it takes the population into a state where we have no idea how it might react or whether it can recover. Resilience in a fishing context is the capacity of a population to sustain itself in the long term despite the added impact of fishing at some given level.

11/11/2018 Population “states” How do we know how stable or resilient a population might be without fishing it?.....we don’t! Cant determine where or if a boundary state exists till you have pushed past it. However, we can learn from history! We can also learn from our understanding of species biology!

Stability and Resilience 11/11/2018 Stability and Resilience Examples: Tropical Tunas Sharks Reproductive mode Broadcast spawning Internal fertilisation Fecundity Millions of eggs ~2-40 eggs/young Growth rate Fast Varies, typically slower Age to maturity 1-5 years (most spp) 6-7 years, up to 20 for some Life span 4-12 years 20-30 years What can we imply or predict from these parameters regarding the relative resilience of these species to fishing pressure? Ref: Last and Stevens (1994)

Variations among WCPO tuna 11/11/2018 Variations among WCPO tuna Yellowfin Bigeye Reproductive mode Serial spawning Multiple spawners Fercundity 2 million+ 2 million+ Growth rate 45-50cm (1yr) 40cm (1yr), 80cm (2yr) Age to maturity 2-3yr (100-110cm) 3yr+ (100-130cm) Life span 7-8yr 12+ Recruitment to fishery 0.5-1yr(PS), ~2+yr(LL) 0.5-1yr(PS), 2+yr(LL) Albacore Skipjack Reproductive mode ? Serial spawners Fercundity 0.8-2.6 million 2 million+ Growth rate 30cm (1yr) 44-48cm (1yr), 61-68 (2yr) Age to maturity 4-5yrs (80cm) <1yr (44cm) Life span ~9yr ~4yr Recruitment to fishery ~2yr(troll), 5+(LL) 0.5-1yr(PS)

Resilience: Importance of biology 11/11/2018 Resilience: Importance of biology Fish A Fish B Age to maturity: 1 years 2 years Fishing Mortality: 2 per year (quota) Natural Mortality: 0 Recruitment: 3/6 per year Growth: 0 Fish A 1 years 2 years 3 years 4 years 5 years Fish B

Resilience: Importance of biology 11/11/2018 Resilience: Importance of biology Fish A Fish B Age to maturity: 1 years 1 years Fishing Mortality: 2 per year (quota) Natural Mortality: 0 Recruitment: 3/6 1/6 Growth: 0 Fish A 1 years 2 years 3 years 4 years 5 years Fish B

Adding “fishing” to our logistic population model 11/11/2018 Adding “fishing” to our logistic population model We have already introduced some simple models for unexploited populations. One of these was a logistic model, which was adapted by Schaefer (1954) to account for the impacts of fishing on a population over time: Bt+1 = Bt + rB(1-Bt/k)-Ct Where… Ct = qEB q = catchability = proportion of the stock taken by one unit effort E = Fishing effort There are number of variations on this equation (e.g. Pella and Tomlinson model)

Adding fishing to our logistic population model 11/11/2018 Adding fishing to our logistic population model Ct = qEB q = catchability = proportion of the stock taken by one unit effort E = Fishing effort For example: If we have a stock of 100 fish, and on average each unit of effort will take one fish, then q = 1/100 = 0.01. So if we put 20 units of effort in the water: C = 0.01 x 20 x 100 = 20 If the fishers efficiency increased (e.g. they could catch two fish per unit effort) then q increases, and C increases with it C = 0.02 x 20 x 100 = 40

Adding “fishing” to our logistic population model 11/11/2018 Adding “fishing” to our logistic population model Today we have discussed two key issues: The importance of biological characteristics of species and how these might relate to vulnerability to fishing pressure The adaptation of population models to account for fishing based exploitation of fish populations We are now going to look at some Excel based examples of some basic logistic models that encorporate fishing impacts, and at how varying biological parameters can influence how a population reacts to a given level of fishing pressure. Recruitment rate Natural Mortality rate

Sustainability and overfishing 11/11/2018 Sustainability and overfishing In the Excel based examples we have just looked at you will have noticed: When a population is at equiliberium, any further increase in Z (due to fishing) will clearly cause the population to decline, continuously if there is no other change in the system. Hence fishing mortality at a level that keeps R = Z is sustainable over time, fishing mortality that causes R<Z is not sustainable. Time Population size R>Z R=Z R<Z

Sustainability and overfishing 11/11/2018 Sustainability and overfishing A sustainable catch can exist at many different levels of stock size. If stock size declines, sustainable catches might still be made, but at a lower level than previously. As we all know, one of the most common objectives in fisheries management is to achieve Maximum Sustainable Yield (MSY). This is the highest amount of catch that can sustainably be taken without impacting the stock to such a degree that catch subsequently declines.

Sustainability and overfishing 11/11/2018 Sustainability and overfishing An overfished fishery generally considered to be one in which the current biomass (B) is less than that which would produce MSY. A stock is considered “overfished” when exploited beyond an explicit limit beyond which its abundance is considered "too low" to ensure safe reproduction. Overfishing is said to be occuring when the level of fishing mortality (F) is greater than the level that would produce MSY. In general, action of exerting a fishing pressure (fishing intensity) beyond agreed optimum level. A reduction of fishing pressure would, in the medium term, lead to an increase in the total catch. These concepts will be discussed in depth further on in the workshop, however it is useful to remind ourselves of them now There are some problems with the use of MSY as an objective, but these will also be discussed later

Sustainability and overfishing 11/11/2018 Sustainability and overfishing Recruitment overfishing A situation in which the rate of fishing is (or has been) such that annual recruitment to the exploitable stock has become significantly reduced. The situation is characterized by a greatly reduced spawning stock, a decreasing proportion of older fish in the catch, and generally very low recruitment year after year. If prolonged, recruitment overfishing can lead to stock collapse, particularly under unfavourable environmental conditions. Restrepo V. (1999): Figure ref: http://www.oceansatlas.com/

Sustainability and overfishing 11/11/2018 Sustainability and overfishing Growth overfishing occurs when too many small fish are being harvested, usually because of excessive effort and poor selectivity (e.g. too small mesh sizes) and the fish are not given the time to grow to the size at which the maximum yield-per-recruit would be obtained from the stock. A reduction of fishing mortality on juveniles, or their outright protection, would lead to an increase in yield from the fishery. Growth overfishing, by itself, does not affect the ability of a fish population to replace itself. Ecosystem overfishing Occurs when the species composition and dominance is significantly modified by fishing (e.g. with reductions of large, long-lived, demersal predators and increases of small, short-lived species at lower trophic levels).

Bt+1=Bt+R+G-M -C Summary 11/11/2018 Summary Bt+1=Bt+R+G-M -C Populations vary naturally. The scale of that variation often depends on the time scale considered. The impact of fishing on a populations dynamics and size over time will depend in part on the inherent biological properties of the population and what that confers about resilience. A key task for stock assessment scientists is to be able to estimate the relative impact of fishing on the stock….whether declines are due to fishing or environment will effect the management decisions made Understanding the likely impact of fishing on a population requires understanding the biology of the species itself