Benthic Invertebrates – habitats, human impacts,

management

Presentation Outline• Importance of benthic invertebrates • Population based model

• Approach • Limitations

• Individual based model • Approach • Combining with population model • Genetic variability

• Concluding Remarks

Benthic Invertebrates • Important components of estuarine and coastal food

webs – sentinel species, many long lived • Provide coupling between benthic and pelagic

systems – Post-settlement and larval phases of life history – Filtering water– Regulate food concentrations (phytoplankton) – Nutrient cycling

• Shellfish important to carbonate balance• Many are commercially important • Important to local history and culture

Benthic Invertebrates • Included in models as loss/gain term via boundary conditions

– Loss of phytoplankton via filtration rate – Nutrient addition term

• Population that grows and declines in response to various forcing functions

• Coupled circulation-biological model focused on larvae - usually transport pathways

• Coupled circulation-biological model that includes larvae and post-settlement populations

• Importance of understanding ecology, physiology and life history of organism

General Characteristics• Most models track energy – given by difference

between assimilation and respiration • Reproduction is energy loss but provides recruits • Mortality – natural, disease, predation, starvation • Movement – pelagic phase to life history – need

circulation • Range of responses within species in rates – genetic

variability • Multiple species – focus on ones with data

Population Dynamics Modeling - The Past

• Population-based model of the average individual

• Based on animal physiology

• Parameterized for average physiology

• Allows projection of responses to environmental conditions

Aspects of Population Dynamics

• Animal grows• Somatic tissue• Reproductive tissue

• Reproduces – biological and environmental cues

• Environmental inputs• Animal filtration rate

sets up assimilation and respiration

• Animal can gain and loose mass

• Model usually in terms of energy or carbon

Size Class Approach Requires conversion between weight and

length

Nonlinear size scale

Size Class Model – Governing Equation

Net production NPj = Pgj + Prj = Aj – Rj j = size class

dOj/dt = Pgj + Prj + gain j-1 – loss j+1

Gain and loss are inputs from current size class to/from larger and smaller size classesTransfers scaled by animal weight so mass and energy are conserved in terms of animal numbers

Shrinkage due to poor environmental conditions

Reproductive tissue accounts for 30-50% of body weight

Spawning is a loss of mass and energy for size class

Larvae provide new recruits and connect to pelagic system

Size Class Model – Governing EquationNet production NPj = Pgj + Prj = Aj – Rj j = size class

dOj/dt = Pgj + Prj + gain j-1 – loss j+1 + gain j+1 – loss j-1Gain and loss are inputs from current size class via shrinkage from larger and to smaller size classes Scale transfers to conserve numbers

Results – what learned

Simulated change inoyster population size

structure

Time history of reproductive tissue andoccurrence of spawning

events

Limitations • Average individual – does not allow

consideration of variability in physiological responses

• Larvae incorporated as a loss of mass and input of mass to smallest size class – not altering characteristics of post-settlement population

• Gain/loss in weight requires a gain/loss in length

Population Dynamics Modeling The Recent Present

• Individual-based model• Multiple cohorts of phenotypically varying individuals• Allows phenotypic variation to determine population response to environment• Age-size decoupled so that age-frequency and size-frequency distributions can be

independently described

AnimalAnimal

Given age canhave a range of

lengths

Given size can have a range of

ages

Represents geneticvariability of population

Nonlinear age-lengthrelationship

Age-length distribution

Net production is apportioned betweenreproductive and somatic tissue

Increase in weight only if NP is positive

Condition index determines if length increase can occur – positive scope for growth

Allows an increase inmass without an increase in length

Governing Equations

Calculate increase in weight

Calculate condition index

Calculate length increase

Increase/decrease in weight without change in length - spawning events

Simulated hard clam growth

Investigate effects of environmental conditions on clam weight and length

Starvation period imposed in years 3-5 via low food conditions

Change in clam condition over time

Management implications

How to extend beyond individual?

Apply a Gaussian function to producea distribution of individuals with rangeof characteristics

Individual hard clam results are extended to cohort and populationlevels

Successful

Track spawning events – gives individuals

Vary characteristics such as assimilation efficiency,respiration rate, initial egg size to produce a cohort

Construct cohort with individuals with a range of variability

Extend Cohorts to Population

Uses broodstock-recruitment relationship

Limitations

• Population variability is based on probability distribution

• Cannot determine cause and effect of variability

• Introduction of new traits and/or modifications to existing traits not possible

• Want to be able to track genetic variability

Population Dynamics Modeling

The Present

Integrate Population and Genetic Processes

Model allows forgenetically determinedphenotypically-based

physiology

Phenotypic response modulated by

genotypic constraints

Phenotype response to environmental conditions

controls population response

G3G1

G4G2

}L1}L2

N Chromosome pairs

Nx2 Chromosomes

Multiple loci per chromosome

Multiple alleles per gene

AnimalAnimal

Characteristics of Oysters• High fecundity – 106 eggs per spawn with

multiple spawnings per season• Protandic – male when young, small size and

become female when older and larger• Sex ratio of the population changes as it ages • High load of lethal mutations• Potentially subject to sweepstakes

reproductive success events

Inclusion of Explicit Genetics• Track trajectory of individual alleles over time

which gives a measure of genetic drift and loss of alleles

• Effective population number • Introduction of new genetic traits • Relevance – pH effects,

disease resistance, warming temperatures

Tracking individual alleles

Model framework provides

Population trajectoryPopulation characteristics

AND Genetic composition

Allele frequency on each chromosomeExample Application

Simulate introduction of specific genes into a population

Larval dispersal – moves individuals

© John Norton (http://www.mdsg.umd.edu)

Pelagic phasePelagic phase

Benthic phase

Physical TransportLarval Behavior

Circulation Model(3D and time)

Circulation Model(3D and time)Atmospheric

TidesRiver Discharge

TemperatureSalinity

Larval Growth

Currents

Particle Tracking Module

Larval Behavior

LARVAL MODELLARVAL MODEL

TemperatureSalinity

Settlement 330 um Modified Particle

Tracking Module

Vertical Velocity, Size, Temperature, Salinity

Post-settlementPopulation

Model Framework Genetics ModelGenetics Model

Population ConnectivityMatrix

Allows determining connectionbetween spawning and

settlement areas

Allows tracking of specific genes and genotypes

1

2

3

4

Area 1 Area 2 Area 3 Area 4

Area 1 to: 11% 54% 27% 8%

Area 2 to: 6% 56% 29% 9%

Area 3 to: 3% 40% 29% 28%

Area 4 to: 3% 19% 14% 64%

Larval Dispersal obtained from coupled circulation-larvae model

From Narváez

Munroe et al. (n press)

33

1

2

3

4

Transport of Alleles via Oyster LarvaeBase Case

2000’s

Even DispersalAll 4 Areas

Reverse LarvalDispersal

Low SalinityLarval Disp.

No Self-RecruitsEqual Disp

Larvae not effective at moving and

introducing new alleles

Munroe et al, in press

34

1

2

3

4

Adult Population Transfer of Alleles

Base Case2000’s

Even AbundanceVia Mortality

1970’s Simulation

Even Abundance

Via Carrying Cap.

Adult mortality controls

movement and

introduction of allelesMunroe et al., in press

Shell Budget

Shells provide habitat

Carbonate source

Concluding Remarks • Understanding and tools allow

consideration of interactions of ecology, biology and genetics

• Shellfish models are extendable to other invertebrate species – understand species and have data

• Consider combined effects of environment, growth, behavior in projections of effects of climate change

Concluding Remarks • Use complex models to develop

parameterizations for larger scale ecosystem models

• Models are sufficiently robust to provide useful inputs for management - shell repletion in estuaries

• Genetic basis allows consideration of adaptation to changing environmental conditions

QUESTIONS?