Coexistence with Stochastic Dispersal in a Nearshore Multi-Species Fishery Heather Berkley & Satoshi Mitarai

Competitive Exclusion Principle Two species with similar ecological traits competing for a limited resource cannot coexist – one will drive the other to extinction. (Volterra- Gause) This does not occur often in nature Several different theories explain why coexistence occurs –Niche differentiation –Intermediate disturbance –Storage effect We will focus on temporal & spatial variability in settlement & recruitment

Simple Two Species Example Consider two similar species A & B – Species A has a slightly better ability to utilize resources – Recruits compete for limited resources at settlement sites – Spawning timings are separated by weeks Compare cases with i) smooth dispersal kernel & ii) packet model for connectivity – Smooth dispersal kernel: spawning timing does not matter – Packet model: species A & B “catch” different eddies & can settle at different sites

Diffusion Case If they are put together, species B becomes extinct, species A thrives Note: this is what eddy-diffusion model predicts On their own, both species can persist Time (years) IC’s: A = 100, B = 100

Packet Model Larval settlement as arrival of N packets L = domain size l = eddy size (50 km) T = Spawning time t = eddy turnover rate (14 d) eddy size ( l ) N larval packets

Packet model case IC’s: A = 100, B = 100 Generations Completely different spawning timing leads to coexistence

Time-space variations Species ASpecies B Coexistence with Species A more abundant at most (but not all) locations Generations Alongshore Location (km)

Spawning Window Overlap Specify how many days of overlap between spawning times for both species Makes some packets perfectly correlated for both species and others independent Packets will have same settlement locations Species A Spawning Window Species B Spawning Window TIME

Connectivity ~half of packets perfectly correlated Species A Species B

Parameters Tsp (spawning time) = 30 days for both –Vary amount of overlap Fecundity of Sp.A = 0.5 Fecundity of Sp.B = 0.45 Adult Mortality = 0.09 Run time = 500 yrs; Patch size = 5 km; Domain size = 500 km; Larvae on larvae DD (total # of both sp) Averaged over 10 simulations

Species A Species B 0 days of overlap

Species A Species B 10 days of overlap

Species A Species B 20 days of overlap

Species A Species B 25 days of overlap

Species A Species B 30 days of overlap

Correlation between Connectivity Matrices for Sp A & B

Mean Correlation Coefficient # of Independent Packets

Spawning Window Overlap SpA has its entire spawning window the same as SpB Only Sp B has independent packets Vary this amount of time Species A Spawning Window Species B Spawning Window TIME

Species A Species B Tsp = 30 days

Species A Species B Tsp = 30 days Tsp = 36 days

Species A Species B Tsp = 30 days Tsp = 42 days

Species A Species B Tsp = 30 days Tsp = 48 days

Species A Species B Tsp = 30 days Tsp = 54 days

Species A Species B Tsp = 30 days Tsp = 60 days

Species A Species B Tsp = 30 days Tsp = 66 days

Species A Species B Tsp = 30 days Tsp = 72 days

Tsp = 30 days Tsp = 78 days Species A Species B

Correlation between Connectivity Matrices for Sp A & B

Spatial Patterns of Adults Look at spatial covariance in Adult densities for SpA and SpB Are these spatial patterns Adult densities strengthening coexistence?

Mean Cov(A,B) through time Overlap (days)

Species A Species B

Next Steps Compare packet model results with particle tracking simulations –Graphs of Correlation vs. Days of overlap in Tsp for 2 scenarios presented Shorten lifespan to see how much is due to the temporal vs spatial storage effect or buffering