Mobulid rays in the eastern Pacific
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1 Mobulid rays in the eastern Pacific Joshua Stewart, Nerea Lezama-Ochoa, Marlon Román, Martin Hall 8 th Meeting of the Bycatch Working Group La Jolla, California USA, May 2018
2 Outline Introduction to group: mobulid rays Data collection: uncertainties, new forms Bycatch estimates: assumptions, release methods Spatial distributions Knowledge gaps Species Distribution Models Survival estimates: pilot program Proposed program: partners
3 Mobulid rays: Ecology and life history Joshua Stewart Scripps Instituion of Oceanography Manta Trust
4 Mobulid rays: Ecology and life history M. birostris M. tarapacana Disc width M. munkiana M. thurstoni M. mobular
5 Mobulid rays: Ecology and life history Old name New name Common name Manta birostris Mobula birostris Giant manta now Giant devil ray Mobula japanica Mobula mobular Spinetail devil ray Mobula thurstoni Smooth tail or Bentfin devil ray Mobula tarapacana Chilean devil ray Mobula munkiana Munk's devil ray White et al. 2017
6 Mobulid life history Long lived 40+ years for mantas for mobulas
7 Mobulid life history Long lived 40+ years for mantas for mobulas Vertebra
8 Mobulid life history Long lived 40+ years for mantas for mobulas Late maturity ~ 8 years for mantas ~ 6 years for mobulas % Mature Disc width = 6 years White et al., 2006
9 Mobulid life history Long lived 40+ years for mantas for mobulas Late maturity ~ 8 years for mantas ~ 6 years for mobulas Low fecundity Mobula alfredi Fetus Single pup per pregnancy, gaps of 2-7 years between pregnancies
10 Mobulid life history Long lived 40+ years for mantas for mobulas Late maturity ~ 8 years for mantas ~ 6 years for mobulas Low fecundity r max Single pup per pregnancy, gaps of 2-7 years between pregnancies One of the lowest population growth rates among elasmobranchs
11 Population trends Global decline in school size and sighting frequency Ward-Paige et al., 2013 Declines in manta and mobula sighting frequency (Cocos Is.) White et al., 2015
12 Data collection issues Early years of the AIDCP program , most unidentified Observer training begins to improve in Taken in all types of sets; most in school and dolphin sets Still many unidentified because of inability to observe characteristics needed Not retained Release methods and vulnerability suggested assumption of 100% mortality
13 Data collection Created by M. Román
14 Data collection Created by M. Román
15 Bycatch estimates
16 Bycatch estimates
17 Bycatch estimates IATTC bycatch database ( ) Lezama-Ochoa et al (in review)
18 Bycatch estimates Lezama-Ochoa et al (in review)
19 Bycatch estimates Lezama-Ochoa et al (in review)
20 Bycatch estimates Lezama-Ochoa et al (in review)
21 Bycatch estimates: release methods Skipper s workshops ISSF IATTC in the EPO
22 Knowledge gaps Population structure Panmictic? Independent stocks?
23 Knowledge gaps Population structure Panmictic? Independent stocks? Genetic analyses of tail samples UC Santa Cruz
24 Knowledge gaps Population structure Panmictic? Independent stocks? Genetic analyses of tail samples UC Santa Cruz Abundance & trends Virtually no data for mobulas Close-kin mark recapture Effective population size Determine impacts of fisheries (still largely unknown)
25 Knowledge gaps Population structure Panmictic? Independent stocks? Genetic analyses of tail samples UC Santa Cruz Abundance & trends Virtually no data for mobulas Close-kin mark recapture Effective population size Determine impacts of fisheries (still largely unknown) Movements & diving behavior & species distribution Very limited information for most mobulids Mainly for aggregation sites Tag movement distributions Croll. et al., 2012
26 Knowledge gaps: Species Distribution Models Species Distribution Models (SDMs) Generalized Additive Models (GAMs)- Eastern Pacific Ocean Integrated-Nested Laplace Approximation (INLA)- Eastern Pacific Ocean Maximum Entropy (MaxEnt)- Gulf of California Climate change Predictions under the RCP85 scenario (2100) of climate change (MaxEnt)- Gulf of California
27 Knowledge gaps: Species Distribution Models Species name: Mobula mobular* (Spinetail Devil Ray) Taxonomic revision: changed from M. japanica (White et al. 2017) Distribution: Circumglobal Habitat: Coastal, pelagic, oceanic Maximum Disc Width (DW): 310 cm Number of pups: one Aggregations: Gulf of California (summer) Diet: Euphausiids (Nyctiphanes simplex)
28 Knowledge gaps: Species Distribution Models M. mobular Lezama-Ochoa et al (in preparation)
29 Knowledge gaps: Species Distribution Models: GAMs DIRECTLY RELATED WITH UPWELLING SYSTEMS Lezama-Ochoa et al (in preparation) Type: 37.3% Chl: 13% SSH: 13.5%
30 Knowledge gaps: Species Distribution Models: INLA Lezama-Ochoa et al. 2018b (in preparation)
31 Knowledge gaps: Species Distribution Models: MaxEnt Occurrence data Presence + Background Habitat distribution models Environmental data Present 2100 (scenario RCP85) K-fold crossvalidation Prediction of models Evaluation of models Potential distribution of species Climate change (RCP85) Area Under the Curve (AUC)
32 Knowledge gaps: Species Distribution Models: MaxEnt Potential habitat M. mobular (PRESENT) AUC: 0.93 Warm waters 18-26ºC CONTRIBUTION 42.6% High salinity waters 35.4 PSU 5.5% Productive waters 30 mg-3 day-1 Primary production 39.7% Lezama-Ochoa et al. 2018c (in preparation)
33 Knowledge gaps: Species Distribution Models: MaxEnt climate barreer? Habitat loss: >20% Gulf of Ulloa Habitat gain: 5% Gulf of Ulloa: potential habitat also for turtles and marine mammals (Etnoyer et al. 2016) The habitat of Mobula mobular could be affected by the effect of climate change
34 Knowledge gaps Post release mortality IATTC currently considers every mobulid capture to be a mortality Some evidence to suggest that, for at least some species, some proportion survive Francis & Jones 2016: Tuna purse-seine fishery: skipjack M. japanica tagged from purse seines in New Zealand. 3 out of 7 (43%) tagged rays survived
35 Knowledge gaps: Survival estimates, pilot project
36 Survival estimates: pilot project Observers were trained to: Deploy survivorship tags SAFELY Collect relevant covariate data Collect a tail sample for genetic analyses Refresher course on mobulid species ID
37 Survival estimates: pilot project Deployed tags Tag nº1 (FAD set): 5.44N/106.19W Tag nº 2 (FAD set): 4.28N/99.01W Tag nº 3 (FAD set): 3.06N/90.55W
38 Survival estimates: pilot project
39 Survival estimates: pilot project
40 Survival estimates: pilot project
41 Survival estimates: pilot project
42 Survival estimates: pilot project
43 Survival estimates: pilot project
44 Survival estimates: pilot project 3 out of 5 mobulids in pilot study survived (mix of species) Good for the fleets; reduces mortality estimate from 100% Allows for a more robust estimate of impacts on stocks Full-scale implementation will support handling guidelines Which release method contributes most to post-release survival? What handling covariates have the greatest impact on mortality? e.g. time spent in net, time spent on deck, number of brailer Use results to develop a best-practices handling and release guide
45 Survival estimates: pilot project What handling covariates could have the greatest impact on mortality? SPECIES SIZE SEX TIME IN NET TIME ON DECK BRAILER SEQUENCE BRAILER SIZE POSITION ON BRAILER SEA SURFACE TEMPERATURE WEATHER CONDITIONS BODY CONDITION BEFORE RELEASE RELEASE METHOD TUNA CATCH QUANTITY TYPE OF SET
46 Survival estimates: pilot project Contribute to ecological studies that benefit management Observer-collected tail samples allow for stock structure and population size analyses Movement data from tagged survivors will help identify mobulid hotspots Diving behavior from tagged survivors will provide information on bycatch risk
47 onclusions Observer can provide a cost-efficient way to study survival of species with infrequent captures With good handling and release techniques, we can reduce bycatch mortality Release can be performed without major operational interference Full support from: Government Industry organizations TUNACONS, OPAGAC, ATUNEC Industry + NGOs: ISSF Skippers and crews Multi-disciplinary team
48 Future directions Deploy 150 survivorship tags Evaluate post release mortality of different species Develop best practices handling and release guidelines based on results Use archival tag data from surviving mobulids to study horizontal and vertical movements, habitat use, and mobulid hotspots Genetic analyses from tail samples Improve species identification, sex determination and verify observer ID Population abundance estimation with close kin mark recapture Evaluate population structure throughout the eastern Pacific
49 Partners/Collaborations AZTI Nerea Lezama-Ochoa (habitat models & climate change) Scripps Institution of Oceanography & Manta Trust Joshua Stewart (mobulid ecologyand telemetry) UC Santa Cruz Donald Croll (mobulid ecology & telemetry) Kelly Newton (mobulid ecology & telemetry) Giacomo Bernardi (genetics) Monterey Bay Aquarium (funder of pilot study) Salvador Jorgensen (elasmobranchs & telemetry) John O Sullivan (mobulid husbandry & survival)
50 Questions?
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