Predicting habitat suitability and geographic distribution of anchovy (Engraulis ringens) due to climate change in the coastal areas off Chile

摘要

The effects of climate change on ocean conditions will have impacts on fish stocks, primarily through physiological and behavioural effects, such as changes in growth, reproduction, mortality and distribution. Habitat and distribution predictions for marine fishery species under climate change scenarios are important for understanding the overall impacts of such global changes on the human society and on the ecosystem. In this study, we examine the impacts of climate change on anchovy fisheries off Chile using predicted changes in global models according to the National Centre for Atmospheric Research (NCAR) Community Climate System Model 3.0 (CCSM3) and IPCC high future CO2 emission scenario A2, habitat suitability index (HSI) models and satellite-based sea surface temperature (SST) and chlorophyll-a (Chl-a) estimates from high-resolution regional models for the simulation period 2015-2065. Predictions of SST from global climate models were regionalised using the Delta statistical down scaling technique. Predictions of chlorophyll-a were developed using historical Chl-a and SST (20032013) satellite data and applying a harmonic model. The results show an increase. in SST of up to 2.5 degrees C by 2055 in the north and central-south area for an A2 scenario. The habitat suitability index model was developed using historical (2001-2011) monthly fisheries and environmental data. The catch per unit effort (CPUE) was used as an abundance index in developing the HSI models and was calculated as the total catch (ton) by hold capacity (m(3)) in a 10' x 10' fishing grid square of anchovy, integrated over one month of fishing activity. The environmental data included the distance to coast (DC), thermal (SST) and food availability (Chl-a) conditions. The HSI modelling consists of estimating SI curves based on available evidence regarding the optimum range of environmental conditions for anchovy and estimating an integrated HSI using the Arithmetic Mean Model (AMM) method. The results of this work show that the model has produced robust estimates of habitat suitability and geographic distribution off Chile and has been especially effective in capturing the spatial and temporal variability of CPUE.