Gomphosus varius (Purple club-nosed wrasse)
Halichoeres purpurescens (Purple striped wrasse)
Notolabrus fucicola (Purple wrasse)
Chlorurus sordidus (Burnt parrotfish)
Notolabrus fucicola (Kelpie)
Thalassoma purpureum (parrotfish)
1. Fishing in hot waters threatens phenotypic diversity.
The Journal of animal ecology J Anim Ecol Fishing in hot waters threatens phenotypic diversity. 1642-1644 10.1111/1365-2656.13066 In Focus: Morrongiello, J. R., Sweetman, P. C., & Thresher, R. E. (2019). Fishing constrains phenotypic responses of marine fish to climate variability. Journal of Animal Ecology, 88, 1645-1656. Forces of unnatural selection, such as climate change and harvest, are rarely studied in concert, yet hold the great potential to act synergistically on individual performance, susceptibility to harvest, tolerance to warming temperatures, and ultimately population persistence and resilience. In this paper, Morrongiello et al. (2019) used long-term monitoring of a site-attached temperate reef fish, the purple wrasse (Notolabrus fucicola), to test novel predictions about how fisheries management and climate variability could alter individual growth rates and thermal reaction norms within and across stocks. Otolith growth increments were collected from three south-east Australian populations between 1980 and 1999, pre- and post-harvest, throughout an intensive warming spell. Using hierarchical models to partition variation in growth within and between individuals and populations, Morrongiello et al. detected increased average growth rate with warming, a release from density dependence post-harvest, and a fishing-by-warming interaction that decreased diversity in thermal growth reaction norms because large individuals that tend to better tolerate warm temperatures were effectively culled from the population. This study outlines the importance of determining which phenotypes are more resilient to increasing temperatures, how fisheries should manage for them, and how such collective knowledge could help preserve and even promote resilience of managed populations to increasing temperatures in ecosystems threatened by climate change. © 2019 The Author Journal of Animal Ecology © 2019 British Ecological Society. Aubry Lise M LM 0000-0003-3318-7329 Fish, Wildlife and Conservation Biology Department, Colorado State University, Fort Collins, CO, USA. eng Journal Article England J Anim Ecol 0376574 0021-8790 IM Animals Australia Climate Change Ecosystem Fisheries Fishes Phenotype climate change fisheries harvest hierarchical model reaction norms unnatural selection wrasse 2019 06 18 2019 07 01 2019 11 7 6 0 2019 11 7 6 0 2019 12 18 6 0 ppublish 31691275 10.1111/1365-2656.13066 REFERENCES, 2019
2. Fishing constrains phenotypic responses of marine fish to climate variability.
Morrongiello JR, Sweetman PC, Thresher RE
The Journal of animal ecology J Anim Ecol Fishing constrains phenotypic responses of marine fish to climate variability. 1645-1656 10.1111/1365-2656.12999 Fishing and climate change are profoundly impacting marine biota through unnatural selection and exposure to potentially stressful environmental conditions. Their effects, however, are often considered in isolation, and then only at the population level, despite there being great potential for synergistic selection on the individual. We explored how fishing and climate variability interact to affect an important driver of fishery productivity and population dynamics: individual growth rate. We projected that average growth rate would increase as waters warm, a harvest-induced release from density dependence would promote adult growth, and that fishing would increase the sensitivity of somatic growth to temperature. We measured growth increments from the otoliths of 400 purple wrasse (Notolabrius funicola), a site-attached temperate marine reef fish inhabiting an ocean warming hotspot. These were used to generate nearly two decades of annually resolved growth estimates from three populations spanning a period before and after the onset of commercial fishing. We used hierarchical models to partition variation in growth within and between individuals and populations, and attribute it to intrinsic (age, individual-specific) and extrinsic (local and regional climate, fishing) drivers. At the population scale, we detected predictable additive increases in average growth rate associated with warming and a release from density dependence. A fishing-warming synergy only became apparent at the individual scale where harvest resulted in the 50% reduction of thermal growth reaction norm diversity. This phenotypic change was primarily caused by the loss of larger individuals that showed a strong positive response to temperature change after the onset of size-selective harvesting. We speculate that the dramatic loss of individual-level biocomplexity is caused by either inadvertent fisheries selectivity based on behaviour, or the disruption of social hierarchies resulting from the selective harvesting of large, dominant and resource-rich individuals. Whatever the cause, the removal of individuals that display a positive growth response to temperature could substantially reduce species' capacity to adapt to climate change at temperatures well below those previously thought stressful. © 2019 The Authors. Journal of Animal Ecology © 2019 British Ecological Society. Morrongiello John R JR 0000-0002-9608-4151 School of BioSciences, University of Melbourne, Melbourne, Victoria, Australia. CSIRO Oceans and Atmosphere, Hobart, Tasmania, Australia. Sweetman Philip C PC CSIRO Oceans and Atmosphere, Hobart, Tasmania, Australia. Institute for Marine and Antarctic Studies, Fisheries and Aquaculture, University of Tasmania, Hobart, Tasmania, Australia. Thresher Ronald E RE CSIRO Oceans and Atmosphere, Hobart, Tasmania, Australia. eng Journal Article Research Support, Non-U.S. Gov't 2019 05 23 England J Anim Ecol 0376574 0021-8790 IM Animals Biota Climate Change Fisheries Fishes Population Dynamics Temperature climate change fish growth fisheries selectivity fisheries-induced evolution multiple stressors otolith biochronology reaction norm time series 2018 08 20 2019 02 02 2019 4 30 6 0 2019 12 18 6 0 2019 4 30 6 0 ppublish 31034605 10.1111/1365-2656.12999 REFERENCES, 2019