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2021 ◽  
Author(s):  
◽  
Amber Brooks

<p>The long-term sustainability and security of food sources for an increasing human population will become more challenging as climate change alters growing and harvesting conditions. Significant infrastructure changes could be required to continue to supply food from traditional sources. Fisheries remain the only major protein supply directly harvested from the wild. This likely makes it the most sensitive primary sector to climate change. Overfishing is an additional concern for harvested species. There is a need to anticipate how marine species may respond to climate change to help inform how management might best be prepared for shifting distributions and productivity levels. The most common response of mobile marine species to changes in climate is an alteration of their geographic distributions and/or range shifts. Predicting changes to a species’ range could promote timely development of more sustainable harvest strategies. Additionally, these predictions could reduce potential conflict when different management areas experience increasing or decreasing catches. Ecological Niche Modelling (ENM) is a helpful approach for predicting the response of key fishery species to climate change scenarios.  The overall aim of this research was to use the maximum entropy method, Maxent, to perform ENM on 10 commercially important fishery species, managed under the Quota management system in Aotearoa (New Zealand). Occurrence data from trawl surveys were used along with climate layers from Bio-ORACLE to estimate the species niche and then predict distributions in four different future climate scenarios, called Representative Concentration Pathway Scenarios (RCPS), in both 2050 and 2100. With little consensus over the best settings and way to apply the Maxent method, hundreds of variations were tried for each species, and the best model chosen from trial experimentation.  In general, Maxent performed well, with evaluation metrics for best models showing little omission error and good discriminatory ability. There was, however, considerable variation between the different species responses to the future climate scenarios. Consistent with other studies, species able to tolerate sub-tropical or temperate conditions tended to expand southward, while subantarctic species generally contracted within their preferred environment. The increasing emissions or ‘business as usual’ climate change scenario consistently presented the most extreme difference from modern predictions. Northern regions of prediction, where sub-tropical or temperate species increased in probability of presence, were often highly uncertain due to novel conditions in future environments. Southern regions were usually less uncertain. Surface temperature consistently influenced base models more so than any other covariates considered, with the exception of bathymetry.  Some predictions showed common areas of relative stability, such as hoki and ling on the southern Chatham Rise, potentially indicating future refugia. The preservation of habitats in the putative refugia may be important for long-term fisheries resilience. Furthermore, most species that showed large predicted declines are currently heavily harvested and managed. Overfishing could compound the effects of climate change and put these fisheries at serious risk of collapse. Identification of potential refugial areas could aid strategy adjustments to fishing practice to help preserve stock viability. Additionally, when some species shift, there are areas where new fisheries may emerge.  This study offers a perspective of what future distributions could be like under different climate scenarios. The ENM predicts that the ‘business as usual’ scenario, where ‘greenhouse gas’ emissions continue to rise throughout the century, will have a negative impact on multiple aspects of distribution. However, in a reduced emissions scenario, less extreme range shifts are predicted. This study has provided a predictive approach to how fisheries in Aotearoa might change. The next step is to determine whether there is any evidence for the beginning of these changes and to consider how fisheries might best adapt.</p>


2021 ◽  
Author(s):  
◽  
Baylee Wade

<p>Climate driven threats are predicted to decrease the complexity of biogenic habitats. Within temperate coastal marine environments, we know that complex macroalgal beds support more complex communities through the provision of microhabitats and refuges. Macroalgal habitats have potential interacting benefits and costs for predators, as increased macroalgal biomass supports higher richness and diversity of prey species, but prey within these habitats might be more difficult to catch. An important New Zealand fishery species, the blue cod (Parapercis colias), is a large bodied temperate reef fish found exclusively throughout the coastal waters of New Zealand. Its dependence on subtidal coastal reef environments mean that it is important to understand how a loss of complex macroalgal habitats might alter the way that blue cod forage, and how the trade-off between prey abundance and availability will affect its abundance and productivity. This thesis aims to understand the influence of complex macroalgal habitats on P. colias prey availability and behaviour, on the foraging success of P. colias, and ultimately on P. colias population dynamics. Experiments were conducted using choice chambers to evaluate whether two alternate P. colias prey, Forsterygion lapillum and Heterozius rotundifrons, showed a preference for complex habitats with and without predation risk. Both species preferred complex habitats in the absence of predation cues, but F. lapillum showed a more consistent preference for complexity in response to predation risk. A mesocosm experiment was used to investigate whether the consumption rate and functional response of P. colias differs for these two prey types in the presence and absence of habitat complexity. Results indicated that the mobile fish prey, F. lapillum benefitted from the refuges provided by complexity and suffered lower consumption rates, whereas the sedentary crab, H. rotundifrons did not. Finally, using a simple population model, the trade-off between prey abundance and predation success on the population dynamics of P. colias with and without habitat complexity was explored. Models showed that scenarios with complex macroalgal habitats generally support more predators, and faster population growth rates than scenarios lacking habitat complexity. However, scenarios with complex habitats were predicted to be more sensitive to fishing pressure and have the potential to be more vulnerable to overexploitation. These results highlight the importance of understanding how habitat complexity mediates relationships between commercially important fishery species and their prey, in order to understand how habitat loss may alter their foraging success and population dynamics.</p>


2021 ◽  
Author(s):  
◽  
Baylee Wade

<p>Climate driven threats are predicted to decrease the complexity of biogenic habitats. Within temperate coastal marine environments, we know that complex macroalgal beds support more complex communities through the provision of microhabitats and refuges. Macroalgal habitats have potential interacting benefits and costs for predators, as increased macroalgal biomass supports higher richness and diversity of prey species, but prey within these habitats might be more difficult to catch. An important New Zealand fishery species, the blue cod (Parapercis colias), is a large bodied temperate reef fish found exclusively throughout the coastal waters of New Zealand. Its dependence on subtidal coastal reef environments mean that it is important to understand how a loss of complex macroalgal habitats might alter the way that blue cod forage, and how the trade-off between prey abundance and availability will affect its abundance and productivity. This thesis aims to understand the influence of complex macroalgal habitats on P. colias prey availability and behaviour, on the foraging success of P. colias, and ultimately on P. colias population dynamics. Experiments were conducted using choice chambers to evaluate whether two alternate P. colias prey, Forsterygion lapillum and Heterozius rotundifrons, showed a preference for complex habitats with and without predation risk. Both species preferred complex habitats in the absence of predation cues, but F. lapillum showed a more consistent preference for complexity in response to predation risk. A mesocosm experiment was used to investigate whether the consumption rate and functional response of P. colias differs for these two prey types in the presence and absence of habitat complexity. Results indicated that the mobile fish prey, F. lapillum benefitted from the refuges provided by complexity and suffered lower consumption rates, whereas the sedentary crab, H. rotundifrons did not. Finally, using a simple population model, the trade-off between prey abundance and predation success on the population dynamics of P. colias with and without habitat complexity was explored. Models showed that scenarios with complex macroalgal habitats generally support more predators, and faster population growth rates than scenarios lacking habitat complexity. However, scenarios with complex habitats were predicted to be more sensitive to fishing pressure and have the potential to be more vulnerable to overexploitation. These results highlight the importance of understanding how habitat complexity mediates relationships between commercially important fishery species and their prey, in order to understand how habitat loss may alter their foraging success and population dynamics.</p>


2021 ◽  
Author(s):  
◽  
Amber Brooks

<p>The long-term sustainability and security of food sources for an increasing human population will become more challenging as climate change alters growing and harvesting conditions. Significant infrastructure changes could be required to continue to supply food from traditional sources. Fisheries remain the only major protein supply directly harvested from the wild. This likely makes it the most sensitive primary sector to climate change. Overfishing is an additional concern for harvested species. There is a need to anticipate how marine species may respond to climate change to help inform how management might best be prepared for shifting distributions and productivity levels. The most common response of mobile marine species to changes in climate is an alteration of their geographic distributions and/or range shifts. Predicting changes to a species’ range could promote timely development of more sustainable harvest strategies. Additionally, these predictions could reduce potential conflict when different management areas experience increasing or decreasing catches. Ecological Niche Modelling (ENM) is a helpful approach for predicting the response of key fishery species to climate change scenarios.  The overall aim of this research was to use the maximum entropy method, Maxent, to perform ENM on 10 commercially important fishery species, managed under the Quota management system in Aotearoa (New Zealand). Occurrence data from trawl surveys were used along with climate layers from Bio-ORACLE to estimate the species niche and then predict distributions in four different future climate scenarios, called Representative Concentration Pathway Scenarios (RCPS), in both 2050 and 2100. With little consensus over the best settings and way to apply the Maxent method, hundreds of variations were tried for each species, and the best model chosen from trial experimentation.  In general, Maxent performed well, with evaluation metrics for best models showing little omission error and good discriminatory ability. There was, however, considerable variation between the different species responses to the future climate scenarios. Consistent with other studies, species able to tolerate sub-tropical or temperate conditions tended to expand southward, while subantarctic species generally contracted within their preferred environment. The increasing emissions or ‘business as usual’ climate change scenario consistently presented the most extreme difference from modern predictions. Northern regions of prediction, where sub-tropical or temperate species increased in probability of presence, were often highly uncertain due to novel conditions in future environments. Southern regions were usually less uncertain. Surface temperature consistently influenced base models more so than any other covariates considered, with the exception of bathymetry.  Some predictions showed common areas of relative stability, such as hoki and ling on the southern Chatham Rise, potentially indicating future refugia. The preservation of habitats in the putative refugia may be important for long-term fisheries resilience. Furthermore, most species that showed large predicted declines are currently heavily harvested and managed. Overfishing could compound the effects of climate change and put these fisheries at serious risk of collapse. Identification of potential refugial areas could aid strategy adjustments to fishing practice to help preserve stock viability. Additionally, when some species shift, there are areas where new fisheries may emerge.  This study offers a perspective of what future distributions could be like under different climate scenarios. The ENM predicts that the ‘business as usual’ scenario, where ‘greenhouse gas’ emissions continue to rise throughout the century, will have a negative impact on multiple aspects of distribution. However, in a reduced emissions scenario, less extreme range shifts are predicted. This study has provided a predictive approach to how fisheries in Aotearoa might change. The next step is to determine whether there is any evidence for the beginning of these changes and to consider how fisheries might best adapt.</p>


Diversity ◽  
2021 ◽  
Vol 13 (12) ◽  
pp. 618
Author(s):  
Jiehong Wei ◽  
Renxie Wu ◽  
Yongshuang Xiao ◽  
Haoran Zhang ◽  
Laith A. Jawad ◽  
...  

The genus Pampus contains seven valid species, which are commercially important fishery species in the Indo-Pacific area. Due to their highly similar external morphologies, Pampus liuorum has been proposed as a synonym of Pampus cinereus. In this study, partial sequences of COI (582 bp) and Cytb (1077 bp) were presented as potential DNA barcodes of six valid Pampus species and the controversial species P. liuorum. A species delimitation of the seven Pampus species was performed to verify their validities. Explicit COI barcoding gaps were found in all assessed species, except for P. liuorum and P. cinereus, which resulted from their smaller interspecific K2P distance (0.0034–0.0069). A Cytb barcoding gap (0.0200) of the two species was revealed, with a K2P distance ranging from 0.0237 to 0.0277. The longer Cytb fragment is thus a more suitable DNA barcode for the genus Pampus. In the genetic tree, using concatenated Cytb and COI sequences, the seven species reciprocally formed well-supported clades. Species delimitations with ABGD, GMYC, and bPTP models identified seven operational taxonomic units, which were congruent with the seven morphological species. Therefore, all of the seven analyzed species, including P. liuorum, should be kept as valid species.


2021 ◽  
Vol 8 ◽  
Author(s):  
Rod M. Connolly ◽  
David V. Fairclough ◽  
Eric L. Jinks ◽  
Ellen M. Ditria ◽  
Gary Jackson ◽  
...  

The ongoing need to sustainably manage fishery resources can benefit from fishery-independent monitoring of fish stocks. Camera systems, particularly baited remote underwater video system (BRUVS), are a widely used and repeatable method for monitoring relative abundance, required for building stock assessment models. The potential for BRUVS-based monitoring is restricted, however, by the substantial costs of manual data extraction from videos. Computer vision, in particular deep learning (DL) models, are increasingly being used to automatically detect and count fish at low abundances in videos. One of the advantages of BRUVS is that bait attractants help to reliably detect species in relatively short deployments (e.g., 1 h). The high abundances of fish attracted to BRUVS, however, make computer vision more difficult, because fish often obscure other fish. We build upon existing DL methods for identifying and counting a target fisheries species across a wide range of fish abundances. Using BRUVS imagery targeting a recovering fishery species, Australasian snapper (Chrysophrys auratus), we tested combinations of three further mathematical steps likely to generate accurate, efficient automation: (1) varying confidence thresholds (CTs), (2) on/off use of sequential non-maximum suppression (Seq-NMS), and (3) statistical correction equations. Output from the DL model was more accurate at low abundances of snapper than at higher abundances (&gt;15 fish per frame) where the model over-predicted counts by as much as 50%. The procedure providing the most accurate counts across all fish abundances, with counts either correct or within 1–2 of manual counts (R2 = 88%), used Seq-NMS, a 45% CT, and a cubic polynomial corrective equation. The optimised modelling provides an automated procedure offering an effective and efficient method for accurately identifying and counting snapper in the BRUV footage on which it was tested. Additional evaluation will be required to test and refine the procedure so that automated counts of snapper are accurate in the survey region over time, and to determine the applicability to other regions within the distributional range of this species. For monitoring stocks of fishery species more generally, the specific equations will differ but the procedure demonstrated here could help to increase the usefulness of BRUVS.


2021 ◽  
pp. 102015
Author(s):  
Muhammed Forruq Rahman ◽  
Shan Xiujuan ◽  
Lin Qun ◽  
Yunlong Chen ◽  
Md. Abdullah Al-Mamun ◽  
...  

Author(s):  
Ismael Esteban Lozano ◽  
Yanina Grisel Piazza ◽  
Paola Babay ◽  
Emanuel Sager ◽  
Fernando Román de la Torre ◽  
...  

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