Ocean warming threatens key trophic interactions supporting a commercial fishery in a climate change hotspot.

Worldwide, rising ocean temperatures are causing declines and range shifts in marine species. The direct effects of climate change on the biology of marine organisms are often well documented; yet, knowledge on the indirect effects, particularly through trophic interactions, is largely lacking. We provide evidence of ocean warming decoupling critical trophic interactions supporting a commercially important mollusc in a climate change hotspot. Dietary assessments of the Australian blacklip abalone (Haliotis rubra) indicate primary dependency on a widespread macroalgal species (Phyllospora comosa) which we show to be in state of decline due to ocean warming, resulting in abalone biomass reductions. Niche models suggest further declines in P. comosa over the coming decades and ongoing risks to H. rubra. This study highlights the importance of studies from climate change hotspots and understanding the interplay between climate and trophic interactions when determining the likely response of marine species to environmental changes.

Fishery independent survey datasets of abalone populations on subtidal coastal reefs in southeastern Australia.

Assessing the status or exploited marine fish populations often relies on fishery dependent catch and effort data reported by licensed commercial fishers in compliance with regulations and by recreational anglers voluntarily. This invariably leads to bias towards the fraction of a fish population or community that can be legally fished i.e., the stock as defined by legal minimum lengths and spatial boundaries. Data are restricted to populations which continue to be exploited at the expense of obtaining data on previously exploited and unexploited populations [1,2], so if a fishery is contracting spatially over time, then successively less of the overall fish community is monitored with bias towards where biomass is highest or most accessible [3]. A viable alternative is to conduct population monitoring surveys independently of a fishery to obtain information that is more broadly representative of the abundance, composition and size structure of fish communities and their supporting habitats [4-6]. Whereas catch and effort data often must be de-identified and aggregated to protect the confidentiality of fishers' commercial and personal interests, this constraint does not exist for independently acquired monitoring data, collected at public expense and hence publicly available at high levels of spatial and temporal resolution. Time series underpins the utility of fishery independent survey (FIS) datasets in terms of the life histories of exploited fish species and the time frames of their responses to various combinations of fishing mortality and environmental fluctuations and trends [7]. One-off surveys can establish a baseline and spatial distribution pattern, but regular surveys conducted consistently over time are necessary to detect trends from which population status can be inferred. We present several unique datasets focused on the commercially valuable blacklip abalone (Haliotis rubra), spanning three decades of annually collected data from up to 204 locations on subtidal rocky reefs along a coastline of almost 2500 km, the State of Victoria, Australia. It is rare for data to be collected consistently at this intensity over such a long period of monitoring [2], especially with surveys conducted by small teams of highly skilled research divers, some of whom up until recently had participated in every year. The data comprises ∼28,000 records from ∼4500 site surveys conducted during 1992 to 2021 [2]. Although the fixed site design remained unchanged, the number of sites surveyed varied over time, mostly increasing in number periodically, and the survey method was refined on several occasions. We defined three different variants in the survey method due to technological advancement for both enumerating abalone abundance and measuring shell size structure [7]. The relative abundance counts were standardized using a Bayesian generalized linear mixed model (GLMM) to test for interannual trends whilst allowing for inherent differences among sites, research divers, and their interactions [8].

Initial impacts of the COVID-19 pandemic on Australian fisheries production, research organisations and assessment: shocks, responses and implications for decision support and resilience.

Australia's fisheries have experience in responding individually to specific shocks to stock levels (for example, marine heatwaves, floods) and markets (for example, global financial crisis, food safety access barriers). The COVID-19 pandemic was, however, novel in triggering a series of systemic shocks and disruptions to the activities and operating conditions for all Australia's commercial fisheries sectors including those of the research agencies that provide the information needed for their sustainable management. While these disruptions have a single root cause-the public health impacts and containment responses to the COVID-19 pandemic-their transmission and effects have been varied. We examine both the impacts on Australian fisheries triggered by measures introduced by governments both internationally and domestically in response to the COVID-19 pandemic outbreak, and the countermeasures introduced to support continuity in fisheries and aquaculture production and supply chains. Impacts on fisheries production are identified by comparing annual and monthly catch data for Australia's commercial fisheries in 2020 with averages for the last 4-5 years. We combine this with a survey of the short-term disruption to and impacts on research organisations engaged in fisheries monitoring and assessment and the adaptive measures they deployed. The dominant impact identified was triggered by containment measures both within Australia and in export receiving countries which led to loss of export markets and domestic dine-in markets for live or fresh seafood. The most heavily impact fisheries included lobster and abalone (exported live) and specific finfishes (exported fresh or sold live domestically), which experienced short-term reductions in both production and price. At the same time, improved prices and demand for seafood sold into domestic retail channels were observed. The impacts observed were both a function of the disruptions due to the COVID-19 pandemic and the countermeasures and support programs introduced by various national and state-level governments across Australia to at least partly mitigate negative impacts on harvesting activities and supply chains. These included protecting fisheries activities from specific restrictive COVID-19 containment measures, pro-actively re-establishing freight links, supporting quota roll-overs, and introducing wage and businesses support packages. Fisheries research organisations were impacted to various degrees, largely determined by the extent to which their field monitoring activities were protected from specific restrictive COVID-19 containment measures by their state-level governments. Responses of these organisations included reducing fisheries dependent and independent data collection as required while developing strategies to continue to provide assessment services, including opportunistic innovations to harvest data from new data sources. Observed short run impacts of the COVID-19 pandemic outbreak has emphasised both the vulnerability of fisheries dependent on export markets, live or fresh markets, and long supply chains and the resilience of fisheries research programs. We suggest that further and more comprehensive analysis over a longer time period of the long-run impacts of subsequent waves of variants, extended pandemic containment measures, autonomous and planned adaptive responses would be beneficial for the development of more effective counter measures for when the next major external shock affects Australian fisheries.

DEB-IBM for predicting climate change and anthropogenic impacts on population dynamics of hairtail Trichiurus lepturus in the East China Sea.

The hairtail Trichiurus lepturus supports the largest fisheries in the East China Sea. The stock has fluctuated in the past few decades and this variation has been attributed to human pressures and climate change. To investigate energetics of individuals and population dynamics of the species in responses to environmental variations and fishing efforts, we have developed a DEB-IBM by coupling a dynamic energy budget (DEB) model to an individual-based model (IBM). The parameter estimation of DEB model shows an acceptable goodness of fit. The DEB-IBM was validated with histological data for a period of 38 years. High fishing pressure was largely responsible for the dramatic decline of the stock in middle 1980s. The stock recovered from early 1990s, which coincided with introduction of fishing moratorium on spawning stocks in inshore waters and substantial decrease of fishing efforts from large fisheries companies. In addition, the population average age showed a trend of slight decrease. The model successfully reproduced these observations of interannual variations in the population dynamics. The model was then implemented to simulate the effect of climate change on the population performance under greenhouse gas emission scenarios projected for 2100. It was also used to explore population responses to changing fishing mortalities. These scenario simulations have shown that the population biomass under SSP1-1.9, SSP2-4.5 and SSP5-8.5 would decline by 7.5%, 16.6% and 30.1%, respectively, in 2100. The model predicts that increasing fishing mortality by 10% will cause 5.3% decline of the population biomass, whereas decrease of fishing mortality by 10% will result in 6.8% increase of the biomass. The development of the DEB-IBM provides a predictive tool to inform management decisions for sustainable exploitation of the hairtail stock in the East China Sea.

Historical fish survey datasets from productive aquatic ecosystems in Lithuania.

Many inland ecosystems (lakes, rivers, reservoirs, lagoons) around the world undergo regular biological monitoring surveys, including monitoring the abundance, biomass and size structure of fish communities. Yet, the majority of fish monitoring datasets for inland ecosystems remain inaccessible. This is especially true for historical datasets from the early and middle 20th century, despite their immense importance for establishing baselines of ecosystem status (e.g., prior to manifestations of climate change and intensive fisheries impacts), assessing the current status of fish stocks, and more generally determining temporal changes in fish populations. Here we present a newly digitized fish monitoring dataset for two major Lithuanian inland ecosystems - Curonian Lagoon and Kaunas Water Reservoir. The data comprises >60000 records from >800 fish surveys conducted during 1950s to 1980s, using a range of fishing gears and sampling methods. We introduce three different definitions for survey methods to describe the level of detail for each fish community study. Method 1 surveys include individual fish sizes and weights, Method 2 surveys record frequencies of fish in length or weight groups, whereas Method 3 only records the total catch biomass of a given species. The majority of historical and currently collected fish survey data can be attributed to one of these three methods and we present R codes to convert data from higher resolution methods into aggregated data formats, to facilitate data sharing. In addition, commercial fisheries catch data for years that were surveyed are also provided. The data presented here can facilitate ecological and fisheries analyses of baseline ecosystem status before the onsets of rapid warming and eutrophication, exploration of fish size structure, evaluation of different catch per unit effort standardization methods, and assessment of population responses to commercial fishing.

Exploring Spatiotemporal Trends in Commercial Fishing Effort of an Abalone Fishing Zone: A GIS-Based Hotspot Model.

Assessing patterns of fisheries activity at a scale related to resource exploitation has received particular attention in recent times. However, acquiring data about the distribution and spatiotemporal allocation of catch and fishing effort in small scale benthic fisheries remains challenging. Here, we used GIS-based spatio-statistical models to investigate the footprint of commercial diving events on blacklip abalone (Haliotis rubra) stocks along the south-west coast of Victoria, Australia from 2008 to 2011. Using abalone catch data matched with GPS location we found catch per unit of fishing effort (CPUE) was not uniformly spatially and temporally distributed across the study area. Spatial autocorrelation and hotspot analysis revealed significant spatiotemporal clusters of CPUE (with distance thresholds of 100's of meters) among years, indicating the presence of CPUE hotspots focused on specific reefs. Cumulative hotspot maps indicated that certain reef complexes were consistently targeted across years but with varying intensity, however often a relatively small proportion of the full reef extent was targeted. Integrating CPUE with remotely-sensed light detection and ranging (LiDAR) derived bathymetry data using generalized additive mixed model corroborated that fishing pressure primarily coincided with shallow, rugose and complex components of reef structures. This study demonstrates that a geospatial approach is efficient in detecting patterns and trends in commercial fishing effort and its association with seafloor characteristics.

Cormorant catch concerns for fishers: estimating the size-selectivity of a piscivorous bird.

Conflict arises in fisheries worldwide when piscivorous birds target fish species of commercial value. This paper presents a method for estimating size selectivity functions for piscivores and uses it to compare predation selectivities of Great Cormorants (Phalacrocorax carbo sinensis L. 1758) with that of gill-net fishing on a European perch (Perca fluviatilis L. 1758) population in the Curonian Lagoon, Lithuania. Fishers often regard cormorants as an unwanted "satellite species", but the degree of direct competition and overlap in size-specific selectivity between fishers and cormorants is unknown. This study showed negligible overlap in selectivity between Great Cormorants and legal-sized commercial nets. The selectivity estimation method has general application potential for use in conjunction with population dynamics models to assess fish population responses to size-selective fishing from a wide range of piscivorous predators.