Stephanie Brodie

Improving consumption rate estimates by incorporating wild activity into a bioenergetics model

Abstract Consumption is the basis of metabolic and trophic ecology and is used to assess an animals trophic impact. The contribution of activity to an animals energy budget is an important parameter when estimating consumption, yet activity is usually measured in captive animals. Developments in telemetry have allowed the energetic costs of activity to be measured for wild animals; however, wild activity is seldom incorporated into estimates of consumption rates. We calculated the consumption rate of a free‐ranging marine predator (yellowtail kingfish, Seriola lalandi) by integrating the energetic cost of free‐ranging activity into a bioenergetics model. Accelerometry transmitters were used in conjunction with laboratory respirometry trials to estimate kingfish active metabolic rate in the wild. These field‐derived consumption rate estimates were compared with those estimated by two traditional bioenergetics methods. The first method derived routine swimming speed from fish morphology as an index of activity (a “morphometric” method), and the second considered activity as a fixed proportion of standard metabolic rate (a “physiological” method). The mean consumption rate for free‐ranging kingfish measured by accelerometry was 152 J·g−1·day−1, which lay between the estimates from the morphometric method (μ = 134 J·g−1·day−1) and the physiological method (μ = 181 J·g−1·day−1). Incorporating field‐derived activity values resulted in the smallest variance in log‐normally distributed consumption rates (σ = 0.31), compared with the morphometric (σ = 0.57) and physiological (σ = 0.78) methods. Incorporating field‐derived activity into bioenergetics models probably provided more realistic estimates of consumption rate compared with the traditional methods, which may further our understanding of trophic interactions that underpin ecosystem‐based fisheries management. The general methods used to estimate active metabolic rates of free‐ranging fish could be extended to examine ecological energetics and trophic interactions across aquatic and terrestrial ecosystems.

Australia’s continental-scale acoustic tracking database and its automated quality control process

Our ability to predict species responses to environmental changes relies on accurate records of animal movement patterns. Continental-scale acoustic telemetry networks are increasingly being established worldwide, producing large volumes of information-rich geospatial data. During the last decade, the Integrated Marine Observing System’s Animal Tracking Facility (IMOS ATF) established a permanent array of acoustic receivers around Australia. Simultaneously, IMOS developed a centralised national database to foster collaborative research across the user community and quantify individual behaviour across a broad range of taxa. Here we present the database and quality control procedures developed to collate 49.6 million valid detections from 1891 receiving stations. This dataset consists of detections for 3,777 tags deployed on 117 marine species, with distances travelled ranging from a few to thousands of kilometres. Connectivity between regions was only made possible by the joint contribution of IMOS infrastructure and researcher-funded receivers. This dataset constitutes a valuable resource facilitating meta-analysis of animal movement, distributions, and habitat use, and is important for relating species distribution shifts with environmental covariates.

Integrating Dynamic Subsurface Habitat Metrics Into Species Distribution Models

Species distribution models (SDMs) have become key tools for describing and predicting species habitats. In the marine domain, environmental data used in modelling species distributions are often remotely sensed, and as such have limited capacity for interpreting the vertical structure of the water column, or are sampled in situ, offering minimal spatial and temporal coverage. Advances in ocean models have improved our capacity to explore subsurface ocean features, yet there has been limited integration of such features in SDMs. Using output from a data-assimilative configuration of the Regional Ocean Modeling System, we examine the effect of including dynamic subsurface variables in SDMs to describe the habitats of four pelagic predators in the California Current System (swordfish Xiphias gladius, blue sharks Prionace glauca, common thresher sharks Alopias vulpinus, and shortfin mako sharks Isurus oxyrinchus). Species data were obtained from the California Drift Gillnet observer program (1997-2017). We used boosted regression trees to explore the incremental improvement enabled by dynamic subsurface variables that quantify the structure and stability of the water column: isothermal layer depth and bulk buoyancy frequency. The inclusion of these dynamic subsurface variables significantly improved model explanatory power for most species. Model predictive performance also significantly improved, but only for species that had strong affiliations with dynamic variables (swordfish and shortfin mako sharks) rather than static variables (blue sharks and common thresher sharks). Geospatial predictions for all species showed the integration of isothermal layer depth and bulk buoyancy frequency contributed value at the mesoscale level (<100 km) and varied spatially throughout the study domain. These results highlight the utility of including dynamic subsurface variables in SDM development and support the continuing ecological use of biophysical output from ocean circulation models.

Continental-scale animal tracking reveals functional movement classes across marine taxa

Acoustic telemetry is a principle tool for observing aquatic animals, but coverage over large spatial scales remains a challenge. To resolve this, Australia has implemented the Integrated Marine Observing System’s Animal Tracking Facility which comprises a continental-scale hydrophone array and coordinated data repository. This national acoustic network connects localized projects, enabling simultaneous monitoring of multiple species over scales ranging from 100 s of meters to 1000 s of kilometers. There is a need to evaluate the utility of this national network in monitoring animal movement ecology, and to identify the spatial scales that the network effectively operates over. Cluster analyses assessed movements and residency of 2181 individuals from 92 species, and identified four functional movement classes apparent only through aggregating data across the entire national network. These functional movement classes described movement metrics of individuals rather than species, and highlighted the plasticity of movement patterns across and within populations and species. Network analyses assessed the utility and redundancy of each component of the national network, revealing multiple spatial scales of connectivity influenced by the geographic positioning of acoustic receivers. We demonstrate the significance of this nationally coordinated network of receivers to better reveal intra-specific differences in movement profiles and discuss implications for effective management.

The influence of ontogenetic diet variation on consumption rate estimates: a marine example

Consumption rates are the foundation of trophic ecology, yet bioenergetics models used to estimate these rates can lack realism by not incorporating the ontogeny of diet. We constructed a bioenergetics model of a marine predatory fish (tailor, Pomatomus saltatrix) that incorporated high-resolution ontogenetic diet variation, and compared consumption estimates to those derived from typical bioenergetics models that do not consider ontogenetic diet variation. We found tailor consumption was over- or under-estimated by ~5–25% when only including the most common prey item. This error was due to a positive relationship between mean prey energy density and predator body size. Since high-resolution diet data isn’t always available, we also simulated how increasing dietary information progressively influenced consumption rate estimates. The greatest improvement in consumption rate estimates occurred when diet variation of 2–3 stanzas (1–2 juvenile stanzas, and adults) was included, with at least 5–6 most common prey types per stanza. We recommend increased emphasis on incorporating the ontogeny of diet and prey energy density in consumption rate estimates, especially for species with spatially segregated life stages or variable diets. A small-moderate increase in the resolution of dietary information can greatly benefit the accuracy of estimated consumption rates. We present a method of incorporating variable prey energy density into bioenergetics models.

Applying acoustic telemetry to understand contaminant exposure and bioaccumulation patterns in mobile fishes

Contamination in urbanised estuaries presents a risk to human health, and to the viability of populations of exploited species. Assessing animal movements in relation to contaminated areas may help to explain patterns in bioaccumulation, and assist in the effective management of health risks associated with consumption of exploited species. Using polychlorinated dibenzodioxin and polychlorinated dibenzofuran (PCDD/Fs) contamination in Sydney Harbour estuary as a case study, we present a study that links movement patterns resolved using acoustic telemetry to the accumulation of contaminants in mobile fish on a multi-species basis. Fifty-four individuals across six exploited species (Sea Mullet Mugil cephalus; Luderick Girella tricuspidata; Yellowfin Bream Acanthopagrus australis; Silver Trevally Pseudocaranx georgianus; Mulloway Argyrosomus japonicus; Yellowtail Kingfish Seriola lalandi) were tagged with acoustic transmitters, and their movements tracked for up to 3years. There was substantial inter-specific variation in fish distribution along the estuary. The proportion of distribution that overlapped with contaminated areas explained 84-98% of the inter-specific variation in lipid-standardised biota PCDD/F concentration. There was some seasonal variation in distribution along the estuary, but movement patterns indicated that Sea Mullet, Yellowfin Bream, Silver Trevally, and Mulloway were likely to be exposed to contaminated areas during the period of gonadal maturation. Acoustic telemetry allows examination of spatial and temporal patterns in exposure to contamination. When used alongside biota sampling and testing, this offers a powerful approach to assess exposure, bioaccumulation, and potential risks faced by different species, as well as human health risks associated with their consumption.

A Framework for Combining Seasonal Forecasts and Climate Projections to Aid Risk Management for Fisheries and Aquaculture

A changing climate, in particular a warming ocean, is likely to impact marine industries in a variety of ways. For example, aquaculture businesses may not be able to maintain production in their current location into the future, or area-restricted fisheries may need to follow the fish as they change distribution. Preparation for these potential climate impacts can be improved with information about the future. Such information can support a risk-based management strategy for industries exposed to both short-term environmental variability and long-term change. In southern Australia, adverse climate impacts on valuable seafood industries have occurred, and they are now seeking advice about future environmental conditions. We introduce a decision tree to explain the potential use of long-term climate projections and seasonal forecasts by these industries. Climate projections provide insight into the likely time in the future when current locations will no longer be suitable for growing or catching particular species. Until this time, seasonal forecasting is beneficial in helping industries plan ahead to reduce impacts in poor years and maximise opportunities in good years. Use of seasonal forecasting can extend the period of time in which industries can cope in a location as environmental suitability declines due to climate change. While a range of short-term forecasting approaches exist, including persistence and climatological forecasts, only dynamic model forecasts provide a viable option for managing environmental risk for marine industries in regions where climate change is reducing environmental suitability and creating novel conditions.

Practical considerations for operationalizing dynamic management tools

Dynamic management (DM) is a novel approach to spatial management that aligns scales of environmental variability, animal movement and human uses. While static approaches to spatial management rely on one‐time assessments of biological, environmental, economic, and/or social conditions, dynamic approaches repeatedly assess conditions to produce regularly updated management recommendations. Owing to this complexity, particularly regarding operational challenges, examples of applied DM are rare. To implement DM, scientific methodologies are operationalized into tools, i.e., self‐contained workflows that run automatically at a prescribed temporal frequency (e.g., daily, weekly, monthly). Here we present a start‐to‐finish framework for operationalizing DM tools, consisting of four stages: Acquisition, Prediction, Dissemination, and Automation. We illustrate this operationalization framework using an applied DM tool as a case study. Our DM tool operates in near real‐time and was designed to maximize target catch and minimize bycatch of non‐target and protected species in a US‐based commercial fishery. It is important to quantify the sensitivity of DM tools to missing data, because dissemination streams for observed (i.e., remotely sensed or directly sampled) data can experience delays or gaps. To address this issue, we perform a detailed example sensitivity analysis using our case study tool. Synthesis and applications. Dynamic management (DM) tools are emerging as viable management solutions to accommodate the biological, environmental, economic, and social variability in our fundamentally dynamic world. Our four‐stage operationalization framework and case study can facilitate the implementation of DM tools for a wide array of resource and disturbance management objectives.;