Task team 2018/03 (Former 2016/06): Modelling animal behaviour in a changing climate.
For highly mobile marine top predators, movement ecology fundamentally underpins the spatial distribution of populations and their response to change. Study of animal movement at-sea is reliant on electronic tags attached to individuals, which is providing increasingly detailed records over longer periods. The 3rd CLIOTOP Symposium included many presentations using electronic tracking data within a variety of modelling approaches exploring and projecting changes in response to habitat features. At the final discussion session it was highlighted that these were predominantly statistical correlative approaches, and there was a notable lack of mechanistic or process-based modelling. The currently popular habitat selectivity and related resource utilisation techniques are phenomenological, correlating animals’ use of space with environmental attributes but being generally blind to the process(es) that underlie animal movement patterns and interactions with the environment. Although there is value in characterising species’ current habitat preferences, approaches that explicitly model movement dynamics, and associated behavioural processes, and their ties to environmental features should be better able to provide robust projections of species’ future distributions in a changing environment. This is currently a key gap – and opportunity – for integrating a mechanistic understanding of how animals use marine areas (e.g. for feeding, migrating) into spatial models of species habitat utilisation and distribution.
The specific aims of this task team are to design and work through, to closure, the necessary steps for developing robust predictions of marine predator at-sea distributions under current and future climate scenarios. This work is premised on using individual-based movement data from satellite telemetry devices combined with state-of-the-art statistical modelling tools for inference of animal movement patterns, associated behaviour and habitat preference (Patterson et al. 2008; Langrock et al. 2012; Jonsen et al. 2013). The first phase of the work plans to develop and implement methodological approaches on a selected case study, followed by a second phase expanding the implementation across multiple species.
The primary output will be a set of robust statistical methods for the modelling of animal movement patterns, estimation of habitat preference/use and projection of at-sea distribution and habitat use under current and future climate scenarios in the Southern Ocean. These will be made available through a fully documented, publicly available R package
Clear and defined linkages are planned to be developed with task team 2016/05, “Assessing variability in the movement patterns of marine predator populations”.
Task team 2018/02 (Former 2016/04): Operational Oceanography for supporting Sustainability of Top Predators (OOSTOP).
Task team leader: Diego Álvarez Berastegui.
Current research presented at the 3rd CLIOTOP symposium highlights the key role that operational oceanography is playing for investigating top predators ecological-environmental dependencies. Operational oceanography data sources, such as marine in situ and remote sensing data and hydrodynamic models, allow for the development of new methods for characterizing the state and variability of the ocean and for improving current stock assessment and management approaches. Effective application of these tools require linking multidisciplinary working groups including experts on marine ecology, operational oceanography and those responsible for species assessment and management.
The objectives of this task team are to:
- Use and integrate the existing operational oceanography tools to improve current assessment and management methods applied for the sustainability of top predators (i.e, stock assessment, design of MPAs), and investigate the potential of giving “early warning”of e.g . survival and growth of early life stages.
- Connect multidisciplinary working groups (marine ecology, oceanography, assessment and management) to identify potential knowledge transference (links) and main challenges.
- Promote the design of operational oceanography data products informing about ecological processes with relevance for assessment/management.
- Provide researchers, focused on ecology of top predators, with examples of successful case studies where operational oceanography had a direct impact on assessment and management for sustainable exploitation and conservation.
Outputs will include:
- A network of researchers investigating the ocean variability, operational oceanography, fish essential habitats, and top predators assessment and management.
- Report of data-requirements destined to the main operational oceanography data providers on the basis of top predator management for sustainable exploitation and conservation goals.
- Open source software interchange among developers and researchers.
- Meeting on operational oceanography for top predators.
- Compilation and dissemination of successful study cases.
Task team 2018/01 (Former 2016/03): Dynamic ocean management and seasonal forecasting for pelagic ecosystems.
Task team leader: Kylie Scales @KylieScales
The world’s oceans are under an unprecedented level of pressure from resource use and commercial activities — for example, fisheries, shipping, aquaculture, and mineral, natural gas, and oil extraction. Balancing sustainable ecological and economic objectives is a continuing challenge for resource managers. Management approaches that can address these growing pressures have been the focus of considerable research and agency action, yet marine resource management has generally lagged behind those in terrestrial systems. However, for systems built upon dynamic oceanography and with species that transit ocean basins regularly, more targeted approaches are needed. Dynamic approaches could solve these problems, particularly in the face of a changing climate as traditional management boundaries such as marine protected areas, international borders, and even ecologically and biologically significant areas (EBSAs) are frequently crossed.
The task team will investigate the following broad areas:
- Identify existing habitat models that could be used in a forecasting framework, e.g. starting with Temperature both surface (SST) and at depth where available.
- Create a summary table / document of key biological variables, eEOVs (ecological Essential Ocean Variables) that are available for the building on Hayes et al 2015
- A historical approach for those species that need more than SST – use past events as a simple forward looking approach
- Concept of scale and persistence of habitat may be a technique for estimating condition.
- Reach out to forage fish modeling efforts (e.g. forage fish task force) as they serve as keystone species for forecasting efforts.
- Identify case study areas / species for where dynamic forecasting is used, but also where past examples could be used to identify new approaches.
A following objective is the development of a reliable predictive capability for the dynamics of top predator populations and oceanic ecosystems that combines both fishing and climate (i.e. environmental) effects. Dynamic forecasting using operational oceanographic products can provide an early warning of population and fishery response. In addition, dynamic forecasting is inherently climate ready.
Task team 2017/01: (Former 2016/01) Global comparative analysis of marine trophodynamics inferred by stable isotopes in top order predators.
This task team represents an international collaborative effort to move from regional trophic studies of top marine predators to a global comparative study of oceanic food webs using stable isotope compositions of three wide-ranging tuna species: albacore (Thunnus alalunga), yellowfin (T. albacares) and bigeye (T. obesus). Nitrogen (δ15N) and carbon (δ13C) stable isotopes are widely-utilized biogeochemical tracers of trophic dynamics and are commonly employed to estimate trophic positions and habitat usage patterns of marine predators. Predictive models will be used to undertake an inter-oceanic comparison of δ15N values, derived from a coupled ocean circulation-biogeochemical-isotope model. A similar approach will be taken with lipid-corrected δ13C values, to examine differences in carbon-based primary production influences. Environmental variables (SST, Chl-a, net primary productivity, and mixed layer depth) will be included to explore the influence of global oceanographic processes on the isotopic compositions of the tuna species. The team will also devise a plan for future trophodynamics work including undertaking similar global comparative analyses for other marine species occupying varying trophic positions in marine food webs. The team will discuss the use of additional increasingly used biochemical tools, such as fatty acids, trace metals, and compound-specific stable isotopes, which will further the comparative efforts of this task team
Expected outputs from this task team will consist of a global database of biogeochemical tracers from tunas sampled in all major ocean basins (from each season ranging the years 2001-2015) and a scientific paper that will be of high interest to the marine ecological community. The database will facilitate future comparative analysis and research into food web structure and function. Importantly, we will produce oceanographic maps that characterise the global distribution of these tuna isotopes and associated trophodynamics, which will provide valuable depictions of trophic links for food-web models thus facilitating global evaluation of climate effects on exploited ecosystems.
Task team 2016/05: Assessing variability in the movement patterns of marine predator populations.
Many marine predator species demonstrate spatial and temporal variability in their movement behaviours. Variation in life history strategies can result in some species/populations undertaking larger movements in comparison to other species/populations and utilising what can be quite different habitats. Movement patterns have evolved to maximize prey resources and top predators respond to temporal and spatial variability in environmental conditions, including potentially long-term change. Movement can rarely be observed directly however, and research increasingly relies on bio-telemetry devices to estimate movement. Errors inherent in observation processes create challenges for distinguishing real biological signals from data collected. Methods that acknowledge such uncertainties are required. Consequently, considerable effort has been placed into methods that provide insights into the foraging behaviour and individual search strategies of marine species, each of which incorporate position estimate uncertainty to varying degrees.
This task team will investigate the movement behaviours of a range of marine species including flying and diving seabirds, turtles, mammals and fish derived from tag technologies used ranging in scale from coarse (geolocation) through medium (ARGOS) to fine (GPS). The task team will firstly assess three metrics (step length, turning angle and step speed) for their appropriateness as simple descriptors of complex movements and their utility in robust analyses of movement across species, telemetry platforms and uncertainty scales. Secondly, using the most appropriate metrics identified in the assessment the task team will undertake an assessment of movement in relation to a number of processes including:
- Type of movement: Central place vs ‘free movement’
- Guild: fish, mammal, seabird
- Reproductive state: Reproductive vs non reproductive
- Latitude: Polar vs tropical vs sub-tropical vs temperate
- Body size
Outputs from the task team will provide clear guidance on the use of metrics when assessing movement in marine animals and identify robust metrics that can be used across technologies, species and spatial scales of movement to assess short term variability and longer term change.
Task team 2016/02: Building scenarios for the sustainability of global oceanic ecosystems and fisheries.
Task team leader: Olivier Maury.