Incorporating climate-readiness into fisheries management strategies.

Tropical oceans are among the first places to exhibit climate change signals, affecting the habitat distribution and abundance of marine fish. These changes to stocks, and subsequent impacts on fisheries production, may have considerable implications for coastal communities dependent on fisheries for food security and livelihoods. Understanding the impacts of climate change on tropical marine fisheries is therefore an important step towards developing sustainable, climate-ready fisheries management measures. We apply an established method of spatial meta-analysis to assess species distribution modelling datasets for key species targeted by the Philippines capture fisheries. We analysed datasets under two global emissions scenarios (RCP4.5 and RCP8.5) and varying degrees of fishing pressure to quantify potential climate vulnerability of the target community. We found widespread responses to climate change in pelagic species in particular, with abundances projected to decline across much of the case study area, highlighting the challenges of maintaining food security in the face of a rapidly changing climate. We argue that sustainable fisheries management in the Philippines in the face of climate change can only be achieved through management strategies that allow for the mitigation of, and adaptation to, pressures already locked into the climate system for the near term. Our analysis may support this, providing fisheries managers with the means to identify potential climate change hotspots, bright spots and refugia, thereby supporting the development of climate-ready management plans.

Bright spots as climate-smart marine spatial planning tools for conservation and blue growth.

Marine spatial planning that addresses ocean climate-driven change ('climate-smart MSP') is a global aspiration to support economic growth, food security and ecosystem sustainability. Ocean climate change ('CC') modelling may become a key decision-support tool for MSP, but traditional modelling analysis and communication challenges prevent their broad uptake. We employed MSP-specific ocean climate modelling analyses to inform a real-life MSP process; addressing how nature conservation and fisheries could be adapted to CC. We found that the currently planned distribution of these activities may become unsustainable during the policy's implementation due to CC, leading to a shortfall in its sustainability and blue growth targets. Significant, climate-driven ecosystem-level shifts in ocean components underpinning designated sites and fishing activity were estimated, reflecting different magnitudes of shifts in benthic versus pelagic, and inshore versus offshore habitats. Supporting adaptation, we then identified: CC refugia (areas where the ecosystem remains within the boundaries of its present state); CC hotspots (where climate drives the ecosystem towards a new state, inconsistent with each sectors' present use distribution); and for the first time, identified bright spots (areas where oceanographic processes drive range expansion opportunities that may support sustainable growth in the medium term). We thus create the means to: identify where sector-relevant ecosystem change is attributable to CC; incorporate resilient delivery of conservation and sustainable ecosystem management aims into MSP; and to harness opportunities for blue growth where they exist. Capturing CC bright spots alongside refugia within protected areas may present important opportunities to meet sustainability targets while helping support the fishing sector in a changing climate. By capitalizing on the natural distribution of climate resilience within ocean ecosystems, such climate-adaptive spatial management strategies could be seen as nature-based solutions to limit the impact of CC on ocean ecosystems and dependent blue economy sectors, paving the way for climate-smart MSP.

Habitat partitioning in Antarctic krill: Spawning hotspots and nursery areas.

Antarctic krill, Euphausia superba, have a circumpolar distribution but are concentrated within the south-west Atlantic sector, where they support a unique food web and a commercial fishery. Within this sector, our first goal was to produce quantitative distribution maps of all six ontogenetic life stages of krill (eggs, nauplii plus metanauplii, calyptopes, furcilia, juveniles, and adults), based on a compilation of all available post 1970s data. Using these maps, we then examined firstly whether "hotspots" of egg production and early stage nursery occurred, and secondly whether the available habitat was partitioned between the successive life stages during the austral summer and autumn, when krill densities can be high. To address these questions, we compiled larval krill density records and extracted data spanning 41 years (1976-2016) from the existing KRILLBASE-abundance and KRILLBASE-length-frequency databases. Although adult males and females of spawning age were widely distributed, the distribution of eggs, nauplii and metanauplii indicates that spawning is most intense over the shelf and shelf slope. This contrasts with the distributions of calyptope and furcilia larvae, which were concentrated further offshore, mainly in the Southern Scotia Sea. Juveniles, however, were strongly concentrated over shelves along the Scotia Arc. Simple environmental analyses based on water depth and mean water temperature suggest that krill associate with different habitats over the course of their life cycle. From the early to late part of the austral season, juvenile distribution moves from ocean to shelf, opposite in direction to that for adults. Such habitat partitioning may reduce intraspecific competition for food, which has been suggested to occur when densities are exceptionally high during years of strong recruitment. It also prevents any potential cannibalism by adults on younger stages. Understanding the location of krill spawning and juvenile development in relation to potentially overlapping fishing activities is needed to protect the health of the south-west Atlantic sector ecosystem.