Journal articles
Witt M, Hawkes L, Exeter O, Kerry C, Rudd J, Henderson S, Kukulya A, Yoda N, Whelan S (In Press). Autonomous underwater videography and tracking of basking sharks. Animal Biotelemetry
Rudd JR, Bartolomeu T, Dolton HR, Exeter OM, Kerry C, Hawkes L, Henderson SM, Shirley M, Witt MJ (In Press). Basking shark sub-surface behaviour revealed by animal-towed cameras. PLoS One
Witt M, Hawkes L, Exeter O, Kerry C, Rudd J, Hall J, Hall G, Henderson S (In Press). High resolution biologging of breaching by the world's second largest shark species. Scientific Reports
Witt M, Exeter O, Bicknell A, Kerry C, Htut T, Kyi MM, Mizrahi M, Turner R (In Press). Shining light on data-poor coastal fisheries. Frontiers in Marine Science
Collins C, Kerry C, de Vos A, Karnad D, Nuno A, Letessier TB (2023). Changes in illegal fishing dynamics in a large-scale MPA during COVID-19. Current Biology, 33(16), R851-R852.
Kerry CR, Exeter OM, Witt MJ (2022). Monitoring global fishing activity in proximity to seamounts using automatic identification systems.
Fish and Fisheries,
23(3), 733-749.
Abstract:
Monitoring global fishing activity in proximity to seamounts using automatic identification systems
AbstractSeamounts are prominent features of the seafloor that are often located in Areas Beyond National Jurisdiction (ABNJs). Whilst comprehensive biological information is lacking on most of these features, they have been recognised for hosting high biodiversity across multiple trophic levels. Technological advancements have enabled greater exploitation of biological resources further offshore with increasing concern over the long‐term impacts of anthropogenic activities on vulnerable distant and deep‐sea habitats. Analysis of ex situ vessel tracking technologies such as Automatic Identification Systems (AIS) have enabled spatial patterns of fishing activity to be monitored over large geographical areas. In this study, analysis of fishing activity within 30 km of seamount summits at the global scale found that these features within the waters of the Pacific Island Group and the Mediterranean Sea were subject to the highest levels of longlining and trawling activities respectively. Fishing in proximity to seamounts is dominated by the flag states of Taiwan, China, Japan, South Korea and Spain. Furthermore, our results reveal that the majority of sea areas managed by many Regional Fishery Management Organisations (RFMOs) have experienced increased fishing activity at seamounts compared to areas in the same ocean basin without management. This study demonstrates how free web‐accessible data can be used to gain insights into remote areas where in situ research is prohibitively expensive and logistically challenging.
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Vieira WF, Kerry C, Hockings KJ (2019). A comparison of methods to determine chimpanzee home-range size in a forest-farm mosaic at Madina in Cantanhez National Park, Guinea-Bissau.
Primates,
60(4), 355-365.
Abstract:
A comparison of methods to determine chimpanzee home-range size in a forest-farm mosaic at Madina in Cantanhez National Park, Guinea-Bissau.
Human activities impact the distribution of numerous species. Anthropogenic habitats are often fragmented, and wildlife must navigate through human-influenced and 'natural' parts of the landscape to access resources. Different methods to determine the home-range areas of nonhuman primates have not considered the additional complexities of ranging in anthropogenic areas. Here, using 6 months of spatial data on the distribution of chimpanzee presence (feces, feeding traces, nests, opportunistic encounters; n = 833) collected across the wet and dry seasons, we examine different analytical techniques to calculate the home-range size of an unhabituated chimpanzee (Pan troglodytes verus) community inhabiting a forest-farm mosaic at Madina, Cantanhez National Park in Guinea-Bissau. The minimum convex polygon method and the grid cell (500 m × 500 m cell size) method estimated the chimpanzees home-range size at 19.02 and 15.50 km2, respectively with kernel analysis calculating a lower value of 8.52 km2. For the grid cell method, home-range estimates varied with cell size, with larger cells producing larger estimates. We compare our home-range estimates with other chimpanzee research sites across Africa. We recommend the use of kernel analysis for determining primate home ranges, especially for those groups exploiting fragmented habitats including forest-farm mosaics, as this method takes account of inaccessible or infrequently used anthropogenic areas across the complete home range of the primate group. However, care must be taken when using this method, since it is sensitive to small sample sizes that can occur when studying unhabituated communities, resulting in underestimated home ranges.
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