RESUMO
The grey rockcod, Lepidonotothen squamifrons is an important prey species for seals, penguins and Patagonian toothfish (Dissostichus eleginoides) in the Southern Ocean. Across the Kerguelen Plateau, the species was fished to commercial extinction (ca. 152 000 tonnes between 1971 and 1978) prior to the declaration of the French Exclusive Economic Zone in 1979 and the Australian Fishing Zone in 1981. In this study we estimate; age, growth, maturity, sex ratio, body condition (weight-at-length), and population density of grey rockcod using data from 19 trawl surveys from 1990 to 2014. There appeared to be three distinct geographical populations, with differences in biological parameters within each population. This study has identified separate metapopulations within the southern region of the Kerguelen Plateau and we recommend that management should take into account the different characteristics of these populations, and that this meta-population structure may be a factor in why this species required several decades to show signs of recovery.
Assuntos
Perciformes , Dinâmica Populacional , Animais , Perciformes/crescimento & desenvolvimento , Perciformes/fisiologia , Feminino , Masculino , Ilhas , Densidade DemográficaRESUMO
The emergence of longline fishing around the world has been concomitant with an increase in depredation-interactions by odontocete whales (removal of fish caught on hooks), resulting in substantial socio-economic and ecological impacts. The extent, trends and underlying mechanisms driving these interactions remain poorly known. Using long-term (2003-2017) datasets from seven major Patagonian toothfish (Dissostichus eleginoides) longline fisheries, this study assessed the levels and inter-annual trends of sperm whale (Physeter macrocephalus) and/or killer whale (Orcinus orca) interactions as proportions of fishing time (days) and fishing area (spatial cells). The role of fishing patterns in explaining between-fisheries variations of probabilities of odontocete interactions was investigated. While interaction levels remained globally stable since the early 2000s, they varied greatly between fisheries from 0 to >50% of the fishing days and area. Interaction probabilities were influenced by the seasonal concentration of fishing effort, size of fishing areas, density of vessels, their mobility and the depth at which they operated. The results suggest that between-fisheries variations of interaction probabilities are largely explained by the extent to which vessels provide whales with opportunities for interactions. Determining the natural distribution of whales will, therefore, allow fishers to implement better strategies of spatio-temporal avoidance of depredation.
Assuntos
Pesqueiros , Cachalote/fisiologia , Orca/fisiologia , Animais , Oceano Atlântico , Oceano Índico , Modelos Teóricos , Estações do AnoRESUMO
Natural populations of plants and animals spatially cluster because (1) suitable habitat is patchy, and (2) within suitable habitat, individuals aggregate further into clusters of higher density. We compare the precision of random and systematic field sampling survey designs under these two processes of species clustering. Second, we evaluate the performance of 13 estimators for the variance of the sample mean from a systematic survey. Replicated simulated surveys, as counts from 100 transects, allocated either randomly or systematically within the study region, were used to estimate population density in six spatial point populations including habitat patches and Matérn circular clustered aggregations of organisms, together and in combination. The standard one-start aligned systematic survey design, a uniform 10 x 10 grid of transects, was much more precise. Variances of the 10 000 replicated systematic survey mean densities were one-third to one-fifth of those from randomly allocated transects, implying transect sample sizes giving equivalent precision by random survey would need to be three to five times larger. Organisms being restricted to patches of habitat was alone sufficient to yield this precision advantage for the systematic design. But this improved precision for systematic sampling in clustered populations is underestimated by standard variance estimators used to compute confidence intervals. True variance for the survey sample mean was computed from the variance of 10 000 simulated survey mean estimates. Testing 10 published and three newly proposed variance estimators, the two variance estimators (v) that corrected for inter-transect correlation (ν8 and ν(W)) were the most accurate and also the most precise in clustered populations. These greatly outperformed the two "post-stratification" variance estimators (ν2 and ν3) that are now more commonly applied in systematic surveys. Similar variance estimator performance rankings were found with a second differently generated set of spatial point populations, ν8 and ν(W) again being the best performers in the longer-range autocorrelated populations. However, no systematic variance estimators tested were free from bias. On balance, systematic designs bring more narrow confidence intervals in clustered populations, while random designs permit unbiased estimates of (often wider) confidence interval. The search continues for better estimators of sampling variance for the systematic survey mean.