Polychlorinated Biphenyl DDT And Dieldrin Residues In Grey Seal (Halichoerus-Grypus) Males Females And Mother-Foetus Pairs Sampled At The Farne Islands England During The Breeding-Season

PCB, DDT, DDE, dieldrin and total non-polar organohalogen residues have been determined in the blubber-lipid of grey seals (Halichoerus grypus) sampled during the 1972 breeding season (November) at the Farne Islands off the north eastern coast of England. PCBs were analysed by gas-liquid chromatography linked to a chlorine- and carbon-selective microwave plasma detector and total organohalogen residues were determined by microcoulometry. Total organohalogen residues were negatively correlated with blubber thickness and positively correlated with age in males (aged 1 to 24 y) and females (aged 5 to 38 y). However, the correlation of blubber-lipid residue with age in males depended upon the inclusion of immature (aged < 6 y) animals, and in females reflected only a small residue increment. The mean blubber organohalogen concentration of the males was significantly greater than that of the females. PCB and DDT group residue concentrations were significantly correlated. PCB, DDT, DDE and dieldrin were detected in the liver of mother/foetus pairs demonstrating transplacental movement of these residues. The possibility of the condition of the seals at breeding time influencing residue levels and of these residues influencing the health of the population is discussed.

Regional and annual variation in black-legged kittiwake breeding productivity is related to sea surface temperature

Spatiotemporal variation in seabird demographic parameters is often pronounced and may be an important source of information on the state of marine ecosystems. Black-legged kittiwakes Rissa tridactyla in Britain and Ireland show strong regional structure in breeding productivity, and both temporal and spatial variation are probably related to abundance of the principal prey of breeding kittiwakes, the lesser sandeel Ammodytes marinus. Annual regional estimates of sandeel abundance do not exist, prohibiting direct tests of this hypothesis. We examined relationships between kittiwake breeding productivity and 2 potential proxies of sandeel abundance, winter sea surface temperature (SST) and abundance of Calanus copepods, within and among 6 regions in Britain and Ireland from 1986 to 2004. Means and trends in winter SST differed among regions, with higher means and less pronounced increasing trends in western (Atlantic) regions than in eastern (North Sea) regions. A negative relationship between breeding productivity and winter SST in the previous year was found within 2 regions (East Scotland and Orkney), as well as in a cross-regional analysis. Results were inconclusive for Calanus abundance, with a positive relationship in East Scotland and negative in Orkney. These results demonstrate that although a single environmental driver (SST) is related to both within- and between-region variation in a key demographic parameter, regional heterogeneity in SST trends as well as the importance of other factors may lead to highly variable responses. Understanding this heterogeneity is critical for predicting long-term effects of climate change or other anthropogenic drivers on marine ecosystems.

Identifying predictable foraging habitats for a wide-ranging marine predator using ensemble ecological niche models

Aim: Ecological niche modelling can provide valuable insight into species' environmental preferences and aid the identification of key habitats for populations of conservation concern. Here, we integrate biologging, satellite remote-sensing and ensemble ecological niche models (EENMs) to identify predictable foraging habitats for a globally important population of the grey-headed albatross (GHA) Thalassarche chrysostoma. Location: Bird Island, South Georgia; Southern Atlantic Ocean. Methods: GPS and geolocation-immersion loggers were used to track at-sea movements and activity patterns of GHA over two breeding seasons (n = 55; brood-guard). Immersion frequency (landings per 10-min interval) was used to define foraging events. EENM combining Generalized Additive Models (GAM), MaxEnt, Random Forest (RF) and Boosted Regression Trees (BRT) identified the biophysical conditions characterizing the locations of foraging events, using time-matched oceanographic predictors (Sea Surface Temperature, SST; chlorophyll a, chl-a; thermal front frequency, TFreq; depth). Model performance was assessed through iterative cross-validation and extrapolative performance through cross-validation among years. Results: Predictable foraging habitats identified by EENM spanned neritic (<500 m), shelf break and oceanic waters, coinciding with a set of persistent biophysical conditions characterized by particular thermal ranges (3–8 °C, 12–13 °C), elevated primary productivity (chl-a > 0.5 mg m−3) and frequent manifestation of mesoscale thermal fronts. Our results confirm previous indications that GHA exploit enhanced foraging opportunities associated with frontal systems and objectively identify the APFZ as a region of high foraging habitat suitability. Moreover, at the spatial and temporal scales investigated here, the performance of multi-model ensembles was superior to that of single-algorithm models, and cross-validation among years indicated reasonable extrapolative performance. Main conclusions: EENM techniques are useful for integrating the predictions of several single-algorithm models, reducing potential bias and increasing confidence in predictions. Our analysis highlights the value of EENM for use with movement data in identifying at-sea habitats of wide-ranging marine predators, with clear implications for conservation and management.

Identifying predictable foraging habitats for a wide-ranging marine predator using ensemble ecological niche models

Aim: Ecological niche modelling can provide valuable insight into species' environmental preferences and aid the identification of key habitats for populations of conservation concern. Here, we integrate biologging, satellite remote-sensing and ensemble ecological niche models (EENMs) to identify predictable foraging habitats for a globally important population of the grey-headed albatross (GHA) Thalassarche chrysostoma. Location: Bird Island, South Georgia; Southern Atlantic Ocean. Methods: GPS and geolocation-immersion loggers were used to track at-sea movements and activity patterns of GHA over two breeding seasons (n = 55; brood-guard). Immersion frequency (landings per 10-min interval) was used to define foraging events. EENM combining Generalized Additive Models (GAM), MaxEnt, Random Forest (RF) and Boosted Regression Trees (BRT) identified the biophysical conditions characterizing the locations of foraging events, using time-matched oceanographic predictors (Sea Surface Temperature, SST; chlorophyll a, chl-a; thermal front frequency, TFreq; depth). Model performance was assessed through iterative cross-validation and extrapolative performance through cross-validation among years. Results: Predictable foraging habitats identified by EENM spanned neritic (<500 m), shelf break and oceanic waters, coinciding with a set of persistent biophysical conditions characterized by particular thermal ranges (3–8 °C, 12–13 °C), elevated primary productivity (chl-a > 0.5 mg m−3) and frequent manifestation of mesoscale thermal fronts. Our results confirm previous indications that GHA exploit enhanced foraging opportunities associated with frontal systems and objectively identify the APFZ as a region of high foraging habitat suitability. Moreover, at the spatial and temporal scales investigated here, the performance of multi-model ensembles was superior to that of single-algorithm models, and cross-validation among years indicated reasonable extrapolative performance. Main conclusions: EENM techniques are useful for integrating the predictions of several single-algorithm models, reducing potential bias and increasing confidence in predictions. Our analysis highlights the value of EENM for use with movement data in identifying at-sea habitats of wide-ranging marine predators, with clear implications for conservation and management.