Abstract: IUGG 2011 Melbourne Australia.

Abstract: Many seabirds are attracted to fishing boats where they exploit foraging opportunities, often involving bycatch-related mortality. Bycatch risk is generally estimated by overlapping seabirds foraging ranges with coarse-scale monthly maps of fishing efforts, but a more direct estimation would be the time birds actually spend attending fishing boats. Here we matched data from Automatic Identification Systems from all declared boats in the Southern Ocean, with 143 simultaneous foraging trips from all populations of large albatrosses (Diomedea amsterdamensis and Diomedea exulans) breeding in the Indian Ocean (Marion, Crozet, Kerguelen, Amsterdam islands). We quantified and compared real-time co-occurrence between boats and albatrosses, at different scales (100, 30 and 5 km). We also examined to what extent co-occurrence at a large-scale (5×5° grid cell) predicted fine-scale attendance (5 km). Albatrosses on average spent about 3 h per trip attending fishing boats (<5 km) at both Amsterdam and Marion and about 30 h per trip at Kerguelen. In all populations, >90% of declared fishing boat attendances occurred within Economic Exclusive Zones (EEZ) where bycatch mitigation measures are enforced. Outside EEZs, birds from all populations to a large extent also attended non-fishing boats. Fishing boat density at a large scale (5 × 5°, 100 km) was a poor predictor of time spent attending fishing boats (<5 km) across populations. Our results indicate a large variation in fishing boat densities within the foraging ranges of different populations and in the time birds spent attending boats. We discuss the pros and cons of considering bycatch risk at a large geographical scale and methods that can be implemented to improve the estimation of seabird vulnerability to fishing activities when fine-scale data are available, particularly for the conservation of those highly threatened species.

Abstract: This study deals with the problem of identifying atmospheric data influenced by local emissions that can result in spikes in time series of greenhouse gases and long-lived tracer measurements. We considered three spike detection methods known as coefficient of variation (COV), robust extraction of baseline signal (REBS) and standard deviation of the background (SD) to detect and filter positive spikes in continuous greenhouse gas time series from four monitoring stations representative of the European ICOS (Integrated Carbon Observation System) Research Infrastructure network. The results of the different methods are compared to each other and against a manual detection performed by station managers. Four stations were selected as test cases to apply the spike detection methods: a continental rural tower of 100 m height in eastern France (OPE), a high-mountain observatory in the south-west of France (PDM), a regional marine background site in Crete (FKL) and a marine clean-air background site in the Southern Hemisphere on Amsterdam Island (AMS). This selection allows us to address spike detection problems in time series with different variability. Two years of continuous measurements of CO2, CH4 and CO were analysed. All methods were found to be able to detect short-term spikes (lasting from a few seconds to a few minutes) in the time series. Analysis of the results of each method leads us to exclude the COV method due to the requirement to arbitrarily specify an a priori percentage of rejected data in the time series, which may over- or underestimate the actual number of spikes. The two other methods freely determine the number of spikes for a given set of parameters, and the values of these parameters were calibrated to provide the best match with spikes known to reflect local emissions episodes that are well documented by the station managers. More than 96 % of the spikes manually identified by station managers were successfully detected both in the SD and the REBS methods after the best adjustment of parameter values. At PDM, measurements made by two analyzers located 200 m from each other allow us to confirm that the CH4 spikes identified in one of the time series but not in the other correspond to a local source from a sewage treatment facility in one of the observatory buildings. From this experiment, we also found that the REBS method underestimates the number of positive anomalies in the CH4 data caused by local sewage emissions. As a conclusion, we recommend the use of the SD method, which also appears to be the easiest one to implement in automatic data processing, used for the operational filtering of spikes in greenhouse gases time series at global and regional monitoring stations of networks like that of the ICOS atmosphere network.

Abstract: The level of solar modulation at different times (related to the solar activity) is a central question of solar and galactic cosmic-ray physics. In the first paper of this series, we have established a correspondence between the uncertainties on ground-based detectors count rates and the parameter ϕ (modulation level in the force-field approximation) reconstructed from these count rates. In this second paper, we detail a procedure to obtain a reference ϕ time series from neutron monitor data. We show that we can have an unbiased and accurate ϕ reconstruction (Δϕ/ϕ≃10%). We also discuss the potential of Bonner spheres spectrometers and muon detectors to provide ϕ time series. Two by-products of this calculation are updated ϕ values for the cosmic-ray database and a web interface to retrieve and plot ϕ from the 50’s to today (http://lpsc.in2p3.fr/crdb).

Abstract: Population consequences of chronic exposure to multiple pollutants at low environmental doses remain speculative, because of the lack of appropriate long-term monitoring surveys. This study integrates proximate and ultimate aspects of persistent organic pollutants (POP) burden in free-living vertebrates, by coupling hormonal and behavioral endpoints, life-history traits, and population dynamics. Blood samples (N=70) were collected in South polar skuas during two breeding periods, in 2003 and 2005, and individuals were annually monitored until 2011. Multi-state mark recapture models were used to test the effects of POP levels on demographic traits. Survival rate and long-term breeding probability were not related to individual POP levels, whereas long-term breeding success significantly decreased with increasing blood levels of mirex, an organochlorine insecticide. At the proximate level, corticosterone (stress hormone) and prolactin (parental care hormone) levels were not linked to individual POP burden. Nest defense in 2005 was significantly less intensive in chick-rearing skuas bearing higher mirex levels, suggesting reproductive behavioral impairment. Matrix population models were then built to project the rate of population decline according to increasing mirex burden. Although mirex levels were 2.8 times higher in 2003 than in 2005, the population-level effect of mirex was only detected in 2005, the year of higher corticosterone levels. The combination of endocrine traits with demographic analysis thereby enables to provide new support of synergistic interactions between pollutants and stress levels on long-term breeding outputs and population dynamics.