Final Report Summary - EVOLBIRD (Demographic strategies under climate variation: a study on Arctic and Antarctic seabirds)
Project context and objectives
The Intergovernmental Panel on Climate Change (IPCC 2007) has highlighted an urgent need to assess how ecosystems respond to climate change. Polar ecosystems are highly sensitive ecosystems making them valuable sentinels of the health of our planet. Indeed, some of the strongest signals of global change come from polar regions (Hoegh-Guldberg and Bruno 2010), and several long-term monitoring studies suggest that the climate patterns of the past few decades may be anomalous when compared with earlier climate variation (Hughes 2000). Global change has profound ecological consequences on the population dynamics of long-lived organisms, such as most seabird species. Also, climate change will alter the evolutionary forces acting on species' demographic strategies and life history traits, as these have evolved to cope with the range of environmental fluctuations experienced in the past. This is especially important in long-lived species (e.g. Cairns 1992), which are typically the upper trophic level predators in ecosystems. Top-predators are therefore considered to be key indicators of short- and long-term changes in food-webs and food availability (Le Maho et al. 1993, Voigt et al. 2003), as they integrate and amplify the effects of climatic forcing on lower levels of food chains (Frederiksen et al. 2007). They are also suitable for studying whether the effects of climate change on top predators may be mitigated by (i) phenotypic plasticity and (ii) microevolutionary changes. Such studies require advanced knowledge of evolutionary and functional ecology, population dynamics and statistics: all of which were uniquely available at the Centre for Ecological and Evolutionary Synthesis where this EVOLBIRD Marie Curie project took place. Moreover, the comparison between the evolution of life history strategies of polar long-lived species in both hemispheres can provide supplementary elements for a better understanding of ecosystem functioning. In that context, the EVOLBIRD project was focused on the Southern Ocean (penguin populations) and on the Barents Sea/Arctic Ocean (kittiwake and guillemot populations).
The main aims of the EVOLBIRD Marie Curie project were (i) to identify the mechanisms through which environmental variability affects age-specific survival, recruitment parameters and breeding performance of polar seabirds, (ii) to determine the vital rates that contribute most to fitness, and (iii) to model the population dynamics of these species in order to predict population trends in relation to climatic changes. To summarise the main results obtained during the project:
First, most available information on penguin population dynamics is based on the controversial use of flipper bands. However, we showed that banding of free-ranging king penguins (Aptenodytes patagonicus) impairs both survival and reproduction, ultimately affecting population growth rate (Saraux et al. 2011). One of our major findings was also that responses of flipper-banded penguins to climate variability differ from those of non-banded birds, meaning that our understanding of the effects of climate change on marine ecosystems based on flipper-band data must be reconsidered. These deleterious effects, which also have serious ethical implications, can however be avoided with alternative methods, such as radiofrequency identification techniques (Le Maho et al. 2011).
Thus, based on more than ten years of automatic monitoring of over 3000 individuals, we investigated the effects of environmental conditions and individual pre-fledging traits on the post-fledging return of these non-banded king penguins to their natal colony (Saraux et al. 2011, Le Bohec et al. in prep). A key finding is that return rates (range 6887 %) were much higher than previously assumed for this species. We found that local survival was lower during their first year spent at sea while learning to forage for the first time, suggesting that lower quality individuals may disappear from cohorts especially during this first stressful event after fledging (i.e. the selection hypothesis). However, it might also result from an increase in foraging performance of individuals as they gain experience (i.e. the constraint hypothesis, Le Vaillant et al. submitted). Moreover, we observed a huge variance in survival during this first year in comparison with the other age classes. This variation between cohorts might be explained by the impact of the environment on specific (and maybe more sensitive) subsets of the population or at decisive phases of the life cycle.
Regardless of the cohort, we found king penguins attempting to breed for the first time between two and three years old. Among our cohorts that were fully recruited (which is between six and eight years), the mean age at the first breeding attempt is four years old (in contrast with the mean age at six years old found in the literature). Females appear to start breeding earlier than males. The shorter their first trip at sea, the earlier birds start to breed. And the better the conditions during growth, the later they start to breed. That last pattern might be explained by the fact that during better environmental conditions, a larger number of chicks survive the winter, even weaker ones, thus there is a greater proportion of lower-quality individuals, which drives the mean start of reproduction later.
Then, using the vital rates described above (age-specific breeding success and survival rate), stage-classified life cycle matrices were built, and, in accordance with life history theory, we found that the population growth rate is more affected by variation in adult survival than by the other vital rates (Le Bohec et al. in prep). However, we can also see the importance of early age survival on the population growth rate, meaning that we should pay more attention to this subset of populations when looking at the effects of climate on population dynamics. We also discovered that population growth rate is mainly sensitive to changes in temperature-dependent parameters such as the survival and breeding success of adult birds, but also post-fledging survival. Population projections were then simulated according to several IPCC warming scenarios. These projections indicate that the colony would reach quasi-extinction (a decline of 90 % of the initial population size) before the end of the 21st century. At the current rate of global changes, king penguins will probably not be able to cope and reverse the predicted population decline with micro-evolutionary changes or behavioural adjustments.
The same analyses are currently being performed for the black-legged kittiwake Rissa tridactyla breeding in Kharlov Island on the coast of the Barents Sea. The number of chicks per nest and survival probabilities were estimated between 1970-1999. Leslie matrix models are currently used to understand the relative importance of juvenile survival on population dynamics of kittiwakes and the influence of environmental fluctuations on the temporal variation in this vital rate.
The secondary objective of the EVOLBIRD project was to explore the adaptive responses of seabird populations to different environmental changes through microevolutionary processes. Thus, a study was started in order to i) identify the genetic structure and diversity of penguin colonies, and ii) evaluate gene flow between colonies within and between Archipelagos. To investigate the first question, our study was based on eight microsatellite loci and was performed using precisely geolocated samples within a continuous sub-section of the colony of La Baie du Marin (Crozet Archipelago). We found no evidence for strong structuring at the sub-colony level: although a number of spatially restricted areas have higher-than-random inbreeding and relatedness levels, the overall colony appears to be near-panmictic, with no obvious effect of philopatry on genetic and spatial structure (Cristofari et al. in prep). To explore gene flow between populations, blood samples were collected last season 2011/2012 in different penguin colonies and different sub-Antarctic archipelagos.
Studies on marine ecosystem dynamics are few and, especially for polar oceans, the time series are short and quantitative knowledge of the dynamics of interactions between predators, their prey, and the environment remains very limited. In this context, the EVOLBIRD Marie Curie project was focused on the polar marine ecosystem. Moreover, by using state-of-the-art technology, this project addressed major methodological and scientific issues. Moreover, in contributing to the understanding of the Antarctic and Arctic ecosystems and their responses to climate variability, this international and multidisciplinary project directly meets both European priorities regarding 'Environment' (a priority area for FP7 (The Seventh Framework Programme) with different aspects that match the present project: 'Climate change', 'Conservation and sustainable management of natural and man-made resources and biodiversity', 'Environmental technologies for observation', 'Earth and ocean observation systems, monitoring methods for the environment and sustainable development') and international priorities as defined by the Convention of Rio on biological diversity, IPCC (Intergovernmental Panel on Climate Change) and ICSU (International Council for Science).
References:
Cairns DK (1992) Population regulation of seabird colonies. In: Power DM (ed) Current ornithology, Dordrecht, The Netherlands: Kluwer Academic/Plenum, pp 37-62
Cristofari R, Trucchi E, Whittington J, Gachot H, Vigetta S, Le Maho Y, Stenseth NC, Le Bohec C (in prep) Spatial and genetic structuration of a king penguin colony. Philopatry and genetic diversity: the paradox of animal colonies
Frederiksen M, Mavor RA, Wanless S (2007) Seabirds as environmental indicators: the advantages of combining data sets. Mar Ecol Prog Ser 352:205-211
Hoegh-Guldberg O, Bruno JF (2010) The impact of climate change on the world's marine ecosystems. Science 328:1523
Hughes L (2000) Biological consequences of global warming: is the signal already apparent? Trends in Ecology and Evolution 15:5661
IPCC (2007) Climate Change 2007: Synthesis Report. Contribution of Working Groups I, II and III to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (eds Core Writing Team, Pachauri RK, Reisinger A)
Le Bohec C, Pradel R, Benoiste M, Whittington J, Saraux C, Durant JM, Gauthier-Clerc M, Le Vaillant M, Gachot H, Stenseth NC, Le Maho Y (in prep) How climate changes affect juvenile survival and recruitment in the King penguin
Le Bohec C, Sabarros P, Durant JM, Vindenes Y, Saraux C, Ergon T, Yoccoz G, Gauthier-Clerc M, Pradel R, Park YH, Friess B, Le Maho Y, Stenseth N (in prep) King penguins on the verge of extinction?
Le Maho Y, Gendner JP, Challet E, Bost CA, Gilles J, Verdon C, Plumeré C, Robin JP, Handrich Y (1993) Undisturbed breeding penguins as indicators of changes in marine resources. Mar Ecol Prog Ser 95:1-6
Le Maho Y, Saraux C, Durant J, Viblanc VA, Gauthier-Clerc M, Yoccoz N, Stenseth NC, Le Bohec C (2011) An ethical issue on biodiversity science: The monitoring of penguins with flipper-bands. Comp Rend Biol 334:378-384
Le Vaillant M, Wilson RP, Kato A, Saraux C, Hanuise N, Prud'Homme O, Le Maho Y, Le Bohec C and Ropert-Coudert Y (submitted) King penguins learn respiratory air load management with age
Saraux C, Le Bohec C, Durant JM, Viblanc VA, Gauthier-Clerc M, Beaune D, Park YH, Yoccoz NG, Stenseth NC, Le Maho Y (2011) Reliability of flipper-banded penguins as indicators of climate change. Nature 469:203-206
Saraux C, Viblanc VV, Hanuise N, Le Maho Y, Le Bohec C (2011) Effects of Individual Pre-Fledging Traits and Environmental Conditions on Return Patterns in Juvenile King Penguins. PloS One, 6:e20407
Voigt W, Perner J, Davis AJ, Eggers T, Schumacher J, Bährmann R, Fabian B, Heinrich, W, Köhler G, Lichter D, Marstaller R, Sander FW (2003) Trophic levels are differentially sensitive to climate. Ecology 84:2444-2453
The Intergovernmental Panel on Climate Change (IPCC 2007) has highlighted an urgent need to assess how ecosystems respond to climate change. Polar ecosystems are highly sensitive ecosystems making them valuable sentinels of the health of our planet. Indeed, some of the strongest signals of global change come from polar regions (Hoegh-Guldberg and Bruno 2010), and several long-term monitoring studies suggest that the climate patterns of the past few decades may be anomalous when compared with earlier climate variation (Hughes 2000). Global change has profound ecological consequences on the population dynamics of long-lived organisms, such as most seabird species. Also, climate change will alter the evolutionary forces acting on species' demographic strategies and life history traits, as these have evolved to cope with the range of environmental fluctuations experienced in the past. This is especially important in long-lived species (e.g. Cairns 1992), which are typically the upper trophic level predators in ecosystems. Top-predators are therefore considered to be key indicators of short- and long-term changes in food-webs and food availability (Le Maho et al. 1993, Voigt et al. 2003), as they integrate and amplify the effects of climatic forcing on lower levels of food chains (Frederiksen et al. 2007). They are also suitable for studying whether the effects of climate change on top predators may be mitigated by (i) phenotypic plasticity and (ii) microevolutionary changes. Such studies require advanced knowledge of evolutionary and functional ecology, population dynamics and statistics: all of which were uniquely available at the Centre for Ecological and Evolutionary Synthesis where this EVOLBIRD Marie Curie project took place. Moreover, the comparison between the evolution of life history strategies of polar long-lived species in both hemispheres can provide supplementary elements for a better understanding of ecosystem functioning. In that context, the EVOLBIRD project was focused on the Southern Ocean (penguin populations) and on the Barents Sea/Arctic Ocean (kittiwake and guillemot populations).
The main aims of the EVOLBIRD Marie Curie project were (i) to identify the mechanisms through which environmental variability affects age-specific survival, recruitment parameters and breeding performance of polar seabirds, (ii) to determine the vital rates that contribute most to fitness, and (iii) to model the population dynamics of these species in order to predict population trends in relation to climatic changes. To summarise the main results obtained during the project:
First, most available information on penguin population dynamics is based on the controversial use of flipper bands. However, we showed that banding of free-ranging king penguins (Aptenodytes patagonicus) impairs both survival and reproduction, ultimately affecting population growth rate (Saraux et al. 2011). One of our major findings was also that responses of flipper-banded penguins to climate variability differ from those of non-banded birds, meaning that our understanding of the effects of climate change on marine ecosystems based on flipper-band data must be reconsidered. These deleterious effects, which also have serious ethical implications, can however be avoided with alternative methods, such as radiofrequency identification techniques (Le Maho et al. 2011).
Thus, based on more than ten years of automatic monitoring of over 3000 individuals, we investigated the effects of environmental conditions and individual pre-fledging traits on the post-fledging return of these non-banded king penguins to their natal colony (Saraux et al. 2011, Le Bohec et al. in prep). A key finding is that return rates (range 6887 %) were much higher than previously assumed for this species. We found that local survival was lower during their first year spent at sea while learning to forage for the first time, suggesting that lower quality individuals may disappear from cohorts especially during this first stressful event after fledging (i.e. the selection hypothesis). However, it might also result from an increase in foraging performance of individuals as they gain experience (i.e. the constraint hypothesis, Le Vaillant et al. submitted). Moreover, we observed a huge variance in survival during this first year in comparison with the other age classes. This variation between cohorts might be explained by the impact of the environment on specific (and maybe more sensitive) subsets of the population or at decisive phases of the life cycle.
Regardless of the cohort, we found king penguins attempting to breed for the first time between two and three years old. Among our cohorts that were fully recruited (which is between six and eight years), the mean age at the first breeding attempt is four years old (in contrast with the mean age at six years old found in the literature). Females appear to start breeding earlier than males. The shorter their first trip at sea, the earlier birds start to breed. And the better the conditions during growth, the later they start to breed. That last pattern might be explained by the fact that during better environmental conditions, a larger number of chicks survive the winter, even weaker ones, thus there is a greater proportion of lower-quality individuals, which drives the mean start of reproduction later.
Then, using the vital rates described above (age-specific breeding success and survival rate), stage-classified life cycle matrices were built, and, in accordance with life history theory, we found that the population growth rate is more affected by variation in adult survival than by the other vital rates (Le Bohec et al. in prep). However, we can also see the importance of early age survival on the population growth rate, meaning that we should pay more attention to this subset of populations when looking at the effects of climate on population dynamics. We also discovered that population growth rate is mainly sensitive to changes in temperature-dependent parameters such as the survival and breeding success of adult birds, but also post-fledging survival. Population projections were then simulated according to several IPCC warming scenarios. These projections indicate that the colony would reach quasi-extinction (a decline of 90 % of the initial population size) before the end of the 21st century. At the current rate of global changes, king penguins will probably not be able to cope and reverse the predicted population decline with micro-evolutionary changes or behavioural adjustments.
The same analyses are currently being performed for the black-legged kittiwake Rissa tridactyla breeding in Kharlov Island on the coast of the Barents Sea. The number of chicks per nest and survival probabilities were estimated between 1970-1999. Leslie matrix models are currently used to understand the relative importance of juvenile survival on population dynamics of kittiwakes and the influence of environmental fluctuations on the temporal variation in this vital rate.
The secondary objective of the EVOLBIRD project was to explore the adaptive responses of seabird populations to different environmental changes through microevolutionary processes. Thus, a study was started in order to i) identify the genetic structure and diversity of penguin colonies, and ii) evaluate gene flow between colonies within and between Archipelagos. To investigate the first question, our study was based on eight microsatellite loci and was performed using precisely geolocated samples within a continuous sub-section of the colony of La Baie du Marin (Crozet Archipelago). We found no evidence for strong structuring at the sub-colony level: although a number of spatially restricted areas have higher-than-random inbreeding and relatedness levels, the overall colony appears to be near-panmictic, with no obvious effect of philopatry on genetic and spatial structure (Cristofari et al. in prep). To explore gene flow between populations, blood samples were collected last season 2011/2012 in different penguin colonies and different sub-Antarctic archipelagos.
Studies on marine ecosystem dynamics are few and, especially for polar oceans, the time series are short and quantitative knowledge of the dynamics of interactions between predators, their prey, and the environment remains very limited. In this context, the EVOLBIRD Marie Curie project was focused on the polar marine ecosystem. Moreover, by using state-of-the-art technology, this project addressed major methodological and scientific issues. Moreover, in contributing to the understanding of the Antarctic and Arctic ecosystems and their responses to climate variability, this international and multidisciplinary project directly meets both European priorities regarding 'Environment' (a priority area for FP7 (The Seventh Framework Programme) with different aspects that match the present project: 'Climate change', 'Conservation and sustainable management of natural and man-made resources and biodiversity', 'Environmental technologies for observation', 'Earth and ocean observation systems, monitoring methods for the environment and sustainable development') and international priorities as defined by the Convention of Rio on biological diversity, IPCC (Intergovernmental Panel on Climate Change) and ICSU (International Council for Science).
References:
Cairns DK (1992) Population regulation of seabird colonies. In: Power DM (ed) Current ornithology, Dordrecht, The Netherlands: Kluwer Academic/Plenum, pp 37-62
Cristofari R, Trucchi E, Whittington J, Gachot H, Vigetta S, Le Maho Y, Stenseth NC, Le Bohec C (in prep) Spatial and genetic structuration of a king penguin colony. Philopatry and genetic diversity: the paradox of animal colonies
Frederiksen M, Mavor RA, Wanless S (2007) Seabirds as environmental indicators: the advantages of combining data sets. Mar Ecol Prog Ser 352:205-211
Hoegh-Guldberg O, Bruno JF (2010) The impact of climate change on the world's marine ecosystems. Science 328:1523
Hughes L (2000) Biological consequences of global warming: is the signal already apparent? Trends in Ecology and Evolution 15:5661
IPCC (2007) Climate Change 2007: Synthesis Report. Contribution of Working Groups I, II and III to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (eds Core Writing Team, Pachauri RK, Reisinger A)
Le Bohec C, Pradel R, Benoiste M, Whittington J, Saraux C, Durant JM, Gauthier-Clerc M, Le Vaillant M, Gachot H, Stenseth NC, Le Maho Y (in prep) How climate changes affect juvenile survival and recruitment in the King penguin
Le Bohec C, Sabarros P, Durant JM, Vindenes Y, Saraux C, Ergon T, Yoccoz G, Gauthier-Clerc M, Pradel R, Park YH, Friess B, Le Maho Y, Stenseth N (in prep) King penguins on the verge of extinction?
Le Maho Y, Gendner JP, Challet E, Bost CA, Gilles J, Verdon C, Plumeré C, Robin JP, Handrich Y (1993) Undisturbed breeding penguins as indicators of changes in marine resources. Mar Ecol Prog Ser 95:1-6
Le Maho Y, Saraux C, Durant J, Viblanc VA, Gauthier-Clerc M, Yoccoz N, Stenseth NC, Le Bohec C (2011) An ethical issue on biodiversity science: The monitoring of penguins with flipper-bands. Comp Rend Biol 334:378-384
Le Vaillant M, Wilson RP, Kato A, Saraux C, Hanuise N, Prud'Homme O, Le Maho Y, Le Bohec C and Ropert-Coudert Y (submitted) King penguins learn respiratory air load management with age
Saraux C, Le Bohec C, Durant JM, Viblanc VA, Gauthier-Clerc M, Beaune D, Park YH, Yoccoz NG, Stenseth NC, Le Maho Y (2011) Reliability of flipper-banded penguins as indicators of climate change. Nature 469:203-206
Saraux C, Viblanc VV, Hanuise N, Le Maho Y, Le Bohec C (2011) Effects of Individual Pre-Fledging Traits and Environmental Conditions on Return Patterns in Juvenile King Penguins. PloS One, 6:e20407
Voigt W, Perner J, Davis AJ, Eggers T, Schumacher J, Bährmann R, Fabian B, Heinrich, W, Köhler G, Lichter D, Marstaller R, Sander FW (2003) Trophic levels are differentially sensitive to climate. Ecology 84:2444-2453
