Limits...
Predicting climate change impacts on polar bear litter size.

Molnár PK, Derocher AE, Klanjscek T, Lewis MA - Nat Commun (2011)

Bottom Line: In western Hudson Bay, we predict climate warming-induced litter size declines that jeopardize population viability: ∼28% of pregnant females failed to reproduce for energetic reasons during the early 1990s, but 40-73% could fail if spring sea ice break-up occurs 1 month earlier than during the 1990s, and 55-100% if break-up occurs 2 months earlier.Simultaneously, mean litter size would decrease by 22-67% and 44-100%, respectively.Similar litter size declines may occur in over one-third of the global polar bear population.

View Article: PubMed Central - PubMed

Affiliation: Department of Mathematical and Statistical Sciences, University of Alberta, Edmonton, Alberta, Canada T6G 2G1. pmolnar@ualberta.ca

ABSTRACT
Predicting the ecological impacts of climate warming is critical for species conservation. Incorporating future warming into population models, however, is challenging because reproduction and survival cannot be measured for yet unobserved environmental conditions. In this study, we use mechanistic energy budget models and data obtainable under current conditions to predict polar bear litter size under future conditions. In western Hudson Bay, we predict climate warming-induced litter size declines that jeopardize population viability: ∼28% of pregnant females failed to reproduce for energetic reasons during the early 1990s, but 40-73% could fail if spring sea ice break-up occurs 1 month earlier than during the 1990s, and 55-100% if break-up occurs 2 months earlier. Simultaneously, mean litter size would decrease by 22-67% and 44-100%, respectively. The expected timeline for these declines varies with climate-model-specific sea ice predictions. Similar litter size declines may occur in over one-third of the global polar bear population.

Show MeSH

Related in: MedlinePlus

Method to estimate changes in litter size under earlier on-shore arrival.The logic of our analyses is illustrated for a female with straight-line body length L=1.9 m that hunted on the sea ice until 1 August and came ashore with body mass MA=350 kg on that date (solid square). We first establish her body masses before and after on-shore arrival, subject to the constraint MA=350 kg. Before on-shore arrival body masses (1 June to 1 August) are estimated by projecting MA backwards in time under the Early (green dashed line, EFS) and Late Feeding (blue dot-dashed line, LFS) scenarios, respectively. After 1 August, body mass is lost because of on-shore fasting in both scenarios (green-blue dashed line), resulting in a den entry (1 October) body mass of 311.1 kg. Energy density at den entry is thus 30.25 MJ kg−1, implying an expected mean litter size X=2.86 (equations (1)–(3)equations (1)–(3)equations (1)–(3)). Next, on-shore fasting is initiated at an earlier date (1 July in this example; arrows) with on-shore arrival body mass equalling the body mass obtained for that date under Early and Late Feeding, ME and ML, respectively. In this example, ME=350 kg (solid circle) and ML=313.1 kg (solid diamond). Mass loss due to fasting then results in den entry body masses 292.4 kg and 259.6 kg, den entry energy densities 28.64 MJ kg−1, and 25.50 MJ kg−1, and expected mean litter sizes XE=2.49 and XL=1.88, under the Early (dashed line) and Late (dot-dashed line) Feeding scenarios, respectively.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC3105343&req=5

f2: Method to estimate changes in litter size under earlier on-shore arrival.The logic of our analyses is illustrated for a female with straight-line body length L=1.9 m that hunted on the sea ice until 1 August and came ashore with body mass MA=350 kg on that date (solid square). We first establish her body masses before and after on-shore arrival, subject to the constraint MA=350 kg. Before on-shore arrival body masses (1 June to 1 August) are estimated by projecting MA backwards in time under the Early (green dashed line, EFS) and Late Feeding (blue dot-dashed line, LFS) scenarios, respectively. After 1 August, body mass is lost because of on-shore fasting in both scenarios (green-blue dashed line), resulting in a den entry (1 October) body mass of 311.1 kg. Energy density at den entry is thus 30.25 MJ kg−1, implying an expected mean litter size X=2.86 (equations (1)–(3)equations (1)–(3)equations (1)–(3)). Next, on-shore fasting is initiated at an earlier date (1 July in this example; arrows) with on-shore arrival body mass equalling the body mass obtained for that date under Early and Late Feeding, ME and ML, respectively. In this example, ME=350 kg (solid circle) and ML=313.1 kg (solid diamond). Mass loss due to fasting then results in den entry body masses 292.4 kg and 259.6 kg, den entry energy densities 28.64 MJ kg−1, and 25.50 MJ kg−1, and expected mean litter sizes XE=2.49 and XL=1.88, under the Early (dashed line) and Late (dot-dashed line) Feeding scenarios, respectively.

Mentions: Next, we followed a two-step approach to determine how the distribution of energy densities at den entry, and thus the distribution of litter sizes at den emergence, will be affected if pregnant females are forced ashore early (see Methods for details). First, we determined the distribution of energy densities at on-shore arrival and den entry in a representative sample of adult females without dependent offspring (N=40) caught during the early 1990s. Second, using a dynamic energy budget model283132 to track changes in body mass, storage energy and energy density due to feeding, somatic maintenance and movement, we estimated how energy densities at on-shore arrival and den entry, and thus litter sizes at den emergence, will change with earlier on-shore arrival (see Fig. 2 and Methods). This second step requires on-ice feeding rate estimates to quantify the energetic impacts of a shortened hunting period. However, on-ice feeding rates are unknown for Hudson Bay, and it is also unclear how these rates vary seasonally. We therefore considered two feeding scenarios, 'Early Feeding' and 'Late Feeding', which estimate likely boundaries for the impacts of earlier on-shore arrival (Fig. 2). Early Feeding assumes that bears can only accumulate storage energy until the end of May (that is, during, and shortly after, seal pupping333435) and that feeding during the remaining on-ice period is reduced to rates that are just sufficient for bears to maintain acquired body mass. For earlier on-shore arrival, the Early Feeding scenario probably overestimates litter sizes at den emergence, because it only considers prolonged fasting but not potential losses in feeding. In the Late Feeding scenario, we account for both the prolonged fast and for missed feeding opportunities by assuming high energy intake during June and July, similar to intake rates in the High Arctic35. Bears accumulate much of their storage energy just before on-shore arrival with Late Feeding, so that females forced ashore early not only fast longer before den entry but they also come ashore in poorer body condition. This scenario probably overestimates the energetic impact of earlier on-shore arrival (thus underestimating litter sizes at den emergence), because summer feeding rates in Hudson Bay are likely lower than in the High Arctic (Supplementary Methods).


Predicting climate change impacts on polar bear litter size.

Molnár PK, Derocher AE, Klanjscek T, Lewis MA - Nat Commun (2011)

Method to estimate changes in litter size under earlier on-shore arrival.The logic of our analyses is illustrated for a female with straight-line body length L=1.9 m that hunted on the sea ice until 1 August and came ashore with body mass MA=350 kg on that date (solid square). We first establish her body masses before and after on-shore arrival, subject to the constraint MA=350 kg. Before on-shore arrival body masses (1 June to 1 August) are estimated by projecting MA backwards in time under the Early (green dashed line, EFS) and Late Feeding (blue dot-dashed line, LFS) scenarios, respectively. After 1 August, body mass is lost because of on-shore fasting in both scenarios (green-blue dashed line), resulting in a den entry (1 October) body mass of 311.1 kg. Energy density at den entry is thus 30.25 MJ kg−1, implying an expected mean litter size X=2.86 (equations (1)–(3)equations (1)–(3)equations (1)–(3)). Next, on-shore fasting is initiated at an earlier date (1 July in this example; arrows) with on-shore arrival body mass equalling the body mass obtained for that date under Early and Late Feeding, ME and ML, respectively. In this example, ME=350 kg (solid circle) and ML=313.1 kg (solid diamond). Mass loss due to fasting then results in den entry body masses 292.4 kg and 259.6 kg, den entry energy densities 28.64 MJ kg−1, and 25.50 MJ kg−1, and expected mean litter sizes XE=2.49 and XL=1.88, under the Early (dashed line) and Late (dot-dashed line) Feeding scenarios, respectively.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3105343&req=5

f2: Method to estimate changes in litter size under earlier on-shore arrival.The logic of our analyses is illustrated for a female with straight-line body length L=1.9 m that hunted on the sea ice until 1 August and came ashore with body mass MA=350 kg on that date (solid square). We first establish her body masses before and after on-shore arrival, subject to the constraint MA=350 kg. Before on-shore arrival body masses (1 June to 1 August) are estimated by projecting MA backwards in time under the Early (green dashed line, EFS) and Late Feeding (blue dot-dashed line, LFS) scenarios, respectively. After 1 August, body mass is lost because of on-shore fasting in both scenarios (green-blue dashed line), resulting in a den entry (1 October) body mass of 311.1 kg. Energy density at den entry is thus 30.25 MJ kg−1, implying an expected mean litter size X=2.86 (equations (1)–(3)equations (1)–(3)equations (1)–(3)). Next, on-shore fasting is initiated at an earlier date (1 July in this example; arrows) with on-shore arrival body mass equalling the body mass obtained for that date under Early and Late Feeding, ME and ML, respectively. In this example, ME=350 kg (solid circle) and ML=313.1 kg (solid diamond). Mass loss due to fasting then results in den entry body masses 292.4 kg and 259.6 kg, den entry energy densities 28.64 MJ kg−1, and 25.50 MJ kg−1, and expected mean litter sizes XE=2.49 and XL=1.88, under the Early (dashed line) and Late (dot-dashed line) Feeding scenarios, respectively.
Mentions: Next, we followed a two-step approach to determine how the distribution of energy densities at den entry, and thus the distribution of litter sizes at den emergence, will be affected if pregnant females are forced ashore early (see Methods for details). First, we determined the distribution of energy densities at on-shore arrival and den entry in a representative sample of adult females without dependent offspring (N=40) caught during the early 1990s. Second, using a dynamic energy budget model283132 to track changes in body mass, storage energy and energy density due to feeding, somatic maintenance and movement, we estimated how energy densities at on-shore arrival and den entry, and thus litter sizes at den emergence, will change with earlier on-shore arrival (see Fig. 2 and Methods). This second step requires on-ice feeding rate estimates to quantify the energetic impacts of a shortened hunting period. However, on-ice feeding rates are unknown for Hudson Bay, and it is also unclear how these rates vary seasonally. We therefore considered two feeding scenarios, 'Early Feeding' and 'Late Feeding', which estimate likely boundaries for the impacts of earlier on-shore arrival (Fig. 2). Early Feeding assumes that bears can only accumulate storage energy until the end of May (that is, during, and shortly after, seal pupping333435) and that feeding during the remaining on-ice period is reduced to rates that are just sufficient for bears to maintain acquired body mass. For earlier on-shore arrival, the Early Feeding scenario probably overestimates litter sizes at den emergence, because it only considers prolonged fasting but not potential losses in feeding. In the Late Feeding scenario, we account for both the prolonged fast and for missed feeding opportunities by assuming high energy intake during June and July, similar to intake rates in the High Arctic35. Bears accumulate much of their storage energy just before on-shore arrival with Late Feeding, so that females forced ashore early not only fast longer before den entry but they also come ashore in poorer body condition. This scenario probably overestimates the energetic impact of earlier on-shore arrival (thus underestimating litter sizes at den emergence), because summer feeding rates in Hudson Bay are likely lower than in the High Arctic (Supplementary Methods).

Bottom Line: In western Hudson Bay, we predict climate warming-induced litter size declines that jeopardize population viability: ∼28% of pregnant females failed to reproduce for energetic reasons during the early 1990s, but 40-73% could fail if spring sea ice break-up occurs 1 month earlier than during the 1990s, and 55-100% if break-up occurs 2 months earlier.Simultaneously, mean litter size would decrease by 22-67% and 44-100%, respectively.Similar litter size declines may occur in over one-third of the global polar bear population.

View Article: PubMed Central - PubMed

Affiliation: Department of Mathematical and Statistical Sciences, University of Alberta, Edmonton, Alberta, Canada T6G 2G1. pmolnar@ualberta.ca

ABSTRACT
Predicting the ecological impacts of climate warming is critical for species conservation. Incorporating future warming into population models, however, is challenging because reproduction and survival cannot be measured for yet unobserved environmental conditions. In this study, we use mechanistic energy budget models and data obtainable under current conditions to predict polar bear litter size under future conditions. In western Hudson Bay, we predict climate warming-induced litter size declines that jeopardize population viability: ∼28% of pregnant females failed to reproduce for energetic reasons during the early 1990s, but 40-73% could fail if spring sea ice break-up occurs 1 month earlier than during the 1990s, and 55-100% if break-up occurs 2 months earlier. Simultaneously, mean litter size would decrease by 22-67% and 44-100%, respectively. The expected timeline for these declines varies with climate-model-specific sea ice predictions. Similar litter size declines may occur in over one-third of the global polar bear population.

Show MeSH
Related in: MedlinePlus