Climate related uncertainties associated with the future conditions for the migratory monarch butterfly (Danaus plexippus)
Abstract
There are large uncertainties in the future climate predictions from global climate models. Predictions vary based on the model types and greenhouse gases concentrations. Climate model simulated environmental variables, such as precipitation and temperatures are widely used in driving ecological models for understanding the future distributions of biodiversity. These models have their own associated uncertainties and combining uncertainties between the environmental and biodiversity models are critical to evaluate how well we are able to forecast possible future ecological changes. Here we address this issue using the eastern US migratory monarch butterfly that famously migrates to Mexico each year as an example.
Monarchs migrate through Texas each spring, and they stop there to breed in March and April before the next generation continues North. Research has determined that temperature and precipitation during this phase of migration is the primary determinant of population size each year. Using Daymet and CPC datasets, ECMWF reanalysis, and 16 IPCC atmosphere-ocean general circulation model output, we propose model selection criteria to deploy the most relevant climate models for understanding future abundance predictions and associated uncertainties. We found that under the most extreme emission scenarios, future springs in Texas are much warmer and slightly drier, but there is substantial uncertainty in the predictions. Further, including those temperatures in models of monarch population dynamics results in substantial associated uncertainties. However, based on known thresholds of physiological tolerance to heat, future climate will become much more severe for monarchs, with up to 24 lethal days even during the spring breeding period. This research suggests that future climate may become more stressful and could interact with other threats, such as habitat loss and disease.- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2018
- Bibcode:
- 2018AGUFM.B41N2923N
- Keywords:
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- 0414 Biogeochemical cycles;
- processes;
- and modeling;
- BIOGEOSCIENCESDE: 0439 Ecosystems;
- structure and dynamics;
- BIOGEOSCIENCESDE: 0466 Modeling;
- BIOGEOSCIENCESDE: 1910 Data assimilation;
- integration and fusion;
- INFORMATICS