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A Bayesian approach for temporally scaling climate for modeling ecological systems.

Post van der Burg M, Anteau MJ, McCauley LA, Wiltermuth MT - Ecol Evol (2016)

Bottom Line: Our results showed that wetland water surface areas tended to be larger in wetter conditions, but also changed less in response to climate fluctuations in the contemporary era.We also found that the average timescale parameter was greater in the historical period, compared with the contemporary period.Our results suggest that perhaps some interaction between climate and hydrologic response may be at work, and further analysis is needed to determine which has a stronger influence.

View Article: PubMed Central - PubMed

Affiliation: U.S. Geological Survey Northern Prairie Wildlife Research Center 8711 37th Street Jamestown North Dakota 58401.

ABSTRACT
With climate change becoming more of concern, many ecologists are including climate variables in their system and statistical models. The Standardized Precipitation Evapotranspiration Index (SPEI) is a drought index that has potential advantages in modeling ecological response variables, including a flexible computation of the index over different timescales. However, little development has been made in terms of the choice of timescale for SPEI. We developed a Bayesian modeling approach for estimating the timescale for SPEI and demonstrated its use in modeling wetland hydrologic dynamics in two different eras (i.e., historical [pre-1970] and contemporary [post-2003]). Our goal was to determine whether differences in climate between the two eras could explain changes in the amount of water in wetlands. Our results showed that wetland water surface areas tended to be larger in wetter conditions, but also changed less in response to climate fluctuations in the contemporary era. We also found that the average timescale parameter was greater in the historical period, compared with the contemporary period. We were not able to determine whether this shift in timescale was due to a change in the timing of wet-dry periods or whether it was due to changes in the way wetlands responded to climate. Our results suggest that perhaps some interaction between climate and hydrologic response may be at work, and further analysis is needed to determine which has a stronger influence. Despite this, we suggest that our modeling approach enabled us to estimate the relevant timescale for SPEI and make inferences from those estimates. Likewise, our approach provides a mechanism for using prior information with future data to assess whether these patterns may continue over time. We suggest that ecologists consider using temporally scalable climate indices in conjunction with Bayesian analysis for assessing the role of climate in ecological systems.

No MeSH data available.


Related in: MedlinePlus

Summary of weather information for a set of sample wetlands in North Dakota. These summaries were generated from interpolated temperature and precipitation values from the Parameter‐elevation Regressions on Independent Slopes Model (PRISM). The top panel shows total annual precipitation in millimeters, while the bottom panel shows the annual mean of average monthly high temperature (red line) and average monthly low temperature (green line). Monthly values of these three measurements were used in calculating potential evapotranspiration.
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ece32092-fig-0001: Summary of weather information for a set of sample wetlands in North Dakota. These summaries were generated from interpolated temperature and precipitation values from the Parameter‐elevation Regressions on Independent Slopes Model (PRISM). The top panel shows total annual precipitation in millimeters, while the bottom panel shows the annual mean of average monthly high temperature (red line) and average monthly low temperature (green line). Monthly values of these three measurements were used in calculating potential evapotranspiration.

Mentions: The wetlands we analyzed in our study showed a general trend toward being less full in the historical era (mean = 0.34 ha, SD =  0.27) compared with the contemporary era (mean = 0.59 ha, SD = 0.27). Annual summaries of the temperature information used in computing our monthly climate indices did show a slight increasing average annual trend for both minimum temperature and for precipitation (Fig. 1). The parameter estimates from our model suggested that era and SPEI were useful variables in predicting the proportion of a basin's area that was covered with water, whereas SPI had a very weak and uncertain relationship with our response variable (Table 1). All further summaries and predictions were made assuming that SPI was held at its mean value. The mean estimate of the model's marginal predictive performance was Rmarginal2 = 0.16. The model's conditional predictive performance showed some improvement (Rconditional2 = 0.61), which indicates additional sources of variation in the observed pattern for our response variable.


A Bayesian approach for temporally scaling climate for modeling ecological systems.

Post van der Burg M, Anteau MJ, McCauley LA, Wiltermuth MT - Ecol Evol (2016)

Summary of weather information for a set of sample wetlands in North Dakota. These summaries were generated from interpolated temperature and precipitation values from the Parameter‐elevation Regressions on Independent Slopes Model (PRISM). The top panel shows total annual precipitation in millimeters, while the bottom panel shows the annual mean of average monthly high temperature (red line) and average monthly low temperature (green line). Monthly values of these three measurements were used in calculating potential evapotranspiration.
© Copyright Policy - creativeCommonsBy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4863021&req=5

ece32092-fig-0001: Summary of weather information for a set of sample wetlands in North Dakota. These summaries were generated from interpolated temperature and precipitation values from the Parameter‐elevation Regressions on Independent Slopes Model (PRISM). The top panel shows total annual precipitation in millimeters, while the bottom panel shows the annual mean of average monthly high temperature (red line) and average monthly low temperature (green line). Monthly values of these three measurements were used in calculating potential evapotranspiration.
Mentions: The wetlands we analyzed in our study showed a general trend toward being less full in the historical era (mean = 0.34 ha, SD =  0.27) compared with the contemporary era (mean = 0.59 ha, SD = 0.27). Annual summaries of the temperature information used in computing our monthly climate indices did show a slight increasing average annual trend for both minimum temperature and for precipitation (Fig. 1). The parameter estimates from our model suggested that era and SPEI were useful variables in predicting the proportion of a basin's area that was covered with water, whereas SPI had a very weak and uncertain relationship with our response variable (Table 1). All further summaries and predictions were made assuming that SPI was held at its mean value. The mean estimate of the model's marginal predictive performance was Rmarginal2 = 0.16. The model's conditional predictive performance showed some improvement (Rconditional2 = 0.61), which indicates additional sources of variation in the observed pattern for our response variable.

Bottom Line: Our results showed that wetland water surface areas tended to be larger in wetter conditions, but also changed less in response to climate fluctuations in the contemporary era.We also found that the average timescale parameter was greater in the historical period, compared with the contemporary period.Our results suggest that perhaps some interaction between climate and hydrologic response may be at work, and further analysis is needed to determine which has a stronger influence.

View Article: PubMed Central - PubMed

Affiliation: U.S. Geological Survey Northern Prairie Wildlife Research Center 8711 37th Street Jamestown North Dakota 58401.

ABSTRACT
With climate change becoming more of concern, many ecologists are including climate variables in their system and statistical models. The Standardized Precipitation Evapotranspiration Index (SPEI) is a drought index that has potential advantages in modeling ecological response variables, including a flexible computation of the index over different timescales. However, little development has been made in terms of the choice of timescale for SPEI. We developed a Bayesian modeling approach for estimating the timescale for SPEI and demonstrated its use in modeling wetland hydrologic dynamics in two different eras (i.e., historical [pre-1970] and contemporary [post-2003]). Our goal was to determine whether differences in climate between the two eras could explain changes in the amount of water in wetlands. Our results showed that wetland water surface areas tended to be larger in wetter conditions, but also changed less in response to climate fluctuations in the contemporary era. We also found that the average timescale parameter was greater in the historical period, compared with the contemporary period. We were not able to determine whether this shift in timescale was due to a change in the timing of wet-dry periods or whether it was due to changes in the way wetlands responded to climate. Our results suggest that perhaps some interaction between climate and hydrologic response may be at work, and further analysis is needed to determine which has a stronger influence. Despite this, we suggest that our modeling approach enabled us to estimate the relevant timescale for SPEI and make inferences from those estimates. Likewise, our approach provides a mechanism for using prior information with future data to assess whether these patterns may continue over time. We suggest that ecologists consider using temporally scalable climate indices in conjunction with Bayesian analysis for assessing the role of climate in ecological systems.

No MeSH data available.


Related in: MedlinePlus