Stochastic flood and precipitation regimes and the population dynamics of a threatened floodplain plant

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Ecological Applications


Boltonia decurrens is an endangered plant restricted to the Illinois River Valley. Its complex life cycle has evolved in response to the dynamics of the historic flood regime, which has changed dramatically in the last century due to the construction of navigation dams and agricultural levees. To explore the effects of these changes, we developed deterministic and stochastic matrix population models of the demography of Boltonia. We used periodic matrix models to incorporate intra-annual seasonal variation. We estimated parameters as a function of the timing of spring flood recession (early or late) and of growing season precipitation (high or low). Late floods and/or low precipitation reduce population growth (λ). Early floods and high precipitation lead to explosive population growth. Elasticity analysis shows that changes in floods and precipitation alter the life history pathways responsible for population growth, from annual to biennial and eventually clonal pathways. We constructed and analyzed a stochastic model in which flood timing and precipitation vary independently, and we computed the stochastic growth rate (log λs) and the variance growth rate (σ2) as functions of the frequency of late floods and low precipitation. Using historical data on floods and rainfall over the last 100 years, we found that log λs has declined as a result of hydrological changes accompanying the regulation of the river. Stochastic elasticity analysis showed that over that time the contribution of annual life history pathways to log λs has declined as the contributions of biennial and clonal pathways have increased. Over the same time period, σ2 has increased, in agreement with observations of large fluctuations in local B. decurrens populations. Undoubtedly, many plant and animal species evolved in concert with dynamic habitats and are now threatened by anthropogenic changes in those dynamics. The data and analyses used in this study can be applied to management and development strategies to preserve other dynamic systems.



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