The influence of hydrological dynamics on vegetational biodiversity and structuring of wetland en... more The influence of hydrological dynamics on vegetational biodiversity and structuring of wetland environments is of growing interest as wetlands are modified by human alteration and the increasing threat from climate change. Hydrology has long been considered a driving force in shaping wetland communities as the frequency of inundation along with the duration and depth of flooding are key determinants of
The simplest theories often have much merit and many limitations, and in this vein, the value of ... more The simplest theories often have much merit and many limitations, and in this vein, the value of Neutral Theory (NT) has been the subject of much debate over the past 15 years. NT was proposed at the turn of the century by Stephen Hubbell to explain pervasive patterns observed in the organization of ecosystems. Its originally tepid reception among ecologists contrasted starkly with the excitement it caused among physicists and mathematicians. Indeed, NT spawned several theoretical studies that attempted to explain empirical data and predicted trends of quantities that had not yet been studied. While there are a few reviews of NT oriented towards ecologists, our goal here is to review the quantitative results of NT and its extensions for physicists who are interested in learning what NT is, what its successes are and what important problems remain unresolved. Furthermore, we hope that this review could also be of interest to theoretical ecologists because many potentially interesting...
ABSTRACT Many models that are devised to capture the stochastic fluctuation of streamflow timeser... more ABSTRACT Many models that are devised to capture the stochastic fluctuation of streamflow timeseries usually derive the stochasticity directly from the streamflow itself without connection to the stochasticity of rainfall. On the other hand, most of those that are devised to link rainfall to streamflow, e.g., traditional rainfall-runoff models, do so through a case-by-case type of representation with a large number of parameters and the corresponding calibration. In this work, we propose an analytical model to describe the probabilistic structure of streamflow timeseries with an explicit link to rainfall stochasticity at a daily timescale. Under this framework, streamflow is modeled as a series of overlapping gamma-shaped pulses, whose arrival follows a Poisson process and whose volume is exponentially distributed. The arrival rate and volume distribution of the streamflow pulses are explicitly linked to those of rainfall. A number of important probabilistic properties are obtained, including autocorrelation function and approximate probability density functions under various conditions. The model thus offers a tool to directly translate changes in precipitation patterns predicted under the climate change to changes in streamflow patterns and subsequently ecosystem functions and services that depend on them. The model also provides a useful framework to infer the shape of the watershed response from the streamflow autocorrelation function. We demonstrate some of these utilities here.
Forests are globally important ecosystems host to outstanding biological diversity. Widespread ef... more Forests are globally important ecosystems host to outstanding biological diversity. Widespread efforts have addressed the impacts of climate change on biodiversity in these ecosystems. We show that a metacommunity model founded on basic ecological processes offers direct linkage from large-scale forcing, such as precipitation, to tree diversity patterns of the Mississippi-Missouri River System and its subregions. We quantify changes in
In this paper, we develop a simple analysis method to infer some properties of the watershed proc... more In this paper, we develop a simple analysis method to infer some properties of the watershed processes from daily streamflow data. The method is built on a simple streamflow model with a link to rainfall stochasticity, which characterizes the streamflow as a series of overlapping gamma distribution-shaped pulses. The key premise of the method is that the complex streamflow processes
We apply an evolutionary game theoretic approach to the evolution of dispersal in explicitly spat... more We apply an evolutionary game theoretic approach to the evolution of dispersal in explicitly spatial metacommunities, using a flexible parametric class of dispersal kernels, namely 2Dt kernels, and study the resulting evolutionary dynamics and outcomes. We observe strong selective pressure on mean dispersal distance (i.e., the first moment), and weaker, but significant, one on the shape of dispersal kernel (i.e., higher moments). We investigate the effects of landscape topology and spatial heterogeneity on the resulting "optimal" dispersal kernels. The shape--importantly the tail structure--and stability of evolutionarily optimal dispersal strategies are strongly affected by landscape topology. Specifically, the results suggest that the optimal dispersal kernels in the river network topology have heavier tails and are stable, while those in the direct topology, where organisms are allowed to travel directly from one location to another, have relatively thin tails and may b...
The influence of hydrological dynamics on vegetational biodiversity and structuring of wetland en... more The influence of hydrological dynamics on vegetational biodiversity and structuring of wetland environments is of growing interest as wetlands are modified by human alteration and the increasing threat from climate change. Hydrology has long been considered a driving force in shaping wetland communities as the frequency of inundation along with the duration and depth of flooding are key determinants of
The simplest theories often have much merit and many limitations, and in this vein, the value of ... more The simplest theories often have much merit and many limitations, and in this vein, the value of Neutral Theory (NT) has been the subject of much debate over the past 15 years. NT was proposed at the turn of the century by Stephen Hubbell to explain pervasive patterns observed in the organization of ecosystems. Its originally tepid reception among ecologists contrasted starkly with the excitement it caused among physicists and mathematicians. Indeed, NT spawned several theoretical studies that attempted to explain empirical data and predicted trends of quantities that had not yet been studied. While there are a few reviews of NT oriented towards ecologists, our goal here is to review the quantitative results of NT and its extensions for physicists who are interested in learning what NT is, what its successes are and what important problems remain unresolved. Furthermore, we hope that this review could also be of interest to theoretical ecologists because many potentially interesting...
ABSTRACT Many models that are devised to capture the stochastic fluctuation of streamflow timeser... more ABSTRACT Many models that are devised to capture the stochastic fluctuation of streamflow timeseries usually derive the stochasticity directly from the streamflow itself without connection to the stochasticity of rainfall. On the other hand, most of those that are devised to link rainfall to streamflow, e.g., traditional rainfall-runoff models, do so through a case-by-case type of representation with a large number of parameters and the corresponding calibration. In this work, we propose an analytical model to describe the probabilistic structure of streamflow timeseries with an explicit link to rainfall stochasticity at a daily timescale. Under this framework, streamflow is modeled as a series of overlapping gamma-shaped pulses, whose arrival follows a Poisson process and whose volume is exponentially distributed. The arrival rate and volume distribution of the streamflow pulses are explicitly linked to those of rainfall. A number of important probabilistic properties are obtained, including autocorrelation function and approximate probability density functions under various conditions. The model thus offers a tool to directly translate changes in precipitation patterns predicted under the climate change to changes in streamflow patterns and subsequently ecosystem functions and services that depend on them. The model also provides a useful framework to infer the shape of the watershed response from the streamflow autocorrelation function. We demonstrate some of these utilities here.
Forests are globally important ecosystems host to outstanding biological diversity. Widespread ef... more Forests are globally important ecosystems host to outstanding biological diversity. Widespread efforts have addressed the impacts of climate change on biodiversity in these ecosystems. We show that a metacommunity model founded on basic ecological processes offers direct linkage from large-scale forcing, such as precipitation, to tree diversity patterns of the Mississippi-Missouri River System and its subregions. We quantify changes in
In this paper, we develop a simple analysis method to infer some properties of the watershed proc... more In this paper, we develop a simple analysis method to infer some properties of the watershed processes from daily streamflow data. The method is built on a simple streamflow model with a link to rainfall stochasticity, which characterizes the streamflow as a series of overlapping gamma distribution-shaped pulses. The key premise of the method is that the complex streamflow processes
We apply an evolutionary game theoretic approach to the evolution of dispersal in explicitly spat... more We apply an evolutionary game theoretic approach to the evolution of dispersal in explicitly spatial metacommunities, using a flexible parametric class of dispersal kernels, namely 2Dt kernels, and study the resulting evolutionary dynamics and outcomes. We observe strong selective pressure on mean dispersal distance (i.e., the first moment), and weaker, but significant, one on the shape of dispersal kernel (i.e., higher moments). We investigate the effects of landscape topology and spatial heterogeneity on the resulting "optimal" dispersal kernels. The shape--importantly the tail structure--and stability of evolutionarily optimal dispersal strategies are strongly affected by landscape topology. Specifically, the results suggest that the optimal dispersal kernels in the river network topology have heavier tails and are stable, while those in the direct topology, where organisms are allowed to travel directly from one location to another, have relatively thin tails and may b...
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Papers by Sandro Azaele