Predicting the Viability of Fish Populations in a Modified Riverine Environment

Riverine fishes evolved to life in a highly variable, flow-driven environment. During the two past centuries, large rivers have been substantially altered by human activities. This has resulted in declines of fish populations that depend on the large river environment. The research described here uses models to evaluate the effects of human activities on the viability of fish populations in rivers. I focused on five modifications of the river environment associated with impoundment: (1) seasonal allocation of river flow; (2) diversion of river flow; (3) fragmentation of the river habitat by dams; (4) conversion of free-flowing river to reservoir habitat; and (5) alteration of migration patterns. To understand the role of flow regulation on chinook salmon (Oncorhynchus tshawytscha) recruitment, I developed an individual-based model to predict recruitment as a function of seasonal flow patterns in the Tuolumne River, California. I used simulated annealing to find flow patterns that maximize chinook recruitment under wet and dry hydrologic conditions. As water availability increased, I found that the optimal flow pattern shifted from allocating low flows uniformly across seasons to a pattern with high spring flows. When I considered a new objective: maximizing the variance of spawning times among recruits, the optimal flow regime called for a winter pulse in flow just before the peak spawning date for the minority (late-fall) run. To evaluate the recovery options for chinook salmon in the Tuolumne River, Ideveloped an age-based model to conduct a population viability analysis (PVA). I developed a flow-dependent spawner-recruitment relationship from the recruitment model. Its shape depended on the flow regime, suggesting that such relationships are not fixed properties of species, but depend on environmental conditions. The PVA model suggested that recovery, in the absence of straying, would be enhanced most by significantly reducing ocean harvest, followed by reduced diversion of water from the river. For white sturgeon (Acipenser transmontanus) populations in the Snake River, Idaho a main concern is habitat fragmentation by dams resulting in smaller, isolated populations. Simulation experiments to evaluate the effects of fragmentation suggested that population viability was higher when dams were spaced widely enough apart to retain free-flowing habitat. A simulation experiment to evaluate the effects of altered migration patterns associated with impoundment showed that both the likelihood of persistence and the genetic diversity among white sturgeon populations were enhanced by balanced upstream and downstream migration rates. Models that simulate the responses of fish populations to modified river habitat do not consider the potential for an evolutionary response. I designed a PVA model simulating the genetic basis of age at maturity for individual fish. Simulated individual variation in this trait lead to increased population viability only when the variation was heritable and subjected to an altered selective regime. The results support the idea that predicting population viability depends on estimating the potential for evolution in fitness-related traits for populations exposed to anthropogenic changes in the environment that impose strong, directional selective forces

Using capture-recapture data and hybrid Monte Carlo sampling to estimate an animal population affected by an environmental catastrophe

We propose a dynamic model for the evolution of an open animal population that is subject to an environmental catastrophe. The model incorporates a capture-recapture experiment often conducted for studying wildlife population, and enables inferences on the population size and possible effect of the catastrophe. A Bayesian approach is used to model unobserved quantities in the problem as latent variables and Markov chain Monte Carlo (MCMC) is used for posterior computation. Because the particular interrelationship between observed and latent variables negates the feasibility of standard MCMC methods, we propose a hybrid Monte Carlo approach that integrates a Gibbs sampler with the strategies of sequential importance sampling (SIS) and acceptance-rejection (AR) sampling for model estimation. We develop results on how to construct effective proposal densities for the SIS scheme. The approach is illustrated through a simulation study, and is applied to data from a mountain pygmy possum (Burramys Parvus) population that was affected by a bushfire.Acceptance-rejection sampling Capture recapture Gibbs sampler Population size Sequential importance sampling

Improved Understanding and Characterisation of Climate Hazards in the UK

This chapter describes new methods and datasets, developed through UK Climate Resilience Programme (UKCR) projects, to better understand climate hazards.We describe projections of hazards using new tools and provide examples of applications for decision-making.Going forward, this new physical and statistical understanding should be incorporated into climate risk assessments

Background Examples of Literature Searches on Topics of Interest

A zip file of various literature searches & some resources related to our work related to exposure after the Chernobyl accident and as we began looking at helping in Semey Kazakhstan----a collection of literature reviews on various topics we were interested in... eg. establishing a registry of those exposed for longterm follow-up, what we knew about certain areas like genetics and some resources like A Guide to Environmental Resources on the Internet by Carol Briggs-Erickson and Toni Murphy which could be found on the Internet and was written to be used by researchers, environmentalists, teachers and any person who is interested in knowing and doing something about the health of our planet. See more at https://archives.library.tmc.edu/dm-ms211-012-0060

Remote Sensing and Geosciences for Archaeology

This book collects more than 20 papers, written by renowned experts and scientists from across the globe, that showcase the state-of-the-art and forefront research in archaeological remote sensing and the use of geoscientific techniques to investigate archaeological records and cultural heritage. Very high resolution satellite images from optical and radar space-borne sensors, airborne multi-spectral images, ground penetrating radar, terrestrial laser scanning, 3D modelling, Geographyc Information Systems (GIS) are among the techniques used in the archaeological studies published in this book. The reader can learn how to use these instruments and sensors, also in combination, to investigate cultural landscapes, discover new sites, reconstruct paleo-landscapes, augment the knowledge of monuments, and assess the condition of heritage at risk. Case studies scattered across Europe, Asia and America are presented: from the World UNESCO World Heritage Site of Lines and Geoglyphs of Nasca and Palpa to heritage under threat in the Middle East and North Africa, from coastal heritage in the intertidal flats of the German North Sea to Early and Neolithic settlements in Thessaly. Beginners will learn robust research methodologies and take inspiration; mature scholars will for sure derive inputs for new research and applications