A non-deterministic approach to forecasting the trophic evolution of lakes

Limnologists have long recognized that one of the goals of their discipline is to increase its predictive capability. In recent years, the role of prediction in applied ecology escalated, mainly due to man\u27s increased ability to change the biosphere. Such alterations often came with unplanned and noticeably negative side effects mushrooming from lack of proper attention to long-term consequences. Regression analysis of common limnological parameters has been successfully applied to develop predictive models relating the variability of limnological parameters to specific key causes. These approaches, though, are biased by the requirement of a priori cause-relation assumption, oftentimes difficult to find in the complex, nonlinear relationships entangling ecological data. A set of quantitative tools that can help addressing current environmental challenges avoiding such restrictions is currently being researched and developed within the framework of ecological informatics. One of these approaches attempting to model the relationship between a set of inputs and known outputs, is based on genetic algorithms and programming (GP). This stochastic optimization tool is based on the process of evolution in natural systems and was inspired by a direct analogy to sexual reproduction and Charles Darwin\u27s principle of natural selection. GP works through genetic algorithms that use selection and recombination operators to generate a population of equations. Thanks to a 25-years long time-series of regular limnological data, the deep, large, oligotrophic Lake Maggiore (Northern Italy) is the ideal case study to test the predictive ability of GP. Testing of GP on the multi-year data series of this lake has allowed us to verify the forecasting efficacy of the models emerging from GP application. In addition, this non-deterministic approach leads to the discovery of non-obvious relationships between variables and enabled the formulation of new stochastic models

Stochastic Community Assembly: Does It Matter in Microbial Ecology?

Understanding the mechanisms controlling community diversity, functions, succession, and biogeography is a central, but poorly understood, topic in ecology, particularly in microbial ecology. Although stochastic processes are believed to play nonnegligible roles in shaping community structure, their importance relative to deterministic processes is hotly debated. The importance of ecological stochasticity in shaping microbial community structure is far less appreciated. Some of the main reasons for such heavy debates are the difficulty in defining stochasticity and the diverse methods used for delineating stochasticity. Here, we provide a critical review and synthesis of data from the most recent studies on stochastic community assembly in microbial ecology. We then describe both stochastic and deterministic components embedded in various ecological processes, including selection, dispersal, diversification, and drift. We also describe different approaches for inferring stochasticity from observational diversity patterns and highlight experimental approaches for delineating ecological stochasticity in microbial communities. In addition, we highlight research challenges, gaps, and future directions for microbial community assembly research

Agricultural Research Service Weed Science Research: Past, Present, and Future

The U.S. Department of Agriculture-Agricultural Research Service (USDA-ARS) has been a leader in weed science research covering topics ranging from the development and use of integrated weed management (IWM) tactics to basic mechanistic studies, including biotic resistance of desirable plant communities and herbicide resistance. ARS weed scientists have worked in agricultural and natural ecosystems, including agronomic and horticultural crops, pastures, forests, wild lands, aquatic habitats, wetlands, and riparian areas. Through strong partnerships with academia, state agencies, private industry, and numerous federal programs, ARS weed scientists have made contributions to discoveries in the newest fields of robotics and genetics, as well as the traditional and fundamental subjects of weed-crop competition and physiology and integration of weed control tactics and practices. Weed science at ARS is often overshadowed by other research topics; thus, few are aware of the long history of ARS weed science and its important contributions. This review is the result of a symposium held at the Weed Science Society of America\u27s 62nd Annual Meeting in 2022 that included 10 separate presentations in a virtual Weed Science Webinar Series. The overarching themes of management tactics (IWM, biological control, and automation), basic mechanisms (competition, invasive plant genetics, and herbicide resistance), and ecosystem impacts (invasive plant spread, climate change, conservation, and restoration) represent core ARS weed science research that is dynamic and efficacious and has been a significant component of the agency\u27s national and international efforts. This review highlights current studies and future directions that exemplify the science and collaborative relationships both within and outside ARS. Given the constraints of weeds and invasive plants on all aspects of food, feed, and fiber systems, there is an acknowledged need to face new challenges, including agriculture and natural resources sustainability, economic resilience and reliability, and societal health and well-being

Addressing drivers of dieback in an endangered shrub species, Persoonia hirsuta

Persoonia hirsuta Pers. (Proteaceae) is an Endangered shrub species endemic to the Sydney Basin region of New South Wales. This species has been in significant decline over the past two decades and is presently threatened by urban development, limited seedling recruitment, and observed dieback (a condition in which a plant begins to die from the tips of its leaves or backwards often owing to disease or an unfavourable environment) of a presently unknown cause. Understanding what causes dieback and limits new seedling recruitment is critical for the successful conservation and management of this species. The overarching goal of this research is to address key biological knowledge gaps associated with this species biology and explore potential drivers of dieback with an aim to improve the conservation and management of this species. My thesis has identified that soil pathogens, fire severity and climate change and/or environmental extremes may be involved in driving dieback and decline for P. hirsuta. However, further research is necessary to explore the intricacies of how these factors are involved in driving dieback. Additionally, these threats necessitate further conservation actions and improved management recommendations for this species. Therefore, the information in this PhD thesis has been prepared to serve in part of a NSW Threatened Species Scientific Committee Conservation Assessment as the combined results from this thesis, and other work suggest this species is eligible to be up listed to Critically Endangered. The increased understanding of ecological processes affecting dieback and decline gained from this thesis will inform future research activities and conservation recommendations for this species through improved delivery of adaptive management strategies such as translocations. Additionally, the novel strategies employed throughout thesis may improve future research associated with addressing possible drivers of dieback in native ecosystems

V Jornadas de Investigación de la Facultad de Ciencia y Tecnología. 2016

171 p.I. Abstracts. Ahozko komunikazioak / Comunicaciones orales: 1. Biozientziak: Alderdi Molekularrak / Biociencias: Aspectos moleculares. 2. Biozientziak: Ingurune Alderdiak / Biociencias: Aspectos Ambientales. 3. Fisika eta Ingenieritza Elektronika / Física e Ingeniería Electrónica. 4. Geología / Geología. 5. Matematika / Matemáticas. 6. Kimika / Química. 7. Ingenieritza Kimikoa eta Kimika / Ingeniería Química y Química. II. Abstracts. Idatzizko Komunikazioak (Posterrak) / Comunicaciones escritas (Pósters): 1. Biozientziak / Biociencias. 2. Fisika eta Ingenieritza Elektronika / Física e Ingeniería Electrónica. 3. Geologia / Geologia. 4. Matematika / Matemáticas. 5. Kimika / Química. 6. Ingenieritza Kimikoa / Ingeniería Química