Advances in Ecological Research, Volume 74 brings together cutting-edge developments, current trends, and emerging concepts in the field of ecology. The book provides an in-depth exploration of fundamental and applied ecological research, offering insights into the complex interactions between organisms and their environments. Specific chapters cover how Conformal Prediction quantifies the uncertainty of Species Distribution Models, How do Earth Observation Foundation Models Help to Predict Multi-Trophic Soil Biodiversity, Evaluating Multi-Sensor Foundation Models as a Strategy for Leveraging Earth Observation Data in Biodiversity Modeling, Exploring Remote Sensing Contributions to High-Resolution IAS Distribution Modeling Using ML/DL Techniques, and much more.
Additional sections cover Predicting Ecological Invasions, The carrying capacity of a fragmented landscape depends on the home-range size of a species, Quantitative tools that form an approach that allows social impacts of ecosystem change, Extending genomic prediction from individuals to a population and community, and Full prediction uncertainty quantification: a plea from science and decision-making.
1. Title of Book - p. i 2. Cover image - p. i 3. Title page - p. ii 4. Table of Contents - p. iii 5. Series Page - p. iii 6. Copyright - p. iv 7. Contributors - p. ix 8. Chapter One: Conformal prediction quantifies the uncertainty of species distribution models - p. 1 9. Chapter Two: Limits and promises of earth observation foundation models in predicting multi-trophic soil biodiversity - p. 31 10. Chapter Three: Predictive ecology for invasive species risk assessment: A narrative review and a case study - p. 65 11. Chapter Four: The carrying capacity of a fragmented landscape depends on the home-range size of a species - p. 95 12. Chapter Five: Quantifying the impact of social and ecosystem changes through expanded ecosystem multifunctionality metrics - p. 123 13. Chapter Six: Extending genomic prediction from individuals to a population and community - p. 153 14. Chapter Seven: Full prediction uncertainty quantification: A plea from science and decision making - p. 191
Advances in Ecological Research, Volume 74 brings together cutting-edge developments, current trends, and emerging concepts in the field of ecology. The book provides an in-depth exploration of fundamental and applied ecological research, offering insights into the complex interactions between organisms and their environments. Specific chapters cover how Conformal Prediction quantifies the uncertainty of Species Distribution Models, How do Earth Observation Foundation Models Help to Predict Multi-Trophic Soil Biodiversity, Evaluating Multi-Sensor Foundation Models as a Strategy for Leveraging Earth Observation Data in Biodiversity Modeling, Exploring Remote Sensing Contributions to High-Resolution IAS Distribution Modeling Using ML/DL Techniques, and much more.
Additional sections cover Predicting Ecological Invasions, The carrying capacity of a fragmented landscape depends on the home-range size of a species, Quantitative tools that form an approach that allows social impacts of ecosystem change, Extending genomic prediction from individuals to a population and community, and Full prediction uncertainty quantification: a plea from science and decision-making.
1. Title of Book - p. i 2. Cover image - p. i 3. Title page - p. ii 4. Table of Contents - p. iii 5. Series Page - p. iii 6. Copyright - p. iv 7. Contributors - p. ix 8. Chapter One: Conformal prediction quantifies the uncertainty of species distribution models - p. 1 9. Chapter Two: Limits and promises of earth observation foundation models in predicting multi-trophic soil biodiversity - p. 31 10. Chapter Three: Predictive ecology for invasive species risk assessment: A narrative review and a case study - p. 65 11. Chapter Four: The carrying capacity of a fragmented landscape depends on the home-range size of a species - p. 95 12. Chapter Five: Quantifying the impact of social and ecosystem changes through expanded ecosystem multifunctionality metrics - p. 123 13. Chapter Six: Extending genomic prediction from individuals to a population and community - p. 153 14. Chapter Seven: Full prediction uncertainty quantification: A plea from science and decision making - p. 191
