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Both evolution and ecology have long been concerned with the impact of variable environmental conditions on observed levels of genetic diversity within and between species. We model the evolution of a quantitative trait under selection that…

Populations and Evolution · Quantitative Biology 2014-11-17 Hannes Svardal , Claus Rueffler , Joachim Hermisson

Concerns about biodiversity and the long-term stability of forest ecosystems have lead to changing attitudes with respect to plantations. These artificial communities are ubiquitous, yet provide reduced habitat value in comparison to their…

Populations and Evolution · Quantitative Biology 2009-10-05 Tom Adams , Graeme Ackland , Glenn Marion , Colin Edwards

Estimating phylogenetic trees is an important problem in evolutionary biology, environmental policy and medicine. Although trees are estimated, their uncertainties are discarded by mathematicians working in tree space. Here we explicitly…

Methodology · Statistics 2017-10-16 Amy D. Willis , Rayna C. Bell

The response of ecosystems to perturbations is considered from a thermodynamic perspective by acknowledging that, as for all macroscopic systems and processes, the dynamics and stability of ecosystems is subject to definite thermodynamic…

Biological Physics · Physics 2008-09-26 K. Michaelian , V. Alonso Chavez

Plant-soil feedback is recognized as a causal mechanism for the emergence of vegetation patterns of the same species especially when water is not a limiting resource (e.g. humid environments). Nevertheless, in the field, plants rarely grow…

Populations and Evolution · Quantitative Biology 2026-04-10 Addolorata Marasco , Francesco Giannino , Annalisa Iuorio

Increasing climate change and habitat loss are driving unprecedented shifts in species distributions. Conservation professionals urgently need timely, high-resolution predictions of biodiversity risks, especially in ecologically diverse…

Quantitative Methods · Quantitative Biology 2025-12-03 Hammed A. Akande , Abdulrauf A. Gidado

Previous research has demonstrated that specific states of the climate system can lead to enhanced subseasonal predictability (i.e., state-dependent predictability). However, biases in Earth system models can affect the representation of…

Atmospheric and Oceanic Physics · Physics 2024-09-18 Kirsten J. Mayer , Katherine Dagon , Maria J. Molina

Earth's forests play an important role in the fight against climate change, and are in turn negatively affected by it. Effective monitoring of different tree species is essential to understanding and improving the health and biodiversity of…

Computer Vision and Pattern Recognition · Computer Science 2025-07-30 Venkatesh Ramesh , Arthur Ouaknine , David Rolnick

Plant phenotyping is the assessment of a plant's traits and plant identification is the process of determining the category such as genus and species. In this paper we present an interpretable neural network trained on the UPWINS spectral…

Machine Learning · Computer Science 2024-07-16 William Basener , Abigail Basener , Michael Luegering

Many biological populations exhibit diversity in their strategy for survival and reproduction in a given environment, and microbes are an example. We explore the fate of different strategies under sustained environmental change by…

Populations and Evolution · Quantitative Biology 2025-09-24 Ruixi Huang , David Waxman

Despite the common misconception of nearly static organisms, plants do interact continuously with the environment and with each other. It is fair to assume that during their evolution they developed particular features to overcome problems…

Populations and Evolution · Quantitative Biology 2016-02-19 Gianna Vivaldo , Elisa Masi , Camilla Pandolfi , Stefano Mancuso , Guido Caldarelli

In the present study it is shown that significant impacts on forests can lead to large climate fluctuations at global level. This research takes into account various scenarios for the reconstruction of forest areas using the geo-ecological…

Atmospheric and Oceanic Physics · Physics 2017-09-26 Costas A. Varotsos , Vladimir F. Krapivin

Random Forest (RF) is a well-known data-driven algorithm applied in several fields thanks to its flexibility in modeling the relationship between the response variable and the predictors, also in case of strong non-linearities. In…

Machine Learning · Statistics 2023-10-18 Luca Patelli , Michela Cameletti , Natalia Golini , Rosaria Ignaccolo

We develop a Random Forest model to estimate the species distribution of Asian elephants in India and study the inter and intra-annual spatiotemporal variability of habitats suitable for them. Climatic, topographic variables and…

Machine Learning · Computer Science 2024-04-16 P. Anjali , Deepak N. Subramani

In this paper we consider two continuous-mass population models as analogues of logistic branching random walks, one is supported on a finite trait space and the other one is supported on an infinite trait space. For the first model with…

Probability · Mathematics 2013-04-18 Anton Bovier , Shi-Dong Wang

A central problem in biology is to understand how organisms evolve and adapt to their environment by acquiring variations in the observable characteristics or traits of species across the tree of life. With the growing availability of…

The stability and ability of an ecosystem to withstand climate change is directly linked to its biodiversity. Dead trees are a key indicator of overall forest health, housing one-third of forest ecosystem biodiversity, and constitute 8%of…

Computer Vision and Pattern Recognition · Computer Science 2021-12-07 Jacquelyn A. Shelton , Przemyslaw Polewski , Wei Yao , Marco Heurich

Phytoplankton plays an important role in marine ecosystem. It is defined as a biological factor to assess marine quality. The identification of phytoplankton species has a high potential for monitoring environmental, climate changes and for…

Machine Learning · Statistics 2017-01-24 Thi-Thu-Hong Phan , Emilie Poisson Caillault , André Bigand

Advances in machine learning have boosted the use of Earth observation data for climate change research. Yet, the interpretability of machine-learned representations remains a challenge, particularly in understanding forests' biophysical…

Machine Learning · Computer Science 2024-03-06 Yihang She , Clement Atzberger , Andrew Blake , Srinivasan Keshav

Random forests are a statistical learning method widely used in many areas of scientific research because of its ability to learn complex relationships between input and output variables and also its capacity to handle high-dimensional…

Machine Learning · Statistics 2024-02-19 Louis Capitaine , Jérémie Bigot , Rodolphe Thiébaut , Robin Genuer