Pine trees structure plant biodiversity patterns in savannas.

Overstory trees serve multiple functions in grassy savannas. Past research has shown that understory species can vary along gradients of canopy cover and basal area in savannas. This variation is frequently associated with light availability but could also be related to other mechanisms, such as heterogeneity in soil and litter depth and fire intensity.

Climate change projection using statistical downscaling model over southern coastal Iran.

Iran is highly vulnerable to climate change, particularly evident in shifting precipitation and temperature patterns, especially in its southern coastal region. With these changing climate conditions, there is an urgent need for practical and adaptive management of water resources and energy supply to address the challenges posed by future climate change. Over the next two to three decades, the effects of climate change, such as precipitation and temperature, are expected to worsen, posing greater risks to water resources, agriculture, and infrastructure stability.

Understanding the temporal dynamics of estimated environmental niche hypervolumes for marine fishes.

Understanding how species respond to the environment is essential in ecology, evolution, and conservation. Abiotic factors can influence species responses and the multi-dimensional space of abiotic factors that allows a species to grow represents the environmental niche. While niches are often assumed to be constant and robust, they are most likely changing over time and estimation can be influenced by population biology, sampling intensity, and computation methodology.

Identification of Thresholds on Population Density for Understanding Transmission of COVID-19.

Pathways of transmission of coronavirus (COVID-19) disease in the human population are still emerging. However, empirical observations suggest that dense human settlements are the most adversely impacted, corroborating a broad consensus that human-to-human transmission is a key mechanism for the rapid spread of this disease. Here, using logistic regression techniques, estimates of threshold levels of population density were computed corresponding to the incidence (case counts) in the human population.

"Ecology of fear" in ungulates: Opportunities for improving conservation.

Because ungulates are important contributors to ecosystem function, understanding the "ecology of fear" could be important to the conservation of ecosystems. Although studying ungulate ecology of fear is common, knowledge from ungulate systems is highly contested among ecologists. Here, we review the available literature on the ecology of fear in ungulates to generalize our current knowledge and how we can leverage it for conservation.

Automated audio recording as a means of surveying tinamous (Tinamidae) in the Peruvian Amazon.

The use of machine learning technologies to process large quantities of remotely collected audio data is a powerful emerging research tool in ecology and conservation.We applied these methods to a field study of tinamou (Tinamidae) biology in Madre de Dios, Peru, a region expected to have high levels of interspecies competition and niche partitioning as a result of high tinamou alpha diversity. We used autonomous recording units to gather environmental audio over a period of several months at lowland rainforest sites in the Los Amigos Conservation Concession and developed a Convolutional Neural Network-based data processing pipeline to detect tinamou vocalizations in the dataset.

The Latent Dirichlet Allocation model with covariates (LDAcov): A case study on the effect of fire on species composition in Amazonian forests.

Understanding and predicting the effect of global change phenomena on biodiversity is challenging given that biodiversity data are highly multivariate, containing information from tens to hundreds of species in any given location and time. The Latent Dirichlet Allocation (LDA) model has been recently proposed to decompose biodiversity data into latent communities. While LDA is a very useful exploratory tool and overcomes several limitations of earlier methods, it has limited inferential and predictive skill given that covariates cannot be included in the model.