Modern soil mapping is characterised by the need to interpolate point referenced (geostatistical) observations and the availability of large numbers of environmental characteristics for consideration as covariates to aid this interpolation. Modelling tasks of this nature also occur in other fields such as biogeography and environmental science. This analysis employs the Least Angle Regression (...

Quantifying the effects of environmental factors over the duration of the growing process on Agaricus Bisporus (button mushroom) yields has been difficult, as common functional data analysis approaches require fixed length functional data. The data available from commercial growers, however, is of variable duration, due to commercial considerations. We employ a recently proposed regression tech...

In many countries, environmental policies and regulations are implemented to improve environmental quality and thus individuals’ well-being. However, how do individuals value the environment? In this paper, we review the life satisfaction approach (LSA), which represents a new nonmarket valuation technique. The LSA builds on the recent development of subjective well-being research in economics ...

Breakwaters are the important and the costly ones of the marine structures. Composite breakwater is one of the common types in the world. Because of the sensitivity of composite breakwaters to environmental conditions, also construction costs, difficulty of repair and maintenance and importance of equipments on and behind the breakwater, design of composite breakwater must be very accurate. Goa...

We present a model for estimating a probabilistic map of ecological habitats using species presence/absence data and environmental covariate data observed at the sites where species presence data were collected. The model is notable because it treats spatially varying patterns of species distributions as the principle defining characteristic of habitats. The model also permits inference about t...

The advancement of predictive models by Machine Learning Algorithms (ML) associated with environmental data enables the improvement fragility, which are essential tools for decision-making. This study aimed to derive a prediction fragility testing ML covariates in state Minas Gerais. We use physical-environmental variables (soil, geology, climate, relief) weight attributes and calculation avera...

Costs associated with reproduction are widely known to play a role in the evolution of reproductive tactics with consequences to population and eco-evolutionary dynamics. Evaluating these costs as they pertain to species in the wild remains an important goal of evolutionary ecology. Individual heterogeneity, including differences in individual quality (i.e., among-individual differences in trai...

The paper uses Italian official survey data collected in 2012 from more than 20 thousand households to shed light on the determinants of people’s pro-environmental behavior, specifically differentiation domestic waste disposal. A rich interdisciplinary literature has developed explain why people may make eco-friendly choices, which come at a personal cost and provide benefits accruing largely o...