In this paper, we present a new approach to address this question, using the smoothing function, a method not previously recruited into this ecological context.

Kernel smoothing in environmental space gives insight into species distributions. Smoothing outperforms random forest for predictive modeling in simulation ...

Abstract. How the observed occurrences of a species relate to environmental gradients is a fundamental question in community ecology.

Nov 15, 2021 · This paper is about gaining a deeper understanding of the fundamental question of the relationship between the recorded occurrences of a ...

Using simulation techniques, we explore its accuracy in recovering known species distributions from simulated noisy data, and we compare the smoothing ...

Smoothing and the Environmental Manifold ; Type. Journal article ; Journal. Ecological Informatics ; Publisher. Elsevier ; Publication Date. 26/10/2021 ...

Smoothing and the environmental manifold. S Unnithan Kumar, PK Maini, L Chiaverini, AJ Hearn, DW Macdonald, ... Ecological Informatics 66, 101472, 2021. 8, 2021.

Dec 7, 2023 · We present Local Manifold distance (LMdist), an unsupervised algorithm which adjusts pairwise beta diversity measures to better represent true ecological ...

This suggests the promising role that such smoothing functions can have in ecological analyses. Our results also support the robustness of random forest machine ...

set of all smooth vector fields on a smooth manifold M, X(M), with the Lie ... Environment. Wiley-Blackwell, Germany. [9] Bézier, P. (1986). The ...