Contextualizing the ecology of plant–plant interactions and constructive networks

Abstract

Botanical concepts have traditionally viewed the environment as a static box containing plants. In this box, plants compete with one another and act as passive resource consumers subjected to the environment in a top-down manner. This entails that plants have only negative effects on other plants and have no influence on the environment. By contrast, there is increasing evidence that plants have positive, bottom-up engineering effects and diversity effects on other plants and on the environment. Here, to overcome limitations of top-down environmental control, antagonistic-only, and pairwise interactions, I propose the concept of constructive networks. Constructive networks unify niche construction and network theory recognizing that (i) plants have manifold ecological functions and impacts on their neighbors, and (ii) the environment shapes and is shaped by diverse organisms, primarily plants. Constructive networks integrate both plant–environment and plant–plant interactions in a relational context. It is addressed how plants influence the environment and support or inhibit other plant species by physically, biochemically, and ecologically shaping environmental conditions. Constructive networks acknowledge the fact that diverse plants change and create novel environmental conditions as well as co-produce, share, and transform resources, thereby influencing biological communities and the environment in constructive ways. Different interaction types are considered simultaneously in constructive networks. Yet, the understanding of constructive networks is mainly limited by identifying plant links. This barrier may be overcame by applying complexity theory and statistical mechanics to comparative data and experimental field botany. Considering multiple interaction types and feedbacks between plants and the environment may improve our understanding of mechanisms responsible for biodiversity maintenance and help us to better anticipate the response of plant systems to global change.

Impact of Spruce Plantation on Plant Diversity

“…The goal of fitting a regression model is to estimate the model parameters β 0 and β 1 given the data x and y. [45] Plant diversity (i.e., number of plant species) has a Poisson probability distribution and our independent variable, which is the habitat type, is a categorical variable. As a consequence, we have decided to analyze plant diversity using a Generalized Linear Model (GLM) that allows us to overcome the issues of non-Normal probability distributions and of non linear independent variables.…”

“…Given x and y this model allows us to estimate the β 0 , β 1 , β 2 (the effect of the second explanatory variable x 2 ) and β 3 (the effect of the interaction of the two explanatory variables) [45].…”