Plant-plant interactions scale up to produce vegetation spatial patterns: the influence of long- and short-term process

Community plant height modulated by aridity promotes spatial vegetation patterns in Alxa plateau in Northwest China

Spatial vegetation patterns are associated with ecosystem stability and multifunctionality in drylands. Changes in patch size distributions (PSDs) are generally driven by both environmental and biological factors. However, the relationships between these factors in driving PSDs are not fully understood. We investigated 80 vegetation plots along an aridity gradient in the Alxa plateau, Northwest China. The sizes of vegetation patches were obtained from aerial images, and the heights of patch-forming species were measured in the field. Soil samples were collected on the bare ground between patches for determination of physiochemical properties. Point pattern analysis was used to infer plant-plant interactions. A model selection procedure was employed to select the best predictors for the shape of PSDs and biological factors (vegetation total cover, community plant height, and plant-plant interactions). We then used structural equation modeling to evaluate the direct and indirect effects of environmental and biological factors on the shape of PSDs. In our study area, two types of PSDs coexisted, namely those that best fit to power law distributions and those that best fit to lognormal distributions. Aridity was the main environmental factor, while community mean height and competition between plants were the main biological factors for the shape of PSDs. As aridity and community mean height increased, power law-like PSDs were exhibited, whereas competition led to deviations of PSDs from power laws. Aridity affected the shape of PSDs indirectly through changes in community mean height. Community mean height was correlated with competition, thereby indirectly affecting the shape of PSDs. Our results suggest the use of community functional traits as a link between the environment and plant-plant interactions, which may improve the understanding of the underlying mechanisms of PSD dynamics.

Variations in Leaf Traits Modulate Plant Vegetative and Reproductive Phenological Sequencing Across Arid Mediterranean Shrublands

Structural and nutrient traits of a leaf are important for understanding plant ecological strategies (e.g., drought avoidance). We studied the specific leaf area (SLA), leaf carbon content (LCC), leaf nitrogen content (LNC), leaf phosphorous content (LPC), and the phenophase sequence index (PSI) in 126 Mediterranean perennial species from predesert (SMS) and semiarid (SaMS) to subalpine (SAS), alpine cushion (AcS), and oro-Mediterranean (AjS) shrublands, which represent eight functional groups (evergreen and deciduous trees, evergreen large and half shrubs, deciduous large and half shrubs, succulents and perennial herbs). We analyzed the variation and relationships between leaf traits and PSI among shrublands, functional groups, and within species with drought-avoidance mechanisms. SLA variation of 20-60% could be ascribed to differences between functional groups and only 38-48% to different shrublands increasing from the predesert to the alpine. Alpine species display low PSI and N:P and high SLA, LNC, LPC, LCC, and C:N. On the contrary, predesert and semiarid showed high PSI and low SLA. SLA mediates the vegetative and reproductive phenological plant sequencing, high SLA is often associated with the overlapping in growth and reproductive phenophases with a seasonal reduction of vegetative growth, whereas low SLA is associated with vegetative and reproductive sequencing and a seasonal extension of vegetative growth. Species with drought-avoidance mechanisms (e.g., semideciduous species) contribute to an increase in the mean values of the SLA and LNC because these species show similar leaf and phenological patterns as the deciduous (high SLA and LNC and low PSI). The N:P indicates that only the alpine shrublands could present P limitations. The positive correlations between SLA and LPC and LNC and LPC (leaf economic spectrum) and the negative correlation between SLA and C:N were consistently maintained in the studied arid Mediterranean shrublands.

Integration of remote sensing in spatial ecology: assessing the interspecific interactions of two plant species in a semi-arid woodland using unmanned aerial vehicle (UAV) photogrammetric data

The spatial structure of plant communities in semi-arid regions is mostly derived by plant-plant interactions and environmental heterogeneity. In this study, we investigated the intra- and interspecific interactions and their contribution to growth inhibition in the patches of Pistacia trees and Amygdalus shrubs in semi-arid woodland communities through the implementation of photogrammetric data provided by unmanned aerial vehicle (UAV). This study was conducted in a part of Wild Pistachio Natural Reserve covered by Pistacia-Amygdalus stands in Zagros Mountains, western Iran. We used univariate and bivariate forms of pair- and mark correlation functions and Analytical Global Envelopes under inhomogeneous Poisson process which allow detection of the interactions of the species within the 45-ha study area. Our results indicated that the UAV-derived photogrammetric data proved to be efficient in identification of the plant individuals (F-score ≈ 0.92 for both species). Additionally, strong coefficients of determination (R² = 0.98 and 0.94 for Pistacia and Amygdalus, respectively) supported prediction of crown area. We observed the aggregation of the species individuals in clusters of conspecifics and heterospecifics at small spatial scales, most likely as a result of aggregation in favourable parts of the study area. The aggregation of the species within patches had a marked effect on their size (i.e., crown area, height) inferred as growth inhibition, probably due to intra- and interspecific competition. Our findings demonstrated that promising UAV photogrammetric data can be effectively utilized by ecologists for investigation of plant associations, hence increasing the potentiality of remote sensing in spatial ecology of vegetation patches in semi-arid environments.