Calibrating the data logger…
1. Establishing trade-offs among traits and the degree to which they co-vary along environmental gradients has become a key focal point in the effort to develop community ecology into a predictive science. While there is evidence for these relationships across global datasets, they are often too broad in scale, and do not consider the particularities of local to regional species pools. This decreases their usefulness for developing predictive models at scales relevant for conservation and management. 2. We tested for trade-offs between traits and relationships with environmental gradients in trees and shrubs sampled across southern African savannas and explored evidence for acquisitive vs. conservative resource use strategies using a phylogenetically explicit approach. 3. We found a distinct trade-off between two major poles of specialization indicative of acquisitive (high leaf nitrogen concentration (LNC), leaf phosphorus concentration (LPC), leaf N:P, specific leaf area (SLA) and average leaf area (ALA)) and conservative resource use strategies (high leaf carbon to nitrogen ratios (C:N), tensile strength (TS) and leaf dry matter content (LDMC)). Although we found that trait variance and species occurrence were constrained by phylogeny, phylogenetically informed analyses did not contradict non-phylogenetic analyses, strengthening relationships in most cases. 4. The high intra-site trait variability and weak relationships with soils and climate may in part be explained by the high levels of deciduousness and disturbance (i.e. fire and herbivory) inherent in African savannas. 5. Synthesis: The relationships between traits and between traits and environmental gradients were far weaker than, and often contradictory to, broad scale studies that compare these relationships across biomes and growth forms, cautioning against making generalizations about relationships at specific sites based on broad scale analyses.
Knowledge graph centered on Data from: Leaf traits of African woody savanna sp with 13 nodes and 58 connections. Top connected: precipitation, trait variation, soil grain size, community structure, Mantel test (Plantae).
Items connected by shared entities, co-authorship, citations, or semantic similarity.