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We mapped native, endemic, and introduced (i.e., exotic) tree species counts, relative basal areas of functional groups, species basal areas, and forest biomass from forest inventory data, satellite imagery, and environmental data for Puerto Rico and the Virgin Islands. Imagery included time series of Landsat composites and Moderate Resolution Imaging Spectroradiometer (MODIS)-based phenology. Environmental data included climate, land-cover, geology, topography, and road distances. Large-scale deforestation and subsequent forest regrowth are clear in the resulting maps decades after large-scale transition back to forest. Stand age, climate, geology, topography, road/urban locations, and protection are clearly influential. Unprotected forests on more accessible or arable lands are younger and have more introduced species and deciduous and nitrogen-fixing basal areas, fewer endemic species, and less biomass. Exotic species are widespread—except in the oldest, most remote forests on the least arable lands, where shade-tolerant exotics may persist. Although the maps have large uncertainty, their patterns of biomass, tree species diversity, and functional traits suggest that for a given geoclimate, forest age is a core proxy for forest biomass, species counts, nitrogen-fixing status, and leaf longevity. Geoclimate indicates hard-leaved species commonness. Until global wall-to-wall remote sensing data from specialized sensors are available, maps from multispectral image time series and other predictor data should help with running ecosystem models and as sustainable development indicators. Forest attribute models trained with a tree species ordination and mapped with nearest neighbor substitution (Phenological Gradient Nearest Neighbor method, PGNN) yielded larger correlation coefficients for observed vs. mapped tree species basal areas than Cubist regression tree models trained separately on each species. In contrast, Cubist regression tree models of forest structural and functional attributes yielded larger such correlation coefficients than the ordination-trained PGNN models.

Studies of leaf traits often focus on tradeoffs between growth and resource conservation, but little is known about variation in the mechanical traits that influence resource conservation. This study investigates how leaf mechanical traits vary across matorral vegetation in central Chile, how they correlate with environmental factors, and how these trends compare at a broader geographic scale. Leaf toughness, strength, stiffness, and associated traits were measured in five matorral types in central Chile, and relationships with soil N and P and climate variables were assessed. Trends with soil and climate were then analyzed across shrubland and woodland in Chile, Western Australia, and New Caledonia. Chilean species varied in leaf mechanics and associated traits, both within and among matorral types, with more species in sclerophyll matorral having strong, tough, and stiff leaves than in arid and littoral matorral. Overall, leaves with high leaf dry mass per area were stiffer, tougher, stronger, thicker, denser, with more fiber, lignin, phenolics and fiber per unit protein and less protein: tannin activity and N and P per mass, forming a broad sclerophylly syndrome. Mechanical traits of matorral species were not correlated with soil N or P, or predictably with climate variables, except flexural stiffness ( EIW) which correlated positively with annual reference evapotranspiration ( ET0). However, soil P made strong independent contributions to variation in leaf mechanics across shrublands and woodlands of Chile, Western Australia, and New Caledonia, either separately (strength) or together with ET0 (toughness) explaining 46-90% of variation. Hence ET0 was predictive of EIW in Chilean matorral, whereas soil P was highly predictive of variation in leaf strength, and combined with ET0 was highly predictive of toughness, at a broader geographic scale. The biological basis of these relationships, however, may be complex. [ABSTRACT FROM AUTHOR]

The defining characteristics of scierophylly are mechanical (e.g., hardness, toughness, stiffness), but little is known about how they vary in contrasting environments and contribute to the adaptiveness of sclerophylly. Here we investigate how the degree and nature of sclerophylly in terms of leaf mechanics differ between vegetation of two contrasting stressful environments, maquis on nutrient-deficient, moist sites and dry forest on moderate-nutrient, drier sites. We measured toughness, strength, and stiffness at the level of the whole leaf ("structural") and per unit thickness ("material"). Leaves of maquis plants were on average structurally stiffer, stronger, and tougher than those in dry forest. There was little difference in material properties between habitats, and leaf thickness was the main contributor to differences in structural mechanical properties between habitats. Flexural stiffness varied most among species and habitats, correlating strongly with leaf mass per area and thickness. We suggest that having thicker leaves allows efficient packaging of biomass to reduce branching costs in sunny but stressful environments, with subsequent impacts on structural mechanical properties. Scierophylly is probably a complex phenomenon, however, with its mechanical constitution arising from both evolved mechanical properties that confer protection or resistance to stress and nonadaptive mechanical consequences of adaptation to stressful environments. [ABSTRACT FROM AUTHOR]

Fundamental plant traits such as support, anchorage, and protection against environmental stress depend substantially on biomechanical design. The costs, subsequent trade-offs, and effects on plant performance of mechanical traits are not well understood, but it appears that many of these traits have evolved in response to abiotic and biotic mechanical forces and resource deficits. The relationships between environmental stresses and mechanical traits can be specific and direct, as in responses to strong winds, with structural reinforcement related to plant survival. Some traits such as leaf toughness might provide protection from multiple forms of stress. In both cases, the adaptive value of mechanical traits may vary between habitats, so is best considered in the context of the broader growth environment, not just of the proximate stress. Plants can also show considerable phenotypic plasticity in mechanical traits, allowing adjustment to changing environments across a range of spatial and temporal scales. However, it is not always clear whether a mechanical property is adaptive or a consequence of the physiology associated with stress. Mechanical traits do not only affect plant survival; evidence suggests they have downstream effects on ecosystem organization and functioning (e.g., diversity, trophic relationships, and productivity), but these remain poorly explored. [ABSTRACT FROM AUTHOR]

Although sclerophylly is widespread through the world and is often the dominant leaf-form in mediterranean climates, the mechanical properties of sclerophyllous leaves are poorly understood. The term ”sclerophyllous” means hard-leaved, but biologists also use terms such as tough, stiff and leathery to describe sclerophyllous leaves. The latter term has no precise definition that allows quantification. However, each of the former terms is well-defined in materials engineering, although they may be difficult or sometimes inappropriate to measure in leaves because of their size, shape or composite and anisotropic nature. Two of the most appropriate and practically applicable mechanical properties of sclerophyllous leaves are ”strength” and ”toughness”, which in this study were applied using punching, tearing and shearing tests to 19 species of tree and shrub at Wilson’s Promontory, Australia. The results of these tests were compared with leaf specific mass (LSM) and a sclerophylly index derived from botanists’ ranks. Principal components analysis was used to reduce the set of mechanical properties to major axes of variation. Component 1 correlated strongly with the botanists’ ranks. Overall, leaves ranked as sclerophyllous by botanists were both tough and strong in terms of punching and tearing tests. In addition, tough and strong leaves typically had high toughness and strength per unit leaf thickness. There was also a significant correlation between component 1 and LSM. Although more detailed surveys are required, we argue that sclerophylly should be defined in terms of properties that have precise meanings and are measurable, such as toughness and strength, and that relate directly to mechanical properties as implicit in the term. [ABSTRACT FROM AUTHOR]

We mapped native, endemic, and introduced (i.e., exotic) tree species counts, relative basal areas of functional groups, species basal areas, and forest biomass from forest inventory data, satellite imagery, and environmental data for Puerto Rico and the Virgin Islands. Imagery included time series of Landsat composites and Moderate Resolution Imaging Spectroradiometer (MODIS)-based phenology. Environmental data included climate, land-cover, geology, topography, and road distances. Large-scale deforestation and subsequent forest regrowth are clear in the resulting maps decades after large-scale transition back to forest. Stand age, climate, geology, topography, road/urban locations, and protection are clearly influential. Unprotected forests on more accessible or arable lands are younger and have more introduced species and deciduous and nitrogen-fixing basal areas, fewer endemic species, and less biomass. Exotic species are widespread—except in the oldest, most remote forests on the least arable lands, where shade-tolerant exotics may persist. Although the maps have large uncertainty, their patterns of biomass, tree species diversity, and functional traits suggest that for a given geoclimate, forest age is a core proxy for forest biomass, species counts, nitrogen-fixing status, and leaf longevity. Geoclimate indicates hard-leaved species commonness. Until global wall-to-wall remote sensing data from specialized sensors are available, maps from multispectral image time series and other predictor data should help with running ecosystem models and as sustainable development indicators. Forest attribute models trained with a tree species ordination and mapped with nearest neighbor substitution (Phenological Gradient Nearest Neighbor method, PGNN) yielded larger correlation coefficients for observed vs. mapped tree species basal areas than Cubist regression tree models trained separately on each species. In contrast, Cubist regression tree models of forest structural and functional attributes yielded larger such correlation coefficients than the ordination-trained PGNN models. [ABSTRACT FROM AUTHOR]