ORCID Profile
0000-0002-3526-9021
Current Organisation
Smithsonian Institution
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Publisher: Wiley
Date: 07-2008
DOI: 10.1890/07-0207.1
Abstract: A central goal of comparative plant ecology is to understand how functional traits vary among species and to what extent this variation has adaptive value. Here we evaluate relationships between four functional traits (seed volume, specific leaf area, wood density, and adult stature) and two demographic attributes (diameter growth and tree mortality) for large trees of 240 tree species from five Neotropical forests. We evaluate how these key functional traits are related to survival and growth and whether similar relationships between traits and demography hold across different tropical forests. There was a tendency for a trade-off between growth and survival across rain forest tree species. Wood density, seed volume, and adult stature were significant predictors of growth and/or mortality. Both growth and mortality rates declined with an increase in wood density. This is consistent with greater construction costs and greater resistance to stem damage for denser wood. Growth and mortality rates also declined as seed volume increased. This is consistent with an adaptive syndrome in which species tolerant of low resource availability (in this case shade-tolerant species) have large seeds to establish successfully and low inherent growth and mortality rates. Growth increased and mortality decreased with an increase in adult stature, because taller species have a greater access to light and longer life spans. Specific leaf area was, surprisingly, only modestly informative for the performance of large trees and had ambiguous relationships with growth and survival. Single traits accounted for 9-55% of the interspecific variation in growth and mortality rates at in idual sites. Significant correlations with demographic rates tended to be similar across forests and for phylogenetically independent contrasts as well as for cross-species analyses that treated each species as an independent observation. In combination, the morphological traits explained 41% of the variation in growth rate and 54% of the variation in mortality rate, with wood density being the best predictor of growth and mortality. Relationships between functional traits and demographic rates were statistically similar across a wide range of Neotropical forests. The consistency of these results strongly suggests that tropical rain forest species face similar trade-offs in different sites and converge on similar sets of solutions.
Publisher: Oxford University Press (OUP)
Date: 04-04-2006
DOI: 10.1093/AOB/MCL066
Publisher: Elsevier BV
Date: 2021
Publisher: Wiley
Date: 05-2007
Publisher: Cambridge University Press
Date: 08-09-2005
Publisher: MDPI AG
Date: 28-06-2019
DOI: 10.3390/RS11131534
Abstract: Tropical forests exhibit complex but poorly understood patterns of leaf phenology. Understanding species- and in idual-level phenological patterns in tropical forests requires datasets covering large numbers of trees, which can be provided by Unmanned Aerial Vehicles (UAVs). In this paper, we test a workflow combining high-resolution RGB images (7 cm ixel) acquired from UAVs with a machine learning algorithm to monitor tree and species leaf phenology in a tropical forest in Panama. We acquired images for 34 flight dates over a 12-month period. Crown boundaries were digitized in images and linked with forest inventory data to identify species. We evaluated predictions of leaf cover from different models that included up to 14 image features extracted for each crown on each date. The models were trained and tested with visual estimates of leaf cover from 2422 images from 85 crowns belonging to eight species spanning a range of phenological patterns. The best-performing model included both standard color metrics, as well as texture metrics that quantify within-crown variation, with r2 of 0.84 and mean absolute error (MAE) of 7.8% in 10-fold cross-validation. In contrast, the model based only on the widely-used Green Chromatic Coordinate (GCC) index performed relatively poorly (r2 = 0.52, MAE = 13.6%). These results highlight the utility of texture features for image analysis of tropical forest canopies, where illumination changes may diminish the utility of color indices, such as GCC. The algorithm successfully predicted both in idual-tree and species patterns, with mean r2 of 0.82 and 0.89 and mean MAE of 8.1% and 6.0% for in idual- and species-level analyses, respectively. Our study is the first to develop and test methods for landscape-scale UAV monitoring of in idual trees and species in erse tropical forests. Our analyses revealed undescribed patterns of high intraspecific variation and complex leaf cover changes for some species.
Publisher: Wiley
Date: 24-10-2017
DOI: 10.1111/GCB.13910
Abstract: Numerous current efforts seek to improve the representation of ecosystem ecology and vegetation demographic processes within Earth System Models (ESMs). These developments are widely viewed as an important step in developing greater realism in predictions of future ecosystem states and fluxes. Increased realism, however, leads to increased model complexity, with new features raising a suite of ecological questions that require empirical constraints. Here, we review the developments that permit the representation of plant demographics in ESMs, and identify issues raised by these developments that highlight important gaps in ecological understanding. These issues inevitably translate into uncertainty in model projections but also allow models to be applied to new processes and questions concerning the dynamics of real-world ecosystems. We argue that stronger and more innovative connections to data, across the range of scales considered, are required to address these gaps in understanding. The development of first-generation land surface models as a unifying framework for ecophysiological understanding stimulated much research into plant physiological traits and gas exchange. Constraining predictions at ecologically relevant spatial and temporal scales will require a similar investment of effort and intensified inter-disciplinary communication.
Publisher: Wiley
Date: 24-02-2022
DOI: 10.1111/NPH.17995
Abstract: Tree size shapes forest carbon dynamics and determines how trees interact with their environment, including a changing climate. Here, we conduct the first global analysis of among-site differences in how aboveground biomass stocks and fluxes are distributed with tree size. We analyzed repeat tree censuses from 25 large-scale (4-52 ha) forest plots spanning a broad climatic range over five continents to characterize how aboveground biomass, woody productivity, and woody mortality vary with tree diameter. We examined how the median, dispersion, and skewness of these size-related distributions vary with mean annual temperature and precipitation. In warmer forests, aboveground biomass, woody productivity, and woody mortality were more broadly distributed with respect to tree size. In warmer and wetter forests, aboveground biomass and woody productivity were more right skewed, with a long tail towards large trees. Small trees (1-10 cm diameter) contributed more to productivity and mortality than to biomass, highlighting the importance of including these trees in analyses of forest dynamics. Our findings provide an improved characterization of climate-driven forest differences in the size structure of aboveground biomass and dynamics of that biomass, as well as refined benchmarks for capturing climate influences in vegetation demographic models.
Location: United States of America
No related grants have been discovered for Helene C. Muller-Landau.