Browsing by Author "Meir, Patrick"

Tree mortality rates appear to be increasing in moist tropical forests (MTFs) with significant carbon cycle consequences. Here, we review the state of knowledge regarding MTF tree mortality, create a conceptual framework with testable hypotheses regarding the drivers, mechanisms and interactions that may underlie increasing MTF mortality rates, and identify the next steps for improved understanding and reduced prediction. Increasing mortality rates are associated with rising temperature and vapor pressure deficit, liana abundance, drought, wind events, fire and, possibly, CO2 fertilization-induced increases in stand thinning or acceleration of trees reaching larger, more vulnerable heights. The majority of these mortality drivers may kill trees in part through carbon starvation and hydraulic failure. The relative importance of each driver is unknown. High species diversity may buffer MTFs against large-scale mortality events, but recent and expected trends in mortality drivers give reason for concern regarding increasing mortality within MTFs. Models of tropical tree mortality are advancing the representation of hydraulics, carbon and demography, but require more empirical knowledge regarding the most common drivers and their subsequent mechanisms. We outline critical datasets and model developments required to test hypotheses regarding the underlying causes of increasing MTF mortality rates, and improve prediction of future mortality under climate change.

In the next few decades, climate of the Amazon basin is expected to change, as a result of deforestation and rising temperatures, which may lead to feedback mechanisms in carbon (C) cycling that are presently unknown. Here, we report how a throughfall exclusion (TFE) experiment affected soil carbon dioxide (CO2) production in a deeply weathered sandy Oxisol of Caxiuanã (Eastern Amazon). Over the course of 2 years, we measured soil CO2 efflux and soil CO2 concentrations, soil temperature and moisture in pits down to 3 m depth. Over a period of 2 years, TFE reduced on average soil CO2 efflux from 4.3±0.1 μmol CO2 m−2 s−1 (control) to 3.2±0.1 μmol CO2 m−2 s−1 (TFE). The contribution of the subsoil (below 0.5 m depth) to the total soil CO2 production was higher in the TFE plot (28%) compared with the control plot (17%), and it did not differ between years. We distinguished three phases of drying after the TFE was started. The first phase was characterized by a translocation of water uptake (and accompanying root activity) to deeper layers and not enough water stress to affect microbial activity and/or total root respiration. During the second phase a reduction in total soil CO2 efflux in the TFE plot was related to a reduction of soil and litter decomposers activity. The third phase of drying, characterized by a continuing decrease in soil CO2 production was dominated by a water stress-induced decrease in total root respiration. Our results contrast to results of a drought experiment on clay Oxisols, which may be related to differences in soil water retention characteristics and depth of rooting zone. These results show that large differences exist in drought sensitivity among Amazonian forest ecosystems, which primarily seem to be affected by the combined effects of texture (affecting water holding capacity) and depth of rooting zone.

Our ability to understand and predict the response of ecosystems to a changing environment depends on quantifying vegetation functional diversity. However, representing this diversity at the global scale is challenging. Typically, in Earth system models, characterization of plant diversity has been limited to grouping related species into plant functional types (PFTs), with all trait variation in a PFT collapsed into a single mean value that is applied globally. Using the largest global plant trait database and state of the art Bayesian modeling, we created fine-grained global maps of plant trait distributions that can be applied to Earth system models. Focusing on a set of plant traits closely coupled to photosynthesis and foliar respiration-specific leaf area (SLA) and dry mass-based concentrations of leaf nitrogen ([Formula: see text]) and phosphorus ([Formula: see text]), we characterize how traits vary within and among over 50,000 [Formula: see text]-km cells across the entire vegetated land surface. We do this in several ways-without defining the PFT of each grid cell and using 4 or 14 PFTs; each model's predictions are evaluated against out-of-sample data. This endeavor advances prior trait mapping by generating global maps that preserve variability across scales by using modern Bayesian spatial statistical modeling in combination with a database over three times larger than that in previous analyses. Our maps reveal that the most diverse grid cells possess trait variability close to the range of global PFT means.