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Matteo Detto

Researcher at Princeton University

Publications -  110
Citations -  5817

Matteo Detto is an academic researcher from Princeton University. The author has contributed to research in topics: Eddy covariance & Environmental science. The author has an hindex of 37, co-authored 98 publications receiving 4442 citations. Previous affiliations of Matteo Detto include Smithsonian Tropical Research Institute & Smithsonian Institution.

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CTFS-ForestGEO: A worldwide network monitoring forests in an era of global change

Kristina J. Anderson-Teixeira, +119 more
TL;DR: The broad suite of measurements made at CTFS-ForestGEO sites makes it possible to investigate the complex ways in which global change is impacting forest dynamics, and continued monitoring will provide vital contributions to understanding worldwide forest diversity and dynamics in an era of global change.
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Soil moisture and vegetation controls on evapotranspiration in a heterogeneous Mediterranean ecosystem on Sardinia, Italy

TL;DR: In this article, a two-source random model (2SR) was proposed for estimating evapotranspiration in heterogeneous ecosystems as the residual term of the energy balance using Ts observations and Quickbird images.
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Consequences of defaunation for a tropical tree community

TL;DR: Using tree census data from a large-scale plot monitored over a 15-year period since the approximate onset of intense hunting, a comprehensive assessment of the immediate consequences of defaunation for a tropical tree community suggests that over-hunting has engendered pervasive changes in tree population spatial structure and dynamics, leading to a consistent decline in local tree diversity over time.
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Evaluating uncertainty in mapping forest carbon with airborne LiDAR

TL;DR: In this paper, the authors used a 50-ha plot with mapped trees, allowing an assessment of LiDAR prediction errors at multiple spatial resolutions, and they found that errors scaled approximately as expected, declining by 38% (compared to 40% predicted from theory) from 0.36-to 1-ha resolution.
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Tree carbon allocation explains forest drought-kill and recovery patterns.

TL;DR: In this paper, a combination of meta-analysis and tree physiological models demonstrate that optimal carbon allocation after drought explains observed patterns of delayed tree mortality and provides a predictive recovery framework, indicating that tree resilience to drought-kill may increase in the future, provided that CO2 fertilisation facilitates more rapid xylem regrowth.