scholarly journals Changes in Biomass Turnover Times in Tropical Forests and Their Environmental Drivers from 2001 to 2012

2020 ◽  
Author(s):  
Jingmeng Wang ◽  
Wei Li ◽  
Philippe Ciais ◽  
Ashley Ballantyne ◽  
Daniel Goll ◽  
...  
2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Subashree Kothandaraman ◽  
Javid Ahmad Dar ◽  
Somaiah Sundarapandian ◽  
Selvadurai Dayanandan ◽  
Mohammed Latif Khan

2018 ◽  
Vol 6 ◽  
pp. 309-316
Author(s):  
Priscilla Sichone ◽  
Vera De Cauwer ◽  
António Valter Chisingui ◽  
Francisco Maiato P. Gonçalves ◽  
Manfred Finckh ◽  
...  

2020 ◽  
Vol 4 (2) ◽  
Author(s):  
Janice S Edgerly ◽  
Brody Sandel ◽  
Isabel Regoli ◽  
Onyekachi Okolo

Abstract String sequence analysis revealed that silk spinning behavior of adult female Embioptera varies from species-specific to individualistic. This analysis included 26 species from ten taxonomic families with a total of 115 individuals. Spin-steps, 28 possible positions of the front feet during spinning, were scored from hour-long DVD recordings produced in the laboratory. Entire transcripts of hundreds to thousands of spin-steps per individual were compared by computing Levenshtein edit distances between all possible pairs of subsequences, with lengths ranging from 5 to 25—intraspecific similarity scores were then computed. Silk gallery characteristics and architecture, body size, climatic variables, and phylogenetic relationships were tested as possible drivers of intraspecific similarity in spinning behavior. Significant differences in intraspecific similarity aligned most strongly with climatic variables such that those species living in regions with high temperature seasonality, low annual precipitation, and high annual temperatures displayed more species-stereotypical spinning sequences than those from other regions, such as tropical forests. Phylogenetic signal was significant but weakly so, suggesting that environmental drivers play a stronger role in shaping the evolution of silk spinning. Body size also appears to play a role in that those of similar size are more like each other, even if not related.


2021 ◽  
Author(s):  
Lore Talle Verryckt ◽  
Sara Vicca ◽  
Leandro Van Langenhove ◽  
Clément Stahl ◽  
Dolores Asensio ◽  
...  

Abstract. Terrestrial biosphere models typically use the biochemical model of Farquhar, von Caemmerer and Berry (1980) to simulate photosynthesis, which requires accurate values of photosynthetic capacity of different biomes. However, data on tropical forests are sparse and highly variable due to the high species diversity, and it is still highly uncertain how these tropical forests respond to nutrient limitation in terms of C uptake. Tropical forests often grow on phosphorus (P)-poor soils and are, in general, assumed to be P- rather than nitrogen (N)-limited. However, the relevance of P as a control of photosynthetic capacity is still debated. Here, we provide a comprehensive dataset of vertical profiles of photosynthetic capacity and important leaf traits, including leaf N and P concentrations, from two three-year, large-scale nutrient addition experiments conducted in two tropical rainforests in French Guiana. These data present a unique source of information to further improve model representations of the roles of N, P, and other leaf nutrients, in photosynthesis in tropical forests. To further facilitate the use of our data in syntheses and model studies, we provide an elaborate list of ancillary data, including important soil properties and nutrients, along with the leaf data. As environmental drivers are key to improve our understanding of carbon (C)-nutrient cycle interactions, this comprehensive dataset will aid to further enhance our understanding of how nutrient availability interacts with C uptake in tropical forests. The data are available at DOI 10.5281/zenodo.4719242 (Verryckt, 2021).


2020 ◽  
Author(s):  
Eliane Gomes-Alves ◽  
Tyeen Taylor ◽  
Pedro Assis ◽  
Giordane Martins ◽  
Rodrigo Souza ◽  
...  

<p>Isoprene regulates large-scale biogeochemical cycles by influencing atmospheric chemical and physical processes, and its dominant sources to the global atmosphere are the tropical forests. Although global and regional model estimates of isoprene emission have been optimized in the last decades, modeled emissions from tropical vegetation still carry high uncertainty due to a poor understanding of the biological and environmental controls on emissions. It is already known that isoprene emission quantities may vary significantly with plant traits, such as leaf phenology, and with the environment; however, current models still lack of good representation for tropical plant species due to the very few observations available. In order to create a predictive framework for the isoprene emission capacity of tropical forests, it is necessary an improved mechanistic understanding on how the magnitude of emissions varies with plant traits and the environment in such ecosystems. In this light, we aimed to quantify the isoprene emission capacity of different tree species across leaf ages, and combine these leaf measurements with long-term canopy measurements of isoprene and its biological and environmental drivers; then, use these results to better parameterize isoprene emissions estimated by MEGAN. We measured at the Amazon Tall Tower Observatory (ATTO) site, central Amazonia: (1) isoprene emission capacity at different leaf ages of 21 trees species; (2) isoprene canopy mixing ratios during six campaigns from 2013 to 2015; (3) isoprene tower flux during the dry season of 2015 (El-Niño year); (3) environmental factors – air temperature and photosynthetic active radiation (PAR) - from 2013 to 2018; and (4) biological factors – leaf demography and phenology (tower based measurements) from 2013 to 2018. We then parameterized the leaf age algorithm of MEGAN with the measurements of isoprene emission capacity at different leaf ages and the tower-based measurements of leaf demography and phenology. Modeling estimates were later compared with measurements (canopy level) and five years of satellite-derived isoprene emission (OMI) from the ATTO domain (2013-2017). Leaf level of isoprene emission capacity showed lower values for old leaves (> 6 months) and young leaves (< 2 months), compared to mature leaves (2-6 months); and our model results suggested that this affects seasonal ecosystem isoprene emission capacity, since the demography of the different leaf age classes varied a long of the year. We will present more results on how changes in leaf demography and phenology and in temperature and PAR affect seasonal ecosystem isoprene emission, and how modeling can be improved with the optimization of the leaf age algorithm. In addition, we will present a comparison of ecosystem isoprene emission of normal years (2013, 2014, 2017 years) and anomalous years (2015 - El-Niño; and 2016 - post El-Niño), and discuss how a strong El-Niño year can influence plant functional strategies that can be carried over to the consecutive year and potentially affect isoprene emission.</p>


2004 ◽  
Vol 359 (1443) ◽  
pp. 437-462 ◽  
Author(s):  
Simon L. Lewis ◽  
Yadvinder Malhi ◽  
Oliver L. Phillips

Recent observations of widespread changes in mature tropical forests such as increasing tree growth, recruitment and mortality rates and increasing above–ground biomass suggest that ‘global change’ agents may be causing predictable changes in tropical forests. However, consensus over both the robustness of these changes and the environmental drivers that may be causing them is yet to emerge. This paper focuses on the second part of this debate. We review (i) the evidence that the physical, chemical and biological environment that tropical trees grow in has been altered over recent decades across large areas of the tropics, and (ii) the theoretical, experimental and observational evidence regarding the most likely effects of each of these changes on tropical forests. Ten potential widespread drivers of environmental change were identified: temperature, precipitation, solar radiation, climatic extremes (including El Niño Southern Oscillation events), atmospheric CO 2 concentrations, nutrient deposition, O 3 /acid depositions, hunting, land–use change and increasing liana numbers. We note that each of these environmental changes is expected to leave a unique ‘fingerprint’ in tropical forests, as drivers directly force different processes, have different distributions in space and time and may affect some forests more than others (e.g. depending on soil fertility). Thus, in the third part of the paper we present testable a priori predictions of forest responses to assist ecologists in attributing particular changes in forests to particular causes across multiple datasets. Finally, we discuss how these drivers may change in the future and the possible consequences for tropical forests.


PLoS ONE ◽  
2018 ◽  
Vol 13 (6) ◽  
pp. e0198489 ◽  
Author(s):  
Emilio Vilanova ◽  
Hirma Ramírez-Angulo ◽  
Armando Torres-Lezama ◽  
Gerardo Aymard ◽  
Luis Gámez ◽  
...  

2019 ◽  
Vol 11 (8) ◽  
pp. 955 ◽  
Author(s):  
Veeranun Songsom ◽  
Werapong Koedsin ◽  
Raymond J. Ritchie ◽  
Alfredo Huete

Vegetation phenology is the annual cycle timing of vegetation growth. Mangrove phenology is a vital component to assess mangrove viability and includes start of season (SOS), end of season (EOS), peak of season (POS), and length of season (LOS). Potential environmental drivers include air temperature (Ta), surface temperature (Ts), sea surface temperature (SST), rainfall, sea surface salinity (SSS), and radiation flux (Ra). The Enhanced vegetation index (EVI) was calculated from Moderate Resolution Imaging Spectroradiometer (MODIS, MOD13Q1) data over five study sites between 2003 and 2012. Four of the mangrove study sites were located on the Malay Peninsula on the Andaman Sea and one site located on the Gulf of Thailand. The goals of this study were to characterize phenology patterns across equatorial Thailand Indo-Malay mangrove forests, identify climatic and aquatic drivers of mangrove seasonality, and compare mangrove phenologies with surrounding upland tropical forests. Our results show the seasonality of mangrove growth was distinctly different from the surrounding land-based tropical forests. The mangrove growth season was approximately 8–9 months duration, starting in April to June, peaking in August to October and ending in January to February of the following year. The 10-year trend analysis revealed significant delaying trends in SOS, POS, and EOS for the Andaman Sea sites but only for EOS at the Gulf of Thailand site. The cumulative rainfall is likely to be the main factor driving later mangrove phenologies.


2022 ◽  
Vol 14 (1) ◽  
pp. 5-18
Author(s):  
Lore T. Verryckt ◽  
Sara Vicca ◽  
Leandro Van Langenhove ◽  
Clément Stahl ◽  
Dolores Asensio ◽  
...  

Abstract. Terrestrial biosphere models typically use the biochemical model of Farquhar, von Caemmerer, and Berry (1980) to simulate photosynthesis, which requires accurate values of photosynthetic capacity of different biomes. However, data on tropical forests are sparse and highly variable due to the high species diversity, and it is still highly uncertain how these tropical forests respond to nutrient limitation in terms of C uptake. Tropical forests often grow on soils low in phosphorus (P) and are, in general, assumed to be P rather than nitrogen (N) limited. However, the relevance of P as a control of photosynthetic capacity is still debated. Here, we provide a comprehensive dataset of vertical profiles of photosynthetic capacity and important leaf traits, including leaf N and P concentrations, from two 3-year, large-scale nutrient addition experiments conducted in two tropical rainforests in French Guiana. These data present a unique source of information to further improve model representations of the roles of N, P, and other leaf nutrients in photosynthesis in tropical forests. To further facilitate the use of our data in syntheses and model studies, we provide an elaborate list of ancillary data, including important soil properties and nutrients, along with the leaf data. As environmental drivers are key to improve our understanding of carbon (C) and nutrient cycle interactions, this comprehensive dataset will aid to further enhance our understanding of how nutrient availability interacts with C uptake in tropical forests. The data are available at https://doi.org/10.5281/zenodo.5638236 (Verryckt, 2021).


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