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Intro -- Contents -- Prologue -- Structure and purposes of this book -- Chapter 1. Tropical Asia as a special case: the physical environment -- 1. History and geology -- 1.1. History over geological time: the interplay of tectonic masses -- 1.2. Surface geology and geomorphology: table tablelands set among a buckled and crushed jumble -- 1.3. Among epicontinental seas -- 2. Climate -- 2.1. What are the tropics? -- 2.2. Mapping the Asian climate -- 2.3. The climate in tropical Asia -- 2.4. A day in the tropics: the diurnal march of the weather -- 3. The history of climate change and stability -- 3.1. Early history -- 3.2 The Pleistocene -- 4. Tropical forest soils -- 4.1. Soils typology and classification -- 4.2. Soils reflect landscape dynamics -- 4.3. Soil distribution in tropical Asia -- 5. Tropical Asia: lands of forests and deserts -- 5.1. Ever-changing landscapes -- 5.2. Dense with the successors of ancient civilizations -- 5.3. The landscapes of Asia and its forests constitute a palimpsest -- References -- Chapter 2. Lowland forest form and function: reconciling light and drought -- Part I. Lowland forests in an aseasonal climate -- 1. Is the mature rain forest vertically stratified? -- 1.1. Stratification by maximum tree height -- 1.2. Stratification by branch architecture -- 1.3. Stratification through gross crown architecture and presentation of flowers -- 1.4. Leaf layers as a source of stratification -- Box 2.1 Palms -- 2. The lowland rain forest cycle: the life of a stand -- 2.1. The regeneration niche: pioneer (and climax) species -- 2.2. The gap phase and succession -- 2.3. The ever-changing canopy -- 2.4. Mortality -- 2.5. Primary productivity -- 3. Structural and physiognomic variation within perhumid landscapes and regions -- 3.1. The lowland mixed dipterocarp forests -- 3.2. Kerangas and peat swamp forest.

The Pasoh Forest Reserve in Malaysia is one of the most species-rich ecological systems on our planet. Since the 1970s it has been the site of intensive research on lowland tropical rain forest across a diverse range of disciplines including ecology, forestry, meteorology, and hydrology. Research has focused on biodiversity and sustainable management of tropical rain forests as well as the role of tropical rain forests in maintaining global climate and carbon sinks. This book compiles diverse studies of the ecology and natural history of the Pasoh Forest Reserve and focuses on six areas: Physical settings and environment; Vegetation structure, diversity, and dynamics; Plant population and functional biology; Animal ecology and biodiversity; Plant-animal interactions; and Anthropogenic impacts and forest management. This book is of interest to tropical forest researchers worldwide in ecology, conservation biology, taxonomy, and forestry

Copyright © 2020 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. The sensitivity of tropical forest carbon to climate is a key uncertainty in predicting global climate change. Although short-term drying and warming are known to affect forests, it is unknown if such effects translate into long-term responses. Here, we analyze 590 permanent plots measured across the tropics to derive the equilibrium climate controls on forest carbon. Maximum temperature is the most important predictor of aboveground biomass (-9.1 megagrams of carbon per hectare per degree Celsius), primarily by reducing woody productivity, and has a greater impact per °C in the hottest forests (>32.2°C). Our results nevertheless reveal greater thermal resilience than observations of short-term variation imply. To realize the long-term climate adaptation potential of tropical forests requires both protecting them and stabilizing Earth's climate.

This paper is a product of the T-FORCES forest monitoring network (Tropical Forests in the Changing Earth System), supported by an ERC Advanced Grant to O.L.P. and by many institutions, NGOs, government agencies and local communities in Malaysia, Brunei, and Indonesia. We are grateful for historical plot data contributed by the Center for Tropical Forest Science (CTFS; two LAM plots and one BEL plot), the Global Ecosystem Monitoring network (GEM; two LAM plots), Institute for Biodiversity and Environmental Research, Universiti Brunei Darussalam (Brunei plots), Kagoshima University (KIS and KIU plots), Forest Department Sarawak (BKO, LAM, MER and GMU plots), Forest Research Centre, Sabah Forestry Department (SEP plots), the Tropenbos Kalimantan project (ITCI plots), Project Barito Ulu, supported by Indonesian Institute of Sciences (LIPI) (BUL plots), and the STREK project, supported by CIRAD, The Ministry of Forestry of Indonesia, and INHUTANI I (STR plots). We are indebted to a great many individuals who contributed to historical data collection. Contemporary fieldwork was supported by a grant from the ERC (T-FORCES) and from NERC (grants NER/A/S/2000/00532, NE/B503384/1, NE/N012542/1). L.Q. was supported by T-FORCES, CIFOR and NERC NE/P00363X/1. S.L.L. was supported by a Royal Society University Research Fellowship, T-FORCES and a Phillip Leverhulme Prize. O.L.P. is supported by T-FORCES and a Royal Society Wolfson Research Merit Award. M.J.P.S. is supported by T-FORCES and NERC NE/N012542/1. L.F.B. was supported by a NERC studentship to the University of Leeds and a RGS-IBG Henrietta Hutton grant. R.H. was supported by a University of Brunei Darussalam Research Fellowship (2011) and a long-term research project RVO 67985939 from the Czech Academy of Sciences. S.L. received additional support from Primate Conservation Inc. M.S. was supported by a Ministry of Education, Youth and Sports grant of the Czech Republic INGO II LG15051. R.R.E.V. was supported by the Netherlands Foundation for the Advancement of Tropical Research (WOTRO, grant No. W76-217). We thank Forest Department Sarawak, Sabah Biodiversity Centre, Sabah Forestry Department, Forest Department Brunei, Institute for Biodiversity and Environmental Research, University of Brunei Darussalam and Indonesia Ministry of Research, Technology, and Higher Education for research permissions. We thank Bako National Park, Lambir Hills National Park, Gunung Mulu National Park, Kuala Belalong Field Study Centre (KBFSC), Glen Reynolds (SEARRP), Danum Valley Conservation Area, Rainforest Discovery Centre Sepilok, Sepilok Laut Reception Centre, Borneo Orangutan Survival Foundation (BOSF), Sungai Wain Protection Forest Management Unit, WWF East Kalimantan and PT. ITCIKU East Kalimantan for logistical support for fieldwork. We thank Timothy Baker, Roel Brienen, Emanuel Gloor, Adriane Esquivel Muelbert and Nicolas Labrière for comments on the manuscript. We thank our deceased colleagues, John Proctor and Suriantata, for their invaluable contributions to both historical work and our wider understanding of tropical forest ecology. ; Peer reviewed ; Publisher PDF

Funding Information: The CMB-S4 collaboration ( https://cmb-s4.org/ ) is working to plan, construct, and operate a next-generation, multisite CMB experiment in the 2020s. The collaboration is led by an elected Governing Board, Spokespeople, Committee Chairs, and Executive Team. Funding for the CMB-S4 Integrated Project Office is provided by the Department of Energy's Office of Science (project level CD-0) and by the National Science Foundation through the Mid-Scale Research Infrastructure-R1 award OPP-1935892. This research used resources of Argonne National Laboratory, a U.S. Department of Energy (DOE) Office of Science User Facility operated under Contract No. DE-AC02-06CH11357. This document was prepared by the CMB-S4 collaboration using the resources of the Fermi National Accelerator Laboratory (Fermilab), a U.S. Department of Energy, Office of Science, HEP User Facility. Fermilab is managed by Fermi Research Alliance, LLC (FRA), acting under Contract No. DE-AC02-07CH11359. Work at Lawrence Berkeley National Laboratory was supported by the Office of Science, Office of Basic Energy Sciences, of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231. Work at SLAC National Accelerator Laboratory is supported by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences under Contract No. DE-AC02-76SF00515. This research used resources of the National Energy Research Scientific Computing Center, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231. In the United States, work on CMB-S4 by individual investigators has been supported by the National Science Foundation (awards 1248097, 1255358, 1815887, 1835865, 1852617, 2009469), the Department of Energy (awards DE-SC0009919, DE-SC0009946, DE-SC0010129, DE-SC0011784), and the National Aeronautics and Space Administration (award ATP-80NSSC20K0518). In Australia, the Melbourne authors acknowledge support from an Australian Research Council Future Fellowship (FT150100074). In Canada, R.H. is supported by the Discovery Grants program from NSERC, and acknowledges funding from CIFAR, the Sloan Foundation, and the Dunlap family. In Italy, C.B. acknowledges support under the ASI COSMOS and INFN INDARK programs. In the Netherlands, D.M. acknowledges NWO VIDI award number 639.042.730. In Switzerland, J.C. is supported by an SNSF Eccellenza Professorial Fellowship (No. 186879). In the United Kingdom, A.L., G.F., and J.C. are supported by the European Research Council under the European Union's Seventh Framework Programme (FP/2007-2013)/ERC grant Agreement No. [616170]. A.L. also acknowledges STFC award ST/P000525/1. S.M. is supported by the research program Innovational Research Incentives Scheme (Vernieuwingsimpuls), which is financed by the Netherlands Organization for Scientific Research through the NWO VIDI grant No. 639.042.612-Nissanke and the Labex ILP (reference ANR-10-LABX-63) part of the Idex SUPER, received financial state aid managed by the Agence Nationale de la Recherche,as part of the program Investissements d'avenir under the reference ANR-11-IDEX-0004-02. Some computations in this paper were run on the Odyssey cluster, supported by the FAS Science Division Research Computing Group at Harvard University. Publisher Copyright: © 2022. The Author(s). Published by the American Astronomical Society. ; CMB-S4-the next-generation ground-based cosmic microwave background (CMB) experiment-is set to significantly advance the sensitivity of CMB measurements and enhance our understanding of the origin and evolution of the universe. Among the science cases pursued with CMB-S4, the quest for detecting primordial gravitational waves is a central driver of the experimental design. This work details the development of a forecasting framework that includes a power-spectrum-based semianalytic projection tool, targeted explicitly toward optimizing constraints on the tensor-to-scalar ratio, r, in the presence of Galactic foregrounds and gravitational lensing of the CMB. This framework is unique in its direct use of information from the achieved performance of current Stage 2-3 CMB experiments to robustly forecast the science reach of upcoming CMB-polarization endeavors. The methodology allows for rapid iteration over experimental configurations and offers a flexible way to optimize the design of future experiments, given a desired scientific goal. To form a closed-loop process, we couple this semianalytic tool with map-based validation studies, which allow for the injection of additional complexity and verification of our forecasts with several independent analysis methods. We document multiple rounds of forecasts for CMB-S4 using this process and the resulting establishment of the current reference design of the primordial gravitational-wave component of the Stage-4 experiment, optimized to achieve our science goals of detecting primordial gravitational waves for r > 0.003 at greater than 5 sigma, or in the absence of a detection, of reaching an upper limit of r < 0.001 at 95% CL. ; Peer reviewed