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Taking the pulse of Earth's tropical forests using networks of highly distributed plots

Authors:
Cecilia Blundo at National University of Tucumán
Cecilia Blundo
Julieta Carilla at National University of Tucumán
Julieta Carilla
Ricardo Grau at National University of Tucumán
Ricardo Grau
Agustina Malizia at National University of Tucumán
Agustina Malizia
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Abstract and Figures

Tropical forests are the most diverse and productive ecosystems on Earth. While better understanding of these forests is critical for our collective future, until quite recently efforts to measure and monitor them have been largely disconnected. Networking is essential to discover the answers to questions that transcend borders and the horizons of funding agencies. Here we show how a global community is responding to the challenges of tropical ecosystem research with diverse teams measuring forests tree-by-tree in thousands of long-term plots. We review the major scientific discoveries of this work and show how this process is changing tropical forest science. Our core approach involves linking long-term grassroots initiatives with standardized protocols and data management to generate robust scaled-up results. By connecting tropical researchers and elevating their status, our Social Research Network model recognises the key role of the data originator in scientific discovery. Conceived in 1999 with RAINFOR (South America), our permanent plot networks have been adapted to Africa (AfriTRON) and Southeast Asia (T-FORCES) and widely emulated worldwide. Now these multiple initiatives are integrated via ForestPlots.net cyber-infrastructure, linking colleagues from 54 countries across 24 plot networks. Collectively these are transforming understanding of tropical forests and their biospheric role. Together we have discovered how, where and why forest carbon and biodiversity are responding to climate change, and how they feedback on it. This long-term pan-tropical collaboration has revealed a large long-term carbon sink and its trends, as well as making clear which drivers are most important, which forest processes are affected, where they are changing, what the lags are, and the likely future responses of tropical forests as the climate continues to change. By leveraging a remarkably old technology, plot networks are sparking a very modern revolution in tropical forest science. In the future, humanity can benefit greatly by nurturing the grassroots communities now collectively capable of generating unique, long-term understanding of Earth's most precious forests.
Current extent of ForestPlots.net. Top: Pantropical plot sampling density per 2.5 degree square with the 4062 multiple-and single-inventory plots hosted at ForestPlots.net. These plots contribute to 24 networks including RAINFOR, AfriTRON, T-FORCES, ATDN, BIOTA, COL-TREE, FATE, GEM, Nordeste, PELD, PPBio, RAS, RBA and SEOSAW. Forest cover based on the Global Land Cover 2000 database (JRC, 2003) with tree cover categories: broad-leaved evergreen; mixed leaf type; and regularly flooded. Our plots also extend into neotropical and African savannas; Bottom: The same plot sampling but displayed at higher-resolution (1-degree grid cells) for each focal continent, South America, Africa, and Southeast Asia and Australia.
Current extent of ForestPlots.net. Top: Pantropical plot sampling density per 2.5 degree square with the 4062 multiple-and single-inventory plots hosted at ForestPlots.net. These plots contribute to 24 networks including RAINFOR, AfriTRON, T-FORCES, ATDN, BIOTA, COL-TREE, FATE, GEM, Nordeste, PELD, PPBio, RAS, RBA and SEOSAW. Forest cover based on the Global Land Cover 2000 database (JRC, 2003) with tree cover categories: broad-leaved evergreen; mixed leaf type; and regularly flooded. Our plots also extend into neotropical and African savannas; Bottom: The same plot sampling but displayed at higher-resolution (1-degree grid cells) for each focal continent, South America, Africa, and Southeast Asia and Australia.
… 
Growth of ForestPlots.net and its contributing networks since 2000. Top: Cumulative upload of unique plot censuses to ForestPlots.net by date of upload (pre-2009 uploads to pre-internet versions allocated evenly back to network beginnings); Bottom: Cumulative peer-reviewed scientific articles based on network plots, excluding research based on single-plot studies.
Growth of ForestPlots.net and its contributing networks since 2000. Top: Cumulative upload of unique plot censuses to ForestPlots.net by date of upload (pre-2009 uploads to pre-internet versions allocated evenly back to network beginnings); Bottom: Cumulative peer-reviewed scientific articles based on network plots, excluding research based on single-plot studies.
… 
Network coverage of geographical and climate space. Analyses include 1500 permanent plots managed at ForestPlots.net. (a) Top panels: (1) Geographic distance between multicensus plots across the humid tropical forest biome; and (2) Minimum climate dissimilarity (Euclidean distance on variables scaled by their standard deviation, accounting for mean annual temperature, temperature seasonality, mean annual precipitation and precipitation seasonality), where for each cell environmental distance represents how dissimilar a location is to the most climatically similar plot in the network. Note that some poorly sampled areas are mostly deforested, such as Central America, Madagascar, and much of tropical South and Southeast Asia. The baseline map depicts WWF terrestrial ecoregions (Olson et al., 2001). (b) Middle panel: Tropical plots displayed in global biome space (Whittaker diagram), showing the main concentration of plots from lowland wet through to moist forests and savanna, with some samples in cooler montane climates. (c) Lower panels: Plots displayed within tropical humid and sub-humid climate space, with plots displayed colour-coded by continent (see Fig. 2) and symbol size corresponding to total census effort. Note the important differences in baseline climatic conditions between continents.
Network coverage of geographical and climate space. Analyses include 1500 permanent plots managed at ForestPlots.net. (a) Top panels: (1) Geographic distance between multicensus plots across the humid tropical forest biome; and (2) Minimum climate dissimilarity (Euclidean distance on variables scaled by their standard deviation, accounting for mean annual temperature, temperature seasonality, mean annual precipitation and precipitation seasonality), where for each cell environmental distance represents how dissimilar a location is to the most climatically similar plot in the network. Note that some poorly sampled areas are mostly deforested, such as Central America, Madagascar, and much of tropical South and Southeast Asia. The baseline map depicts WWF terrestrial ecoregions (Olson et al., 2001). (b) Middle panel: Tropical plots displayed in global biome space (Whittaker diagram), showing the main concentration of plots from lowland wet through to moist forests and savanna, with some samples in cooler montane climates. (c) Lower panels: Plots displayed within tropical humid and sub-humid climate space, with plots displayed colour-coded by continent (see Fig. 2) and symbol size corresponding to total census effort. Note the important differences in baseline climatic conditions between continents.
… 
Pantropical forest carbon storage is independent of species richness. There are no clear within-continent or pantropical relationships between carbon stocks and tree species richness per hectare in structurally intact oldgrowth tropical forests. Figure adapted from Sullivan et al. (2017).
Pantropical forest carbon storage is independent of species richness. There are no clear within-continent or pantropical relationships between carbon stocks and tree species richness per hectare in structurally intact oldgrowth tropical forests. Figure adapted from Sullivan et al. (2017).
… 
Accurately measuring and identifying trees in remote tropical forests requires dedication, skill and courage. To measure the diameter of this giant Ceiba (Malvaceae) tree in Reserva Amargal (Colombia's Chocó), three researchers of the COL-TREE network each needed to climb >10 m. Such techniques can be the most practical and accurate options for measuring large trees. Here, like many of our sites, there is no electric power, let alone a field station, and chronic insecurity due to political and social conflicts and narcotrafficking means that aircraft and laserscanners are not deployable. Images: Pauline Kindler, University of Rouen (France).
Accurately measuring and identifying trees in remote tropical forests requires dedication, skill and courage. To measure the diameter of this giant Ceiba (Malvaceae) tree in Reserva Amargal (Colombia's Chocó), three researchers of the COL-TREE network each needed to climb >10 m. Such techniques can be the most practical and accurate options for measuring large trees. Here, like many of our sites, there is no electric power, let alone a field station, and chronic insecurity due to political and social conflicts and narcotrafficking means that aircraft and laserscanners are not deployable. Images: Pauline Kindler, University of Rouen (France).
… 
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Taking the pulse of Earth’s tropical forests using networks of highly
distributed plots
☆
ForestPlots.net
nx
, Cecilia Blundo
a
, Julieta Carilla
a
, Ricardo Grau
a
, Agustina Malizia
a
,
Lucio Malizia
b
, Oriana Osinaga-Acosta
a
, Michael Bird
c
, Matt Bradford
d
, Damien Catchpole
e
,
Andrew Ford
d
, Andrew Graham
f
, David Hilbert
g
, Jeanette Kemp
h
, Susan Laurance
i
,
William Laurance
i
, Francoise Yoko Ishida
j
, Andrew Marshall
k
,
l
,
m
, Catherine Waite
k
,
Hannsjoerg Woell
n
, Jean-Francois Bastin
o
, Marijn Bauters
p
, Hans Beeckman
q
, Pfascal Boeckx
r
,
Jan Bogaert
s
, Charles De Canniere
t
, Thales de Haulleville
u
, Jean-Louis Doucet
v
,
Olivier Hardy
w
, Wannes Hubau
x
, Elizabeth Kearsley
y
, Hans Verbeeck
z
, Jason Vleminckx
aa
,
Steven W. Brewer
ab
, Alfredo Alarc´
on
ac
, Alejandro Araujo-Murakami
ad
, Eric Arets
ae
,
Luzmila Arroyo
ad
, Ezequiel Chavez
af
, Todd Fredericksen
ac
, Ren´
e Guill´
en Villaroel
ag
,
Gloria Gutierrez Sibauty
ah
, Timothy Killeen
ai
, Juan Carlos Licona
ac
, John Lleigue
ae
,
Casimiro Mendoza
aj
, Samaria Murakami
ae
, Alexander Parada Gutierrez
ad
, Guido Pardo
ak
,
Marielos Pe˜
na-Claros
ae
, Lourens Poorter
ae
, Marisol Toledo
al
, Jeanneth Villalobos Cayo
am
,
Laura Jessica Viscarra
ai
, Vincent Vos
an
, Jorge Ahumada
ao
, Everton Almeida
ap
,
Jarcilene Almeida
aq
, Edmar Almeida de Oliveira
ar
, Wesley Alves da Cruz
as
,
Atila Alves de Oliveira
at
, Fabrício Alvim Carvalho
au
, Fl´
avio Amorim Obermuller
av
,
Ana Andrade
aw
, Fernanda Antunes Carvalho
ax
, Simone Aparecida Vieira
ay
,
Ana Carla Aquino
az
, Luiz Arag˜
ao
ba
, Ana Claudia Araújo
bb
, Marco Antonio Assis
bc
,
Jose Ataliba Mantelli Aboin Gomes
bd
, Fabrício Baccaro
be
, Plínio Barbosa de Camargo
bf
,
Paulo Barni
bg
, Jorcely Barroso
bh
, Luis Carlos Bernacci
bi
, Kauane Bordin
bj
,
Marcelo Brilhante de Medeiros
bk
, Igor Broggio
bl
, Jos´
e Luís Camargo
av
, Domingos Cardoso
bm
,
Maria Antonia Carniello
as
, Andre Luis Casarin Rochelle
bn
, Carolina Castilho
bo
,
Antonio Alberto Jorge Farias Castro
bp
, Wendeson Castro
bq
, Sabina Cerruto Ribeiro
bh
,
Fl´
avia Costa
br
, Rodrigo Costa de Oliveira
bs
, Italo Coutinho
bt
, John Cunha
bu
, Lola da Costa
bv
,
Lucia da Costa Ferreira
bw
, Richarlly da Costa Silva
bx
, Marta da Graça Zacarias Simbine
ay
,
Vitor de Andrade Kamimura
bc
, Haroldo Cavalcante de Lima
by
, Lia de Oliveira Melo
bz
,
Luciano de Queiroz
ca
, Jos´
e Romualdo de Sousa Lima
cb
, M´
ario do Espírito Santo
cc
,
Tomas Domingues
cd
, Nayane Cristina dos Santos Prestes
ce
, Steffan Eduardo Silva Carneiro
cf
,
Fernando Elias
cg
, Gabriel Eliseu
cf
, Thaise Emilio
ch
, Camila Laís Farrapo
ci
, Letícia Fernandes
bh
,
Gustavo Ferreira
cf
, Joice Ferreira
bk
, Leandro Ferreira
cj
, Socorro Ferreira
ck
,
Marcelo Fragomeni Simon
bk
, Maria Aparecida Freitas
cl
, Queila S. García
cm
,
Angelo Gilberto Manzatto
cn
, Paulo Graça
co
, Frederico Guilherme
cf
, Eduardo Hase
cl
,
Niro Higuchi
cp
, Mariana Iguatemy
cq
, Reinaldo Imbrozio Barbosa
cr
, Margarita Jaramillo
cs
,
☆
The article is attributed collectively as ForestPlots.net et al., with individual authors listed alphabetically rst by country of institution and secondly by family
name.
* Corresponding author.
E-mail address: o.l.phillips@leeds.ac.uk (O.L. Phillips).
Contents lists available at ScienceDirect
Biological Conservation
journal homepage: www.elsevier.com/locate/biocon
https://doi.org/10.1016/j.biocon.2020.108849
Received 26 June 2020; Received in revised form 26 September 2020; Accepted 23 October 2020
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, Kath Jeffery
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,
Tommaso Jucker
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, Michelle Kalamandeen
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,
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,
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, Bente Klitgaard
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, Aurora Levesley
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Simon L. Lewis
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, Jeremy Lindsell
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, Gabriela Lopez-Gonzalez
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, Jon Lovett
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,
Yadvinder Malhi
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, Toby Marthews
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, Emma McIntosh
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, Karina Melgaço
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, William Milliken
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Edward Mitchard
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, Peter Moonlight
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, Sam Moore
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, Alexandra Morel
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, Julie Peacock
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, Colin Pendry
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, R. Toby Pennington
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,
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, Luciana de Oliveira Pereira
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, Oliver L. Phillips
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,
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, Georgia Pickavance
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, Thomas Pugh
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, Lan Qie
nw
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, Katherine Roucoux
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, Casey Ryan
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, Tiina Sarkinen
lm
, Camila Silva Valeria
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Dominick Spracklen
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, Suzanne Stas
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, Martin Sullivan
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, Michael Swaine
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,
Joey Talbot
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,
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, James Taplin
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, Geertje van der Heijden
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, Laura Vedovato
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, Mathew Williams
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, Luciana Alves
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, Patricia Alvarez Loayza
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Gabriel Arellano
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, Cheryl Asa
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, Peter Ashton
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, Gregory Asner
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, Terry Brncic
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Foster Brown
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, Robyn Burnham
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, Connie Clark
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, James Comiskey
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, Gabriel Damasco
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, Tony Di Fiore
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, Terry Erwin
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, William Farfan-Rios
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, Jefferson Hall
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,
David Kenfack
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, Thomas Lovejoy
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, Roberta Martin
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, Olga Martha Montiel
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John Pipoly
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, John Poulsen
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, Richard Primack
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, Miles Silman
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Marc Steininger
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, Varun Swamy
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, John Terborgh
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, Duncan Thomas
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, Peter Umunay
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, Emilio Vilanova Torre
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, Ophelia Wang
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, Kenneth Young
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, Lionel Hern´
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, Rafael Herrera Fern´
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Hirma Ramírez-Angulo
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, Pedro Salcedo
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, Elio Sanoja
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, Julio Serrano
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,
Armando Torres-Lezama
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, Tinh Cong Le
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, Trai Trong Le
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, Hieu Dang Tran
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a
Instituto de Ecología Regional (IER), Universidad Nacional de Tucum´
an (UNT), Consejo Nacional de Investigaciones Cientícas y T´
ecnicas (CONICET), Argentina
b
Facultad de Ciencias Agrarias, Universidad Nacional de Jujuy, Jujuy, Argentina
c
James Cook University (JCU), Australia
d
CSIRO (Commonwealth Scientic and Industrial Research Organisation), Australia
ForestPlots.net et al.
e
School of Land & Food, University of Tasmania, Australia
f
CSIRO Tropical Forest Research Centre, Australia
g
Independent Researcher, Australia
h
Environmental Protection Agency (EPA), Australia
i
Centre for Tropical Environmental and Sustainability Science (TESS), College of Marine and Environmental Sciences, James Cook University, Australia
j
Centre for Tropical Environmental and Sustainability Science, College of Science and Engineering, James Cook University, Australia
k
University of the Sunshine Coast, Australia
l
University of York, United Kingdom
m
Flamingo Land Ltd., United Kingdom
n
Sommersbergseestrasse, Austria
o
Ghent University, Belgium
p
CAVElab, Ghent University, Belgium
q
Royal Museum for Central Africa - Service of Wood Biology, Belgium
r
Isotope Bioscience Laboratory-ISOFYS, Ghent University, Belgium
s
Gembloux Agro-Bio Tech, Universit´
e de Liege, Belgium
t
Landscape Ecology and Vegetal Production Systems Unit, Belgium
u
CAVElab Computational & Applied Vegetation Ecology, Ghent University, Belgium
v
Tropical Forestry, Forest Resources Management, Gembloux Agro-Bio Tech, University of Liege, Belgium
w
Universit´
e Libre de Bruxelles (ULB), Evolutionary Biology and Ecology, Belgium
x
Royal Museum for Central Africa, Belgium
y
Royal Museum for Central Africa, Ghent University, Belgium
z
Department of Environment, Ghent University, Belgium
aa
Service Evolution Biologique et Ecologie, Belgium
ab
Belize Foundation for Research and Environmental Education, Belize
ac
IBIF, Bolivia
ad
Museo de Historia Natural Noel Kempff Mercado, Universidad Autonoma Gabriel Rene Moreno, Bolivia
ae
PROMAB, Bolivia
af
Museo Noel Kempff, Bolivia
ag
Consultor Independiente, Bolivia
ah
Jardin Botanico Municipal de Santa Cruz, Bolivia
ai
Museo de Historia Natural Noel Kempff Mercado, Bolivia
aj
Forest Management in Bolivia, Bolivia
ak
Universidad Aut´
onoma del Beni Riberalta, Bolivia
al
Museo de Historia Natural Noel Kempff, Bolivia
am
Herbario del Sur de Bolivia, Bolivia
an
Universidad Aut´
onoma del Beni, Bolivia
ao
Conservation International, Brazil
ap
Instituto de Biodiversidade e Floresta, Universidade Federal do Oeste do Par´
a, Brazil
aq
Universidade Federal de Pernambuco, Brazil
ar
Universidade do Estado de Mato Grosso, Brazil
as
Universidade do Estado de Mato Grosso (UNEMAT), Brazil
at
Projeto TEAM – Manaus, Brazil
au
Universidade Federal de Juiz de Fora (UFJF), Brazil
av
Universidade Federal do Rio de Janeiro, Brazil
aw
Instituto Nacional de Pesquisas da Amazˆ
onia, Projeto Dinˆ
amica Biol´
ogica de Fragmentos Florestais, Brazil
ax
Departamento de Gen´
etica, Ecologia e Evoluç˜
ao, Universidade Federal de Minas Gerais, Brazil
ay
Universidade Estadual de Campinas, Brazil
az
Laborat´
orio de Ecologia de Comunidades e Funcionamento de Ecossistemas-ECoFERP, Departamento de Biologia, Faculdade de Filosoa, Ciˆ
encias e Letras, USP,
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ba
National Institute for Space Research (INPE), Brazil
bb
Universidade Federal de Roraima (UFRR), Brazil
bc
UNESP - S˜
ao Paulo State University, Brazil
bd
Carbonozero Consultoria Ambiental, Brazil
be
Departamento de Biologia, Universidade Federal do Amazonas (UFAM), Brazil
bf
Centro de Energia Nuclear na Agricultura, Universidade de S˜
ao Paulo, Brazil
bg
UERR - Campus Rorain´
opolis, Brazil
bh
Universidade Federal do Acre, Brazil
bi
Instituto Agronˆ
omico de Campinas, Brazil
bj
Universidade Federal do Rio Grande do Sul, Brazil
bk
Embrapa, Brazil
bl
Universidade Estadual do Norte Fluminense (UENF), Brazil
bm
Universidade Federal da Bahia (UFBA), Brazil
bn
Instituto de Biologia, Universidade Estadual de Campinas, Brazil
bo
Embrapa, Roraima, Brazil
bp
Universidade Federal do Piauí (UFPI), Teresina, Brazil
bq
Botany and Plant Ecology Laboratory, Federal University of Acre, Brazil
br
INPA- Instituto Nacional de Pesquisas da Amazˆ
onia, Brazil
bs
UERR - Campus Boa Vista, Brazil
bt
Universidade Federal do Cear´
a, Brazil
bu
Universidade Federal de Campina Grande, Brazil
bv
Universidade Federal do Para, Brazil
bw
Núcleo de Estudos e Pesquisas Ambientais, Universidade Estadual de Campinas, Brazil
bx
Instituto Federal de Educaç˜
ao, Ciˆ
encia e Tecnologia do Acre, Brazil
by
Instituto de Pesquisas Jardim Botˆ
anico do Rio de Janeiro, Brazil
bz
Universidade Federal do Oeste do Par´
a, Brazil
ca
UEFS, Depto. de Ciˆ
encias Biol´
ogicas, Brazil
cb
Universidade Federal do Agreste de Pernambuco (UFAPE), Brazil
cc
Universidade Estadual de Montes Claros, Brazil
cd
FFCLRP-USP/Br, Brazil
ce
UNEMAT, Brazil
ForestPlots.net et al.
cf
Universidade Federal de Jataí, Brazil
cg
Universidade Federal do Par´
a, Instituto de Ciˆ
encias Biol´
ogicas, Brazil
ch
Universidade de Campinas, Brazil
ci
Universidade Federal de Lavras (UFLA), Brazil
cj
Museu Goeldi, Brazil
ck
Embrapa Amazˆ
onia Oriental, Brazil
cl
Instituto Nacional de Pesquisas da Amazˆ
onia, Brazil
cm
UFMG - Universidade Federal de Minas Gerais, Brazil
cn
Fundaç˜
ao Universidade Fedral de Rondˆ
onia - UNIR, Brazil
co
INPA- Instituto Nacional de Pesquisas Amazˆ
onicas, Brazil
cp
Instituto Nacional de Pesquisas da Amazˆ
onia - Coordenaç˜
ao de Pesquisas em Silvicultura Tropical, Brazil
cq
Jardim Botˆ
anico do Rio de Janeiro, Brazil
cr
National Institute for Research in Amazonia, Brazil
cs
Universidade Federal de Roraima (UFRR/PRONAT), Brazil
ct
Universidade Estadual de Campinas/UNICAMP, Brazil
cu
Instituto Nacional de Pesquisas da Amazˆ
onia/CPBO, Brazil
cv
Universidade Federal de Santa Catarina (UFSC), Brazil
cw
INCAPER- Instituto Capixaba de Pesquisa, Assistˆ
encia T´
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ao Rural, Brazil
cx
INPE- Instituto Nacional de Pesquisas Espaciais, Brazil
cy
Universidade de S˜
ao Paulo, Brazil
cz
Instituto de Biociˆ
encias, Universidade Estadual Paulista, Brazil
da
Semiarid National Institute (INSA), Brazil
db
Universidade de Brasília, Departamento de Engenharia Florestal, Brazil
dc
IBAM - Instituto Bem Ambiental, Brazil
dd
Universidade do Estado de Mato Grosso, Campus de Nova Xavantina, Brazil
de
University in Campinas, Brazil
df
Universidade Estadual do Norte Fluminense Darcy Ribeiro (UENF), Brazil
dg
LMF, Instituto Nacional de Pesquisas da Amazˆ
onia, Brazil
dh
Universidade Federal do Vale do S˜
ao Francisco, Brazil
di
USP - University of S˜
ao Paulo, Brazil
dj
Instituto Federal do Espírito Santo (IFES), Brazil
dk
INPA - Instituto Nacional de Pesquisas da Amazˆ
onia, Grupo MAUA, Brazil
dl
Universidade Federal de Mato Grosso, Instituto de Ciˆ
encias Naturais, Humanas e Sociais, Sinop, Brazil
dm
Instituto Nacional da Mata Atlˆ
antica, Brazil
dn
RAINFOR-PPBIO, Brazil
do
Universidade Federal Rural da Amazˆ
onia - UFRA/CAPES, Brazil
dp
Universidade Federal do Amazonas (UFAM), Brazil
dq
INPA/Max-Planck Project, Brazil
dr
EMBRAPA- Empresa Brasileira de Pesquisa Agropecu´
aria (Amazˆ
onia Oriental), Brazil
ds
Serviço Florestal Brasileiro, Brazil
dt
Museu Universit´
ario, Universidade Federal do Acre, Brazil
du
Universidade Federal Rural de Pernambuco, Brazil
dv
PUCPR - Pontifícia Universidade Cat´
olica do Paran´
a, Brazil
dw
Museu Paraense Emilio Goeldi, Brazil
dx
Universiti Brunei Darussalam, Brunei
dy
Environmental and Life Sciences, Faculty of Science, Universiti Brunei Darussalam, Brunei
dz
Institute for Biodiversity and Environmental Research, Universiti Brunei Darussalam, Brunei
ea
Plant Systematic and Ecology Laboratory, Department of Biology, Higher Teachers’ Training College, University of Yaounde I, Cameroon
eb
Faculty of Science, Department of Botany and Plant Physiology, University of Buea, Buea, Cameroon
ec
Faculty of Science, Department of Plant Science, University of Buea, Cameroon
ed
National Herbarium, Yaounde, Cameroon
ee
Plant Systematics and Ecology Laboratory, Higher Teachers’ Training College, University of Yaound´
e I, Cameroon
ef
Department of Plant Biology, Faculty of Sciences, University of Yaounde 1, Cameroon
eg
Bioversity International, Yaound´
e, Cameroon
eh
Faculty of Forestry, University of Toronto, Canada
ei
Minist`
ere des Eaux, Forˆ
ets, Chasse et Pˆ
eche (MEFCP), Bangui, Central African Republic
ej
Universidad Cat´
olica de la Santísima Concepci´
on, Chile
ek
Universidad de La Serena, Chile
el
Research Institute of Tropical Forestry, Chinese Academy of Forestry, China
em
Kunming Institute of Botany, Chinese Academy of Sciences, China
en
Beijing Forestry University, China
eo
Universidad Nacional Abierta y a Distancia, Red COL-TREE, Colombia
ep
Corporaci´
on COL-TREE, Colombia
eq
Nuevo Est´
andar Biotropical NEBIOT SAS, Colombia
er
Universidad del Tolima, Colombia
es
Asociaci´
on GAICA, Universidad de Nari˜
no – Red BST-Col, Colombia
et
Parques Nacionales Naturales, Territorial Caribe – Red BST-Col, Colombia
eu
Universidad del Atlantico – Red BST-Col, Colombia
ev
Departamento de Ciencias Forestales, Universidad Nacional de Colombia - Sede Medellín, Colombia
ew
Socioecosistemas y Clima Sostenible, Fundacion con Vida, Colombia
ex
Parques Nacionales Naturales de Colombia – Red BST-Col, Colombia
ey
Instituto de Investigaci´
on de Recursos Biol´
ogicos Alexander von Humboldt – Red BST-Col, Colombia
ez
UNAL, Colombia
fa
Instituto de Investigaci´
on Recursos Biologicos Alexander von Humboldt – Red BST-Col, Colombia
fb
Fundaci´
on Jardín Bot´
anico de Medellín, Herbario “Joaquín Antonio Uribe” (JAUM) – Red BST-Col, Colombia
fc
Universidad Nacional de Colombia sede Amazonia, Colombia
fd
Coltree, Colombia
fe
Facultad del Medio Ambiente y Recursos Naturales, Universidad Distrital Francisco Jos´
e de Caldas – Red BST-Col, Colombia
ff
Universidad de Tolima, Colombia
fg
Fundaci´
on Orinoquia Biodiversa – Red BST-Col, Colombia
ForestPlots.net et al.
fh
Departamento de Biología, Facultad de Ciencias Naturales, Universidad Icesi – Red BST-Col, Colombia
Instituto de Ciencias Naturales, Universidad Nacional de Colombia, Colombia
fj
Universidad de los Llanos, Colombia
fk
Servicios Ecoysistemicos y Cambio Climatico (SECC) Fundaci´
on Con Vida & Corporaci´
on COL-TREE, Colombia
Universidad del Rosario, Colombia
fm
Fundacion Ecosistemas Secos de Colombia – Red BST-Col, Colombia
fn
Universidad de los Andes - ANDES herbarium, Colombia
fo
Institute of Botany, Czech Academy of Sciences, Czech Republic
fp
Palacky University, Czech Republic
fq
Czech University of Life Sciences, Prague, Czech Republic
fr
Mendel University, Brno, Czech Republic
fs
World Wide Fund for Nature, Democratic Republic of the Congo
ft
Wildlife Conservation Society-DR Congo, Democratic Republic of the Congo
fu
Lukuru Wildlife Research Foundation, Democratic Republic of the Congo
fv
Universit´
e de Kisangani, Democratic Republic of the Congo
fw
Facult´
e des Sciences, Laboratoire d’
´
ecologie et am´
enagement forestier, Universit´
e de Kisangani, Kisangani, Democratic Republic of the Congo
fx
Universit´
e de Kisangani Facult´
e des Sciences Agronomiques R´
epublique D´
emocratique du Congo, Democratic Republic of the Congo
fy
Minist`
ere de l’Environnement et D´
eveloppement Durable, Kinshasa, Democratic Republic of the Congo
fz
Aarhus University, Denmark
ga
University of Copenhagen, Denmark
gb
Escuela Polit´
ecnica Nacional del Ecuador, Ecuador
gc
Herbario Alfredo Paredes (QAP), Universidad Central del Ecuador, Ecuador
gd
Universidad T´
ecnica Particular de Loja, Ecuador
ge
Grupo de Investigaci´
on en Biodiversidad, Medio Ambiente y Salud-BIOMAS, Universidad de las Am´
ericas, Campus Queri, Quito, Ecuador
gf
Keller Science Action Center, The Field Museum, 1400 South Lake Shore Dr., Chicago, IL, USA
gg
Universidad Estatal Amaz´
onica, Facultad de Ingeniería Ambiental, Ecuador
gh
Universidad Tecnica del Norte, Herbario Nacional del Ecuador, Ecuador
gi
Grupo de Ecosistemas Tropicales y Cambio Global, Universidad Regional Amaz´
onica ikiam, Ecuador
gj
Colegio de Ciencias Biol´
ogicas y Ambientales COCIBA & Extensi´
on Gal´
apagos, Universidad San Francisco de Quito-USFQ, Ecuador
gk
Herbario de Bot´
anica Econ´
omica del Ecuador QUSF, Universidad San Francisco de Quito USFQ, Ecuador
gl
Galapagos Science Center, USFQ, UNC Chapel Hill, San Cristobal, Galapagos, Ecuador
gm
University of North Carolina-UNC Chapel Hill, USA
gn
University of Florida, Gainesville, USA
go
FindingSpecies, Ecuador
gp
Mekelle University, Ethiopia
gq
Independent Researcher, Ethiopia
gr
Environment, Climate Change and Coffee Forest Forum (ECCCFF), Ethiopia
gs
University of Turku, Finland
gt
Centre de coop´
eration International en Recherche Agronomique pour le D´
eveloppement (CIRAD), France
gu
CNRS, France
gv
ONF, France
gw
INRAE, France
gx
Centre National de la Recherche Scientique, France
gy
AMAP, Univ Montpellier, IRD, CNRS, CIRAD, INRA, Montpellier, France
gz
Forˆ
ets et Soci´
et´
es (F&S), Centre de coop´
eration International en Recherche Agronomique pour le D´
eveloppement (CIRAD), Montpellier, France
ha
Departement Hommes Natures Societes, Museum national d’histoire naturelle, France
hb
INRA, Kourou, French Guiana
hc
Cirad, UMR Ecologie des Forˆ
ets de Guyane (AgroparisTech, CNRS, INRAE, Universit´
e des Antilles, Universit´
e de la Guyane), French Guiana
hd
Ministry of Forests, Seas, Environment and Climate, Gabon
he
Rougier-Gabon, Gabon
hf
Agence Nationale des Parcs Nationaux Gabon, Gabon
hg
Commission of Central African Forests (COMIFAC), Libreville, Gabon
hh
Agence Nationale des Parcs Nationaux, Minist`
ere des Forˆ
ets, des Eaux, de la Mer, de l’Environnement, Charg´
e du Plan Climat, des Objectifs de D´
eveloppement Durable
et du Plan d’Affectation des Terres, Gabon
hi
Institut de Recherche en Ecologie Tropicale (CENAREST) Gabon/Agence Nationale des Parcs Nationaux, Gabon
hj
Georg-August-University G¨
ottingen, Germany
hk
University of Freiburg, Germany
hl
Institute of Botany, University of Hohenheim, 70593 Stuttgart, Germany
hm
Max Planck Institute for Chemistry, Germany
hn
Forestry Research Institute of Ghana (FORIG), Ghana
ho
Mensuration Unit, Forestry Commission of Ghana, Ghana
hp
Center for International Forestry Research, Guinea
hq
Iwokrama International Centre for Rainforest Conservation and Development, Guyana
hr
Guyana Forestry Commission, Guyana
hs
Utrecht University, Guyana
ht
Centre for Sustainable Technologies, Indian Institute of Science, India
hu
Centre for International Forestry Research (CIFOR), Indonesia
hv
Herbarium Borgoriense, Indonesian Institute of Sciences (LIPI), Indonesia
hw
Indonesian Institute of Science, Bogor, Indonesia
hx
Forest Research and Development Agency (FORDA), Indonesia
hy
Balitek-KSDA Samboja, Indonesia
hz
University of Florence and MUSE - Museo delle Scienze, Italy
ia
Bioversity International, Italy
ib
Cirad, Cote d’Ivoire
ic
Hokkaido University, Japan
id
Graduate School of Agriculture, Kyoto University, Japan
ie
Forestry Development Authority of the Government of Liberia (FDA), Liberia
if
University of Liberia, Liberia
ig
Sungai Wain Protection Forest, Malaysia
ih
South East Asia Rainforest Research Partnership, Danum Valley Field Centre, Lahad Datu, Sabah, Malaysia
ForestPlots.net et al.
ii
Malaysian Palm Oil Board, Malaysia
ij
Sabah Forestry Department, Forest Research Centre, Sandakan, Sabah, Malaysia
ik
Universiti Malaysia Sabah, Malaysia
il
Sabah Forestry Department, Malaysia
im
Sarawak Forestry Corporation, Malaysia
in
Eduardo Mondlane University, Mozambique
io
Herbarium UNAN-Leon, Universidad Nacional Aut´
onoma de Nicaragua, Nicaragua
ip
University of Abeokuta, Nigeria
iq
Natural History Museum of Norway, Norway
ir
University of Oslo, Norway
is
Norwegian University of Life Sciences, Norway
it
Universidad Nacional de la Amazonía Peruana (UNAP), Peru
iu
Universidad Nacional de Ja´
en, Peru
iv
Jardin Botanico de Missouri, Oxapampa, Peru
iw
Andes to Amazon Biodiversity Program, Peru
ix
Universidad Nacional de San Agustín de Arequipa, Peru
iy
Facultad de Ciencias Biol´
ogicas, Universidad Nacional de la Amazonía Peruana, Peru
iz
Ken´
e - Instituto de Estudios Forestales y Ambientales, Peru
ja
Instituto de Investigaciones de la Amazonia Peruana (IIAP), Peru
jb
Universidad Nacional Jorge Basadre de Grohmann (UNJBG), Peru
jc
Universidad Nacional de San Antonio Abad del Cusco, Peru
jd
Centro de Conservaci´
on, Investigaci´
on y Manejo, CIMA, Peru
je
Ponticia Universidad Cat´
olica del Perú, Peru
jf
Asociacion Bosques Perú, Peru
jg
Universit´
e Ofcielle de Bukavu, Bukavu, Congo
jh
Universit´
e Marien N’Gouabi, Brazzaville, Congo
ji
Wildlife Conservation Society, Congo
jj
Ecole Nationale Sup´
erieure d’Agronomie et de Foresterie, Universit´
e Marien Ngouabi, Congo
jk
Univeriste Marien Ngouabi, Congo
jl
The Gola Rainforest National Park, Kenema, Sierra Leone
jm
Department of Geography, National University of Singapore, Singapore
jn
Departamento de Biología y Geología, Física y Química inorg´
anica, Universidad Rey Juan Carlos, Spain
jo
Real Jardín Bot´
anico – CSIC, Spain
jp
Departamento de Biología, ´
Area de Bot´
anica, Universidad Aut´
onoma de Madrid, Spain
jq
Museo Nacional de Ciencias Naturales (MNCN-CSIC), Spain
jr
Centre for Agricultural Research in Suriname (CELOS), Suriname
js
Stockholm Environment Institute, Sweden
jt
Department of Plant Ecology and Evolution, Uppsala University, Sweden
ju
Southern Swedish Forest Research Centre, Sweden
jv
InfoFlora, Conservatoire et Jardin Botanique Geneve, Switzerland
jw
National Chung Hsing University, Taiwan
jx
Sokoine University of Agriculture, Tanzania
jy
Naturalis Biodiversity Center, The Netherlands
jz
Wageningen University, Forest Ecology and Forest Management Group, The Netherlands
ka
Tropenbos International, The Netherlands
kb
Institute for Biodiversity and Ecosystem Dynamics, University of Amsterdam, The Netherlands
kc
Bureau Waardenburg BV, The Netherlands
kd
Van Hall Larenstein University of Applied Sciences, The Netherlands
ke
Van der Hout Forestry Consulting, The Netherlands
kf
Utrecht University, Domplein 29, 3512 JE Utrecht, The Netherlands
kg
PROMAB, The Netherlands
kh
Wageningen University, Plant Ecology and Nature Conservation Group, The Netherlands
ki
Data for Sustainability, The Netherlands
kj
Utrecht University, The Netherlands
kk
Department of Zoology, Entomology & Fisheries Sciences, Makerere University, Kampala, Uganda
kl
The Institute of Tropical Forest Conservation (ITFC), Mbarara University of Science and Technology (MUST), Mbarara, Uganda
km
George Washington University, Uganda
kn
Makerere University, Kampala, Uganda
ko
Department of Forestry, Biodiversity and Tourism, Makerere University, Kampala, Uganda
kp
Wildlife Conservation Society, Uganda
kq
University of Stirling, United Kingdom
kr
University of Kent, United Kingdom
ks
School of Geography, University of Leeds, U.K.
kt
UK Centre of Ecology & Hydrology, United Kingdom
ku
Lancaster University, United Kingdom
kv
University of Oxford, United Kingdom
kw
The Landscapes and Livelihoods Group (TLLG), United Kingdom
kx
Overseas Development Institute, United Kingdom
ky
Manchester Metropolitan University, United Kingdom
kz
University of Aberdeen, United Kingdom
la
University of Exeter, United Kingdom
lb
School of GeoSciences, University of Edinburgh, United Kingdom
lc
University of Cambridge, United Kingdom
ld
Department of Environment and Geography, University of York, United Kingdom
le
Department of Geography, University College London, United Kingdom
lf
Imperial College, London, United Kingdom
lg
School of Geography, Earth & Environmental Sciences, Birmingham Institute of Forest Research, University of Birmingham, United Kingdom
lh
University of Plymouth, United Kingdom
li
Geography, College of Life and Environmental Sciences, University of Exeter, United Kingdom
lj
Lancaster Environment Centre, Lancaster University, United Kingdom
ForestPlots.net et al.
lk
University of Edinburgh, United Kingdom
ll
School of Biology, University of Leeds, United Kingdom
lm
Royal Botanic Garden Edinburgh, United Kingdom
ln
CENAREST & ANPN & Stirling University, United Kingdom
lo
University of Bristol, School of Biological Sciences, United Kingdom
lp
Department of Plant Sciences, University of Cambridge, United Kingdom
lq
Living with Lake Centre, Laurentian University, Canada
lr
Royal Botanic Gardens Kew, United Kingdom
ls
The Royal Society for the Protection of Birds, Centre for Conservation Science, Sandy, United Kingdom
lt
Environmental Change Institute, School of Geography and the Environment, University of Oxford, United Kingdom
lu
UK Centre for Ecology & Hydrology, United Kingdom
lv
School of Geography and the Environment, University of Oxford, United Kingdom
lw
The Royal Botanic Gardens, United Kingdom
lx
Department of Geography and Environmental Science, University of Dundee, United Kingdom
ly
School of Biological Sciences, University of Southampton, United Kingdom
lz
University of East Anglia, United Kingdom
ma
Stirling University, United Kingdom
mb
School of Earth and Environment, University of Leeds, United Kingdom
mc
Department of Plant & Soil Science, Cruickshank Building, School of Biological Sciences, University of Aberdeen, United Kingdom
md
Institute for Transport Studies, University of Leeds, United Kingdom
me
UK Research & Innovation, United Kingdom
mf
University of Nottingham, United Kingdom
mg
University of Bangor, United Kingdom
mh
Center for Tropical Research, Institute of the Environment and Sustainability, University of California, Los Angeles, USA
mi
Center for Tropical Conservation, Nicholas School of the Environment, Duke University, USA
mj
Ecology and Evolutionary Biology, University of Michigan, USA
mk
Saint Louis Zoo, USA
ml
Department of Organismic and Evolutionary Biology, Harvard University, USA
mm
Center for Global Discovery and Conservation Science, Arizona State University, USA
mn
Wildlife Conservation Society – Programme Congo, USA
mo
Woods Hole Research Center, USA
mp
The University of Michigan Herbarium, USA
mq
Nicholas School of the Environment, USA
mr
National Park Service, USA
ms
University of California, USA
mt
ForestGEO, Smithsonian Tropical Research Institute, USA
mu
University of Texas at Austin, USA
mv
Smithsonian Institute, USA
mw
Washington University in Saint Louis, Center for Conservation and Sustainable Development at the Missouri Botanical Garden, USA
mx
Smithsonian Tropical Research Institute, Smithsonian Institution Forest Global Earth Observatory (ForestGEO), USA
my
Forest Global Earth Observatory (ForestGEO), Smithsonian Tropical Research Institute, Washington, DC, USA
mz
George Mason University, VA, USA
na
Missouri Botanical Garden, USA
nb
Broward County Parks and Recreation, USA
nc
Nova Southeastern University, USA
nd
Science and Education, The Field Museum, USA
ne
Department of Biology, Boston University, USA
nf
Wake Forest University, USA
ng
Department of Geographical Sciences, University of Maryland, College Park, MD, USA
nh
San Diego Zoo Institute for Conservation Research, USA
ni
Biology Department, Washington State University, Vancouver, WA, USA
nj
Yale School of Forestry & Environmental Studies, USA
nk
Columbia University, USA
nl
Department of Environmental Science, Policy, and Management, University of California, Berkeley, USA
nm
School of Earth Sciences and Environmental Sustainability, Northern Arizona University, USA
nn
Department of Geography and the Environment, University of Texas at Austin, USA
no
UNELLEZ-Guanare, Programa de Ciencias del Agro y el Mar, Herbario Universitario (PORT), Ci Progress GreenLife, Venezuela
np
Universidad Nacional Experimental de Guayana, Venezuela
nq
Instituto Venezolano de Investigaciones Cientícas (IVIC), Venezuela
nr
Universidad de los Andes, Merida, Venezuela
ns
Viet Nature Conservation Centre, Viet Nam
nt
CIRAD, French Guiana
nu
INRAE, French Guiana
nv
Center for International Forestry Research, Indonesia
nw
School of Life Sciences, University of Lincoln, U.K.
nx
A global collaborative hosted at the University of Leeds
ny
Universidad Nacional Agraria La Molina (UNALM), Peru
ARTICLE INFO
Keywords:
Amazonia
Africa
Southeast Asia
Rainforest
RAINFOR
AfriTRON
Species richness
ABSTRACT
Tropical forests are the most diverse and productive ecosystems on Earth. While better understanding of these
forests is critical for our collective future, until quite recently efforts to measure and monitor them have been
largely disconnected. Networking is essential to discover the answers to questions that transcend borders and the
horizons of funding agencies. Here we show how a global community is responding to the challenges of tropical
ecosystem research with diverse teams measuring forests tree-by-tree in thousands of long-term plots. We review
the major scientic discoveries of this work and show how this process is changing tropical forest science. Our
core approach involves linking long-term grassroots initiatives with standardized protocols and data
ForestPlots.net et al.
Forest plots
Permanent sample plots
Monitoring
Dynamics
Carbon sink
Global change
Ecology
Biodiversity
management to generate robust scaled-up results. By connecting tropical researchers and elevating their status,
our Social Research Network model recognises the key role of the data originator in scientic discovery.
Conceived in 1999 with RAINFOR (South America), our permanent plot networks have been adapted to Africa
(AfriTRON) and Southeast Asia (T-FORCES) and widely emulated worldwide. Now these multiple initiatives are
integrated via ForestPlots.net cyber-infrastructure, linking colleagues from 54 countries across 24 plot networks.
Collectively these are transforming understanding of tropical forests and their biospheric role. Together we have
discovered how, where and why forest carbon and biodiversity are responding to climate change, and how they
feedback on it. This long-term pan-tropical collaboration has revealed a large long-term carbon sink and its
trends, as well as making clear which drivers are most important, which forest processes are affected, where they
are changing, what the lags are, and the likely future responses of tropical forests as the climate continues to
change. By leveraging a remarkably old technology, plot networks are sparking a very modern revolution in
tropical forest science. In the future, humanity can benet greatly by nurturing the grassroots communities now
collectively capable of generating unique, long-term understanding of Earth’s most precious forests.
Resumen: Los bosques tropicales son los ecosistemas m´
as diversos y productivos del mundo y entender su
funcionamiento es crítico para nuestro futuro colectivo. Sin embargo, hasta hace muy poco, los esfuerzos para
medirlos y monitorearlos han estado muy desconectados. El trabajo en redes es esencial para descubrir las
respuestas a preguntas que trascienden las fronteras y los plazos de las agencias de nanciamiento. Aquí mos-
tramos c´
omo una comunidad global est´
a respondiendo a los desafíos de la investigaci´
on en ecosistemas tropicales
a trav´
es de diversos equipos realizando mediciones ´
arbol por ´
arbol en miles de parcelas permanentes de largo
plazo. Revisamos los descubrimientos m´
as importantes de este trabajo y discutimos c´
omo este proceso est´
a
cambiando la ciencia relacionada a los bosques tropicales. El enfoque central de nuestro esfuerzo implica la
conexi´
on de iniciativas locales de largo plazo con protocolos estandarizados y manejo de datos para producir
resultados que se puedan trasladar a múltiples escalas. Conectando investigadores tropicales, elevando su pos-
ici´
on y estatus, nuestro modelo de Red Social de Investigaci´
on reconoce el rol fundamental que tienen, para el
descubrimiento cientíco, quienes generan o producen los datos. Concebida en 1999 con RAINFOR (Suram´
erica),
nuestras redes de parcelas permanentes han sido adaptadas en ´
Africa (AfriTRON) y el sureste asi´
atico (T-
FORCES) y ampliamente replicadas en el mundo. Actualmente todas estas iniciativas est´
an integradas a trav´
es de
la ciber-infraestructura de ForestPlots.net, conectando colegas de 54 países en 24 redes diferentes de parcelas.
Colectivamente, estas redes est´
an transformando nuestro conocimiento sobre los bosques tropicales y el rol de
´
estos en la bi´
osfera. Juntos hemos descubierto c´
omo, d´
onde y porqu´
e el carbono y la biodiversidad de los bosques
tropicales est´
a respondiendo al cambio clim´
atico y c´
omo se retroalimentan. Esta colaboraci´
on pan-tropical de
largo plazo ha expuesto un gran sumidero de carbono y sus tendencias, mostrando claramente cu´
ales son los
factores m´
as importantes, qu´
e procesos se ven afectados, d´
onde ocurren los cambios, los tiempos de reacci´
on y
las probables respuestas futuras mientras el clima continúa cambiando. Apalancando lo que realmente es una
tecnología antigua, las redes de parcelas est´
an generando una verdadera y moderna revoluci´
on en la ciencia
tropical. En el futuro, la humanidad puede beneciarse enormemente si se nutren y cultivan comunidades de
investigadores de base, actualmente con la capacidad de generar informaci´
on única y de largo plazo para
entender los que probablemente son los bosques m´
as preciados de la tierra.
Resumo: Florestas tropicais s˜
ao os ecossistemas mais diversos e produtivos da Terra. Embora uma boa
compreens˜
ao destas orestas seja crucial para o nosso futuro coletivo, at´
e muito recentemente os esforços de
mediç˜
oes e monitoramento tem sido amplamente desconexos. ´
E essencial formarmos redes para obtermos
respostas que transcendam as fronteiras e horizontes das agˆ
encias nanciadoras. Neste estudo n´
os mostramos
como uma comunidade global est´
a respondendo aos desaos da pesquisa de ecossistemas tropicais, com equipes
diversas medindo orestas, ´
arvore por ´
arvore, em milhares de parcelas monitoradas a longo prazo. N´
os revisamos
as maiores descobertas cientícas deste esforço global, e mostramos tamb´
em como este processo vem mudando a
ciˆ
encia de orestas tropicais. Nossa abordagem principal envolve unir iniciativas de base a protocolos padro-
nizados e gerenciamento de dados a m de gerar resultados robustos em grandes escalas. Ao conectar pesqui-
sadores tropicais e elevar seus status, nosso modelo de Rede de Pesquisa Social reconhece o papel chave do
produtor dos dados na descoberta cientíca. Concebida em 1999 com o RAINFOR (Am´
erica do Sul), nossa rede
de parcelas permanentes foi adaptada para ´
Africa (AfriTRON) e Sudeste Asi´
atico (T-FORCES), e tem sido
extensamente reproduzida em todo o mundo. Agora estas múltiplas iniciativas est˜
ao integradas atrav´
es da
infraestrutura cibern´
etica do ForestPlots.net, conectando colegas de 54 países e 24 redes de parcelas. Estas
iniciativas est˜
ao transformando coletivamente o entendimento das orestas tropicais e seus pap´
eis na biosfera.
Juntos n´
os descobrimos como, onde e por que o carbono e a biodiversidade da oresta est˜
ao respondendo `
as
mudanças clim´
aticas, e seus efeitos de retroalimentaç˜
ao. Esta duradoura colaboraç˜
ao pantropical revelou um
grande sumidouro de carbono persistente e suas tendˆ
encias, assim como tem evidenciado quais os fatores que
inuenciam essas tendˆ
encias, quais processos orestais s˜
ao mais afetados, onde eles est˜
ao mudando, seus atrasos
no tempo de resposta, e as prov´
aveis respostas das orestas tropicais conforme o clima continua a mudar. Dessa
forma, aproveitando uma not´
avel tecnologia antiga, redes de parcelas acendem as faíscas de uma moderna
revoluç˜
ao na ciˆ
encia das orestas tropicais. No futuro a humanidade pode se beneciar incentivando estas
comunidades locais que agora s˜
ao coletivamente capazes de gerar conhecimentos únicos e duradouros sobre as
orestas mais preciosas da Terra.
R´
esume: Les forˆ
ets tropicales sont les ´
ecosyst`
emes les plus diversi´
es et les plus productifs de la plan`
ete. Si une
meilleure compr´
ehension de ces forˆ
ets est essentielle pour notre avenir collectif, jusqu’`
a tout r´
ecemment, les
efforts d´
eploy´
es pour les mesurer et les surveiller ont ´
et´
e largement d´
econnect´
es. La mise en r´
eseau est essentielle
pour d´
ecouvrir les r´
eponses `
a des questions qui d´
epassent les fronti`
eres et les horizons des organismes de
nancement. Nous montrons ici comment une communaut´
e mondiale rel`
eve les d´
es de la recherche sur les
´
ecosyst`
emes tropicaux avec diverses ´
equipes qui mesurent les forˆ
ets arbre apr`
es arbre dans de milliers de par-
celles permanentes. Nous passons en revue les principales d´
ecouvertes scientiques de ces travaux et montrons
comment ce processus modie la science des forˆ
ets tropicales. Notre approche principale consiste `
a relier les
initiatives de base `
a long terme `
a des protocoles standardis´
es et une gestion de donn´
ees an de g´
en´
erer des
r´
esultats solides `
a grande ´
echelle. En reliant les chercheurs tropicaux et en ´
elevant leur statut, notre mod`
ele de
ForestPlots.net et al.
r´
eseau de recherche sociale reconnaît le rˆ
ole cl´
e de l’auteur des donn´
ees dans la d´
ecouverte scientique. Conçus
en 1999 avec RAINFOR (Am´
erique du Sud), nos r´
eseaux de parcelles permanentes ont ´
et´
e adapt´
es `
a l’Afrique
(AfriTRON) et `
a l’Asie du Sud-Est (T-FORCES) et largement imit´
es dans le monde entier. Ces multiples initiatives
sont d´
esormais int´
egr´
ees via l’infrastructure ForestPlots.net, qui relie des coll`
egues de 54 pays `
a travers 24
r´
eseaux de parcelles. Ensemble, elles transforment la compr´
ehension des forˆ
ets tropicales et de leur rˆ
ole bio-
sph´
erique. Ensemble, nous avons d´
ecouvert comment, où et pourquoi le carbone forestier et la biodiversit´
e
r´
eagissent au changement climatique, et comment ils y r´
eagissent. Cette collaboration pan-tropicale `
a long terme
a r´
ev´
el´
e un important puits de carbone `
a long terme et ses tendances, tout en mettant en ´
evidence les facteurs les
plus importants, les processus forestiers qui sont affect´
es, les endroits où ils changent, les d´
ecalages et les
r´
eactions futures probables des forˆ
ets tropicales `
a mesure que le climat continue de changer. En tirant parti d’une
technologie remarquablement ancienne, les r´
eseaux de parcelles d´
eclenchent une r´
evolution tr`
es moderne dans
la science des forˆ
ets tropicales. `
A l’avenir, l’humanit´
e pourra grandement b´
en´
ecier du soutien des communaut´
es
de base qui sont maintenant collectivement capables de g´
en´
erer une compr´
ehension unique et `
a long terme des
forˆ
ets les plus pr´
ecieuses de la Terre.
Abstrak: Hutan tropika adalah di antara ekosistem yang paling produktif dan mempunyai kepelbagaian bio-
diversiti yang tinggi di seluruh dunia. Walaupun pemahaman mengenai hutan tropika amat penting untuk masa
depan kita, usaha-usaha untuk mengkaji dan mengawas hutah-hutan tersebut baru sekarang menjadi lebih
diperhubungkan. Perangkaian adalah sangat penting untuk mencari jawapan kepada soalan-soalan yang men-
jangkaui sempadan dan batasan agensi pendanaan. Di sini kami menunjukkan bagaimana sebuah komuniti
global bertindak balas terhadap cabaran penyelidikan ekosistem tropika melalui penglibatan pelbagai kumpulan
yang mengukur hutan secara pokok demi pokok dalam beribu-ribu plot jangka panjang. Kami meninjau semula
penemuan saintik utama daripada kerja ini dan menunjukkan bagaimana proses ini sedang mengubah bidang
sains hutan tropika. Teras pendekatan kami memberi tumpuan terhadap penghubungan inisiatif akar umbi
jangka panjang dengan protokol standar serta pengurusan data untuk mendapatkan hasil skala besar yang
kukuh. Dengan menghubungkan penyelidik-penyelidik tropika dan meningkatkan status mereka, model Rang-
kaian Penyelidikan Sosial kami mengiktiraf kepentingan peranan pengasas data dalam penemuan saintik.
Bermula dengan pengasasan RAINFOR (Amerika Selatan) pada tahun 1999, rangkaian-rangkaian plot kekal kami
kemudian disesuaikan untuk Afrika (AfriTRON) dan Asia Tenggara (T-FORCES) dan selanjutnya telah banyak
dicontohi di seluruh dunia. Kini, inisiatif-inisiatif tersebut disepadukan melalui infrastruktur siber ForestPlots.
net yang menghubungkan rakan sekerja dari 54 negara di 24 buah rangkaian plot. Secara kolektif, rangkaian ini
sedang mengubah pemahaman tentang hutan tropika dan peranannya dalam biosfera. Kami telah bekerjasama
untuk menemukan bagaimana, di mana dan mengapa karbon serta biodiversiti hutan bertindak balas terhadap
perubahan iklim dan juga bagaimana mereka saling bermaklum balas. Kolaborasi pan-tropika jangka panjang ini
telah mendedahkan sebuah sinki karbon jangka panjang serta arah alirannya dan juga menjelaskan pemandu-
pemandu perubahan yang terpenting, di mana dan bagaimana proses hutan terjejas, masa susul yang ada dan
kemungkinan tindakbalas hutan tropika pada perubahan iklim secara berterusan di masa depan. Dengan
memanfaatkan pendekatan lama, rangkaian plot sedang menyalakan revolusi yang amat moden dalam sains
hutan tropika. Pada masa akan datang, manusia sejagat akan banyak mendapat manfaat jika memupuk
komuniti-komuniti akar umbi yang kini berkemampuan secara kolektif menghasilkan pemahaman unik dan
jangka panjang mengenai hutan-hutan yang paling berharga di dunia.
1. Introduction
As the most diverse and productive ecosystems on Earth, tropical
forests play essential roles in the carbon and water cycles and mainte-
nance of global biodiversity. Tropical forest lands are also home to more
than a billion people and thousands of cultures. Having rst provided
the environments and germplasm that sustained foragers and farmers
since the earliest days of humanity, today they underpin a large fraction
of our globalized diet and intense demand for water, food and clean air.
They also affect our health in multiple ways, providing rich pharma-
copoeias to traditional and modern societies, and capable of changing
the course of history when pandemic zoonotic pathogens emerge as
forests and wildlife are exploited. Tropical forests are also critical to
determining the degree and impact of anthropogenic climate change.
Because of their extent, carbon density and productivity, they may both
slow global heating by absorbing carbon into their biomass and soils, or
accelerate it as deforestation and high temperatures damage forests and
release carbon to the atmosphere.
Tropical carbon and biodiversity are therefore critical targets for
environmental measurement and monitoring. While vital to our past and
future, efforts to measure and monitor them have until recently been
localised and largely disconnected. Although aspects of their ecology
can be sensed remotely, on-the-ground, tree-by-tree measurement is
essential. Indeed ground measurements are irreplaceable – whether to
address a plethora of ecological questions (e.g., Wright, 2021), inform
and validate ecosystem models (e.g., Malhi et al., 2021), or assist with
interpreting remotely acquired data (e.g., Chave et al., 2019; Duncanson
et al., 2019; Phillips et al., 2019). Yet the very features that enhance
tropical forests’ ecological value, such as remoteness, diversity and high
rainfall, make eldwork challenging. Tropical forest science and scien-
tists from forest-rich countries are often under-resourced and academi-
cally marginalised. Often colonized from afar and distant from economic
centres, tropical nature and many who explore it remain peripheral to
national and global academic and political priorities.
The focus of this paper is specically about the power of new
collaborative networks to transform tropical forest science – what we do,
how we do it, and eventually who does it - to understand tropical forest
functioning and dynamics over large temporal and spatial scales.
Conceived and funded starting in South America in 1999 (RAINFOR,
Malhi et al., 2002) and later adapted to Africa (AfriTRON, Lewis et al.,
2009) and Southeast Asia (T-FORCES, Qie et al., 2017) our approach
encourages international grassroots initiatives and links them
with standardized eld methods and data management. Now, with
ForestPlots.net (L´
opez-Gonzalez et al., 2011, 2015) we support multiple
networks with cyber-infrastructure that enables tropical scientists to do
together what was previously impossible alone. Providing tools to
ensure tropical scientists can manage, share and analyse their data
themselves, ForestPlots.net is a global platform where data originators
are in control and free to collaborate, support, or lead as much as they
like. However, while much has been accomplished the wider challenges
still run deep. Our aim of supporting the best possible science within a
model of equitable access to data and other resources remains as much
ForestPlots.net et al.
an aspiration as a claim of achievements already made.
Here we rst review how the continental networks and ForestPlots.net
emerged, in terms of collaborators, institutions, people and plots. Next we
focus on key scientic achievements of the combined networks, including
a comprehensive understanding of the variation in biomass carbon stock,
growth rates, and carbon residence time among continents. We also review
multiple discoveries concerning large-scale changes over time, with in-
sights emerging from highly distributed permanent plots that have trans-
formed our understanding of the role that tropical forests play in the
biosphere. Finally, we return to the challenges of building and sustaining
long-term science networks in the tropics and outline key priorities for the
future.
2. Network development
Tropical research plots that tag, measure, identify and follow forests
tree-by-tree have existed for decades. They long precede any continental
or global network, but no plot survives since before 1939 and few pre-
date 1970. The earliest efforts were closely connected to the imperial
and post-imperial projects of European nations. As such, these were
largely motivated by questions of timber inventory and wood produc-
tion, and only later diversity and wider ecological questions. The very
rst permanent sample plots we are aware of in the tropics were
installed in 1857 by the German forester Brandis, who worked for the
British in Burma (now Myanmar) and later in other parts of India
(Dawkins and Philip, 1998). In India a few extant Forest Department
plots date to 1939 (Pomeroy et al., 2003). Important early work in
Southeast Asia included plots installed by Don Nicholson and J.E.D.
Fox in the 1950s through to the 1970s, as well as Peter Ashton since the
1960s and John Proctor since the 1970s. In Africa, early permanent
plots include those installed by William Eggeling in Uganda in the
1930s. Among plots surviving today are one in Mpanga Forest, Uganda,
set up by Alan Hamilton in 1968, and those established by Mike Swaine
in Ghana and Hans Woell in Liberia in the 1970s. Later plots were
established by Jan Reistma and Lee White (Gabon), Bonaventure Sonk´
e
(Cameroon), Ko Affum Baffoe (Ghana), and Henri-F´
elix Maître and
colleagues (Gabon, Congo, C.A.R.). In Australia, North Queensland saw
the rst plot sampling, for timber, in the 1930s, with many sites from the
1970s still maintained today by the national science agency (CSIRO).
Separately Joe Connell, co-originator of the inuential Janzen-Connell
hypothesis, installed and expanded long-term ecological plots in 1963.
In the tropical Americas, T.A.W. Davis and Paul Richards installed
ecological plots in Guyana in the 1930s (Davis and Richards, 1933) but
these do not survive, while Frank Wadsworth established
long-term plots in Puerto Rico’s subtropical forests starting in 1943
(e.g. Drew et al., 2009). In Suriname, Schulz and colleagues established
silvicultural studies in the 1950s and 60s that were used to design the
CELOS Management System (Werger, 2011). Neotropical ecological
plots that persist today include many in Venezuela by Jean-Pierre
Veillon in the 1950s, 60s and 70s (Vilanova et al., 2018) and Rafael
Herrera, Ernesto Medina and colleagues in the 1970s, as well as a few in
Brazilian Amazonia by Jo˜
ao Murça Pires, H. Dobzhansky and G.A. Black
and later Ghillean Prance, and several in Costa Rica since 1969 by Diana
and Milton Lieberman. Elsewhere, Alwyn Gentry, John Terborgh, Terry
Erwin, Gary Hartshorn, David Neill and Rodolfo V´
asquez set up the rst
long-term plots in western Amazon in the late 1970s and 80s (Gentry,
1988a; Monteagudo Mendoza et al., 2020). Eastern and central Amazon
plots survive established by Samuel Almeida, Ima Vieira and Rafael
Salom˜
ao in Par´
a (Salom˜
ao, 1991; Pires and Salom˜
ao, 2000), Tom
Lovejoy, Niro Higuchi and colleagues near Manaus, Henri-F´
elix Maître
in French Guiana, and Marcelo Nascimento and colleagues in Roraima.
The earliest extant plots in southern Amazonia originated with Tim
Killeen, Luzmila Arroyo, Beatriz Marimon and Jos´
e Roberto Rodrigues.
The rst long-term tropical large plot was established in Costa Rica
(Hubbell, 1979), which represented a separate innovation that
permitted plot-level analysis of multi-species demography, followed
soon after by the rst 50-ha plot in Panama (Hubbell and Foster, 1983;
Wright, 2021) and later developments by the Smithsonian Institution
and the ForestGEO network (e.g. Anderson-Teixeira et al., 2015).
RAINFOR (Red Amaz´
onica de Inventarios Forestales) is the rst in-
ternational tropical forest network encompassing highly distributed
long-term plots. RAINFOR was inspired by Alwyn Gentry, a virtuoso
tropical botanist who established the rst globally standardized oristic
inventories. In the 1970s Gentry developed a 0.1-ha sampling design to
rapidly inventory diversity in species-rich tropical forests, capturing all
stems ≥2.5 cm diameter. He and his colleagues applied it throughout the
tropical Americas as well as parts of Africa, India, Southeast Asia, Aus-
tralasia, and some northern and southern temperate forests. By the time
of his untimely death at the age of 48 in 1993, Gentry had completed 226
of these samples, comprising an inventory of thousands of tree and liana
species including many new to science. His legacy lives on in multiple
ways. After studying with Walter Lewis and recruited by Peter Raven in
the early 1970s, Gentry was a key gure in the Missouri Botanical
Garden’s golden age of tropical botany. He collected >80,000 plant
specimens, approximately half of which are tropical trees and lianas. He
pioneered a new approach to the challenge of identifying plants in the
world’s most diverse forests (Gentry and Vasquez, 1993) that has
inspired generations of botanists throughout Latin America. Perhaps
most importantly, it was Gentry who embodied the ambition of
combining efcient ecological sampling with high-quality identica-
tions and replicating these to create highly distributed measurements of
the world’s forests (e.g. Gentry, 1988b; Clinebell et al., 1995; Phillips
and Miller, 2002; Phillips and Raven, 1997). He also established per-
manent plots (Gentry, 1988a) that feature in the rst continental and
pan-tropical analyses of forest carbon and dynamics (Phillips and
Gentry, 1994; Phillips et al., 1994; Phillips et al., 1998), which in turn
led to the creation of RAINFOR (Malhi et al., 2002; L´
opez-Gonz´
alez and
Phillips, 2012) and its protocols (e.g. Phillips et al., 2002). Originating in
1999 from a small nucleus of researchers and plots and supported by EU
funding to Brazil’s LBA initiative and UK scientists, RAINFOR grew to
tackle the challenge of analysing Amazonian forests and climate re-
sponses tree-by-tree from the ground up. By bringing different groups
together RAINFOR facilitated the development of long-term interna-
tional collaborations to measure and understand not only forest dy-
namics and diversity but also biogeochemistry and carbon uxes.
While RAINFOR has grown steadily, other plot networks later
emerged with complementary foci in South America. Some are daughter
initiatives to RAINFOR, others were formed separately, but most share a
similar ethos and strongly overlapping protocols. To the extent that they
can be combined together these networks represent an impressive Ob-
servatory for Neotropical Forests. Below we report key information
about many vibrant networks worldwide that specically contribute to
ForestPlots.net (Table 1), while here we briey enumerate national
and international neotropical networks, the majority of which
ForestPlots.net supports. These include (with dates when plots were
censused or consolidated as a network) Tropical Ecology Assessment
and Monitoring (TEAM, 2002), Amazon Tree Diversity Network (ATDN,
2003; ter Steege et al., 2003), Programa de Pesquisa em Biodiversidade
(PPBio, 2004, Brazil), Red Colombiana de Monitoreo de los Bosques
(COL-TREE, 2004), Global Ecosystems Monitoring (GEM, 2010;
Malhi et al., 2021), Latin American Seasonally Dry Tropical Forest
Network (DryFlor, 2012), Red de Investigaci´
on y Monitoreo del Bosque
Seco Tropical en Colombia (Red BST-Col, 2014), Secondary Forest
Network (2ndFOR, 2015), Peru Monitoring Network (MonANPerú,
2017), sANDES (Tree Diversity, Composition and Carbon in Andean
Montane Forests, 2019), and Red de Bosques Andinos (RBA, 2020), as
well as global networks and meta-networks including ForestGEO
(Anderson-Teixeira et al., 2015), GFBI (Steidinger et al., 2019), sPlot
(Bruelheide et al., 2019), FOS (Schepaschenko et al., 2019) and TmFO in
logged forests (Sist et al., 2015). Each of these has notable achievements
of their own and at the time of writing this article in 2020 almost all have
active research programmes.
ForestPlots.net et al.
Table 1
Networks contributing to ForestPlots.net.
We report the 24 international, national, and regional plot networks contributing to and supported by ForestPlots.net in 2020, in order of date of afliation. Note that
some plots contribute to more than one network, in some cases the plots managed at ForestPlots.net are fewer than the total number of plots of the network, while
others are not ‘networked’ but managed by individual researchers. Hence, cross-network totals do not correspond precisely to the number of plots managed. We
include 20 tropical networks with multi-census plots plus four large-scale oristic-focussed scientic networks (ATDN, CAO, sANDES, RedGentry) that work exclu-
sively with single-census data. All numbers compiled September 2020. As an open collaborative project ForestPlots.net welcomes all contributors with carefully-
managed plots.
Network
a
Geography Main
purposes
b
Joined
ForestPlot
s.net
Initiated [e.g.
plots censused
as a network]
First census
in Forest
Plots.net
n (plots in
ForestPlot
s.net)
n (plots
recensued)
Modal plot Mean
size
(ha)
Mean
(maximum)
years monitored
RAINFOR South America:
tropical forests
B,D,F,M,T,
V
2000 2000 1961 593 427 1-ha,
>10 cm d
0.8 15 (56)
DBTV Venezuela:
tropical forests
B,D,M,T 2004 1956 1961 48 48 0.25-ha,
>10 cm d
0.25 30 (55)
COL-TREE Colombia B,D,F,H,M,
R,V
2004 2004 1992 61 55 1-ha,
>10 cm d
0.8 9 (25)
TROBIT Pantropical:
forest-savanna
transition
B,D,F,H,R,T 2006 2006 2006 58 49 1-ha,
>10 cm d
1 12
AfriTRON Africa: tropical
forests
B,D,F,M 2009 2009 1939 575 407 1-ha,
>10 cm d
0.9 11 (69)
ABERG Peru Andes:
Kos˜
nipata Valley
B,D,F,M,P,T 2011 2011 2003 23 23 1-ha,
>10 cm d
1 12 (16)
T-FORCES Southeast Asia:
tropical forests
B,D,F,H,M 2012 2012 1958 95 71 1-ha,
>10 cm d
1.3 22 (56)
GEM Worldwide D,H,M,P,R,
T
2012 2010 2010 53 45 1-ha,
>10 cm d
0.8 5 (16)
PELD-TRAN Brazil: Amazon-
Cerrado transition
B,D,F,H,M,
R,T,V
2012 2010 1996 48 45 1-ha,
>10 cm d
1 9 (22)
DRYFLOR Latin America and
Caribbean dry
forests
B,D,F,H,M,
R,T,V
2013 2012 2007 39 8 0.5-ha,
>5 cm d
0.3 7 (8)
ATDN Amazonia:
tropical forests
F,V 2014 2003 1974 413 N/A 1-ha,
>10 cm d
1 N/A
PPBio Brazil: forests and
savanna
B,D,F,H,M,
T,V
2015 2004 2000 277 205 1-ha,
>10 cm d
c
0.9 7 (17)
BIOTA Brazil: S˜
ao Paulo
state, Atlantic
forests
B,D,F,H,M,
P,R,T,V
2016 2005 2005 20 18 1-ha,
>10 cm d
0.9 11 (14)
FATE Brazil: Amazon
re-impacted
B,D,H,M,R,
S,T
2016 2014 2009 57 38 0.25-ha,
>10 cm d
c
0.3 4 (10)
RAS Brazil: Para state B,D,F,H,M,
P,R,T,U,V
2016 2009 1999 256 59 0.25-ha,
>10 cm d
c
0.26 6 (20)
MonANPeru Peru B,D,F,H,M,
R,U,V
2017 2017 1974 128 103 1-ha,
>10 cm d
1 15 (43)
Nordeste Brazil: Caatinga
biome
B,D,F,H,M,
R,T
2017 2017 2017 33 3 0.5-ha,
>10 cm d
0.5 3
SEOSAW Southern Africa
woodlands
B,D,F,H,M,
R,S,T,U,V
2018 2018 2006 113 98 1-ha,
>5 cm d
0.5 9 (15)
Red BST-Col Colombia: dry
forests
B,D,F,H,M,
R,U,V
2018 2014 2014 11 1 1-ha,
>2.5 cm d
1 3 (3)
CAO Peru Amazon-
Andes
B,F,S,T,V 2019 2009 2009 276 N/A 0.28-ha,
>5 cm d
0.28 N/A
RedSPP Argentina:
subtropical
B,D,F,H,M,
R,V
2019 2019 1992 16 7 1-ha,
>10 cm d
1.4 10 (25)
RBA South America:
Andean forests
B,D,F,H,M,
R,V
2020 2012 1992 46 34 1-ha,
>10 cm d
1 11 (25)
sANDES South America:
Andean forests
B,F,V 2020 2019 2003 191 N/A 0.1-ha,
>2.5 cm d
0.4 N/A
AfriMont Africa: tropical
montane forests
B,H,M,U,V 2020 2020 1939 105 N/A 1-ha,
>10 cm d
0.6 10 (69)
RedGentry South America:
Amazon forests
F,V 2020 2020 1983 350 N/A 0.1-ha,
>2.5 cm d
0.2 N/A
a
Full Network Names:
Red Amaz´
onica de Inventarios Forestales (RAINFOR)
Din´
amica y crecimiento del Bosque Tropical Venezolano (DBTV)
Tropical Biomes in Transition (TROBIT)
African Tropical Rainforest Observation Network (AfriTRON)
Andes Biodiversity and Ecosystem Research Group (ABERG)
Tropical Forests in the Changing Earth System (T-FORCES)
Red Colombiana de Monitoreo de los Bosques (COL-TREE)
Global Ecosystems Monitoring (GEM)
Programa Ecol´
ogico de Longa Duraç˜
ao (PELD-TRAN)
Amazon Tree Diversity Network (ATDN)
Programa de Pesquisa em Biodiversidade (PPBio)
ForestPlots.net et al.
In Africa, our early networking focussed on assessing whether there
were similar patterns of changes in carbon stocks as observed in South
American forests and the causes of such changes. Efforts began in 2001
to recensus many of the earlier plots installed in post-independence
Africa (UK funding to O. Phillips, Y. Malhi and S. Lewis), which were
later formalised as the African Tropical Rainforest Observation Network
(AfriTRON; Lewis et al., 2009) and catalysed a tripling of the African
multi-census plot dataset over the last decade (Hubau et al., 2020).
These span 12 African countries with moist forests from Sierra Leone in
the west to Tanzania in the east. Like RAINFOR in Amazonia, AfriTRON
pools expertise and data to tackle long-term, large-scale questions
relating to the ecology and biogeochemistry of tropical forests. Networks
sharing a similar ethos with programmes in Africa now include TEAM,
DynAfFor (Gourlet-Fleury et al., 2013), TmFO and ForestGEO. Recently,
the SEOSAW (SEOSAW partnership, 2020) and AfriMont networks have
also been established, extending long-term plots into the extensive
southern woodlands and savannas and Africa’s distinctive montane
forests.
Our work in Southeast Asia began in 2001 to assess forest carbon
balance and later developed into a network once Lan Qie undertook
eldwork and networking. European Research Council investment (T-
FORCES 2012 grant to Phillips, Malhi and Lewis) enabled intensive
Fig. 1. Current extent of ForestPlots.net.
Top: Pantropical plot sampling density per 2.5 degree square with the 4062 multiple- and single-inventory plots hosted at ForestPlots.net. These plots contribute to 24
networks including RAINFOR, AfriTRON, T-FORCES, ATDN, BIOTA, COL-TREE, FATE, GEM, Nordeste, PELD, PPBio, RAS, RBA and SEOSAW. Forest cover based on
the Global Land Cover 2000 database (JRC, 2003) with tree cover categories: broad-leaved evergreen; mixed leaf type; and regularly ooded. Our plots also extend
into neotropical and African savannas; Bottom: The same plot sampling but displayed at higher-resolution (1-degree grid cells) for each focal continent, South
America, Africa, and Southeast Asia and Australia.
Programa de Pesquisas em Caracterizaç˜
ao, Conservaç˜
ao e Uso Sustent´
avel da Biodiversidade (BIOTA)
Fire-Associated Transient Emissions (FATE)
Rede Amazˆ
onia Sustent´
avel (RAS)
Monitoreo de las Areas Naturales Protegidos del Peru (MonANPeru)
Projeto Nordeste (Nordeste)
A Socio-Ecological Observatory for Southern African Woodlands (SEOSAW)
Red de Investigaci´
on y Monitoreo del Bosque Seco Tropical en Colombia (Red BST-Col)
Carnegie Airborne Observatory (CAO)
Red Subtropical de Parcelas Permanentes (RedSPP)
Red de Bosques Andinos (RBA)
Tree Diversity, Composition and Carbon in Andean Montane Forests (sANDES)
African tropical Montane forest network (AfriMont)
Red de parcelas Gentry (RedGentry)
b
Purpose: Biomass; Dynamics (mortality, recruitment, growth); Floristic composition; Human-impacts (re, logging, fragmentation); Monitoring carbon storage,
sink, change; Productivity and carbon-cycle; Recovery and restoration, Remote-Sensing calibration/validation; Traits; Sustainable Use; DiVersity.
c
With nested sub-plots for smaller stems.
ForestPlots.net et al.
campaigns to develop long-term plot networking in Borneo (Qie et al.,
2017), and supported African recensuses (Hubau et al., 2020). While
smaller than its Amazonian and African counterparts, the Asian network
builds on plots installed by a number of foresters and botanists as long as
60 years ago. Critically, RAINFOR, AfriTRON, T-FORCES and TmFO use
the same eld and analytical protocols.
How can we combine the different strengths of these and other ini-
tiatives to maximise their impact on science and society? To achieve this
requires shared data management tools and horizontal organisational
structures that foster leadership by tropical scientists. Our plot data
management scheme was originally conceived in 2000 as a desktop
database to support RAINFOR analyses of spatial variation in wood
density, biomass, productivity, and changes in biomass over time (Baker
et al., 2004a, 2004b; Malhi et al., 2004). This was expanded to draw
together inventory data from >100 sites in Amazonia and then African
forest plots to include some of the longest running monitoring sites
worldwide (Peacock et al., 2007).
Since 2009 we have developed a Structured Query Language web
application with sophisticated programming, providing a one-stop
platform to a growing global community of contributors and users
(L´
opez-Gonzalez et al., 2011). Now, ForestPlots.net supplies ecological
informatics to colleagues in scientist-led networks from 54 countries
working across 44 tropical nations (Fig. 1). Key advances in this plat-
form include the ability to manage complex time-series data, track
species linked to high-quality botanical records, and analyse records
with common BiomasaFP R-language protocols (L´
opez-Gonzalez et al.,
2015). While focussed on species identity, tree growth, mortality and
carbon dynamics, ForestPlots.net encompasses many related forest at-
tributes including lianas, soils, and plant traits.
At their heart, long-term plots are an intensely human enterprise and
so we also document the personal contributions to plot establishment
and continued monitoring. By tracking who did what, and when, we also
Fig. 2. Growth of pan-tropical forest monitoring
since the mid-twentieth-century.
Top: Plot-censuses curated at ForestPlots.net by
date of census.
Bottom: Cumulative number of contributors to
ForestPlots.net by date of rst recorded eld-
work. Growth was slow following the rst census
in 1939, only reaching 100 censuses by 1969.
For early censuses, records of eld team
personnel and leaders are often sparse or absent.
Note that ‘contributors’ are dened inclusively
to reect members of indigenous communities,
protected area guards, parataxonomists, stu-
dents, and technicians, as well as principal in-
vestigators, botanists, and other specialists.
ForestPlots.net et al.
honour the inter-generational aspect of plots that allows modern ana-
lysts to stand on the shoulders of giants. With ForestPlots.net
data contributors retain control and are able to manage, share and
analyse their records using a common toolset. If new projects requesting
to use their data are proposed they can agree to collaborate, or not, as
they wish. Contributors often propose their own multi-site projects.
ForestPlots.net can provide DOIs to datasets, further ensuring that
contributors are properly acknowledged. Developing this functionality
has supported a surge in multi-site and multi-national analyses that are
increasingly initiated by scientists from the tropics, gradually
supplanting the traditional model where researchers from the Global
North lead. In sum, ForestPlots.net enables the level of control and
collaboration that individual researchers wish for while also promoting
network and multi-network integration. In turn, this is empowering data
owners and networks and helping to transform the face of tropical
ecological science.
The networks and ForestPlots share a 20-year history, but as we have
seen the history of plot monitoring is much longer. The rst recorded
census in ForestPlots.net dates from 1939 in Budongo, Uganda. Forty
years later, 676 censuses had been completed from 90 plots, but since
1979 eldwork has accelerated greatly with >10,000 censuses
completed across 4000 plots by 2020 (Fig. 2a). This acceleration is re-
ected by the growing community of contributors, which by 2020 had
reached 2000 individuals (Fig. 2b). ForestPlots.net itself has grown
steadily both in terms of censuses uploaded and in outputs (Fig. 3). The
neotropics dominate much of this inventory and monitoring effort as
well as the growth of ForestPlots.net in particular, but contributions
from Africa and other continents are increasing (Figs. 2, 3). Scientic
outputs emerging from this collective effort have always spanned local
to global scales but now have an increasingly pan-tropical theme
(Fig. 3b).
3. Environmental representation
While it is not possible to intensively sample the whole tropical forest
extent, in practice RAINFOR, AfriTRON and T-FORCES have managed to
cover almost the entire climatic and geographic space across the humid
tropics with permanent plots (Fig. 4a) as well as extensively sample the
Fig. 3. Growth of ForestPlots.net and its
contributing networks since 2000.
Top: Cumulative upload of unique plot censuses
to ForestPlots.net by date of upload (pre-2009
uploads to pre-internet versions allocated evenly
back to network beginnings);
Bottom: Cumulative peer-reviewed scientic ar-
ticles based on network plots, excluding
research based on single-plot studies.
ForestPlots.net et al.
Fig. 4. Network coverage of geographical
and climate space.
Analyses include >1500 permanent plots
managed at ForestPlots.net. (a) Top panels:
(1) Geographic distance between multi-
census plots across the humid tropical forest
biome; and (2) Minimum climate dissimi-
larity (Euclidean distance on variables scaled
by their standard deviation, accounting for
mean annual temperature, temperature sea-
sonality, mean annual precipitation and pre-
cipitation seasonality), where for each cell
environmental distance represents how dis-
similar a location is to the most climatically
similar plot in the network. Note that some
poorly sampled areas are mostly deforested,
such as Central America, Madagascar, and
much of tropical South and Southeast Asia.
The baseline map depicts WWF terrestrial
ecoregions (Olson et al., 2001). (b) Middle
panel: Tropical plots displayed in global
biome space (Whittaker diagram), showing
the main concentration of plots from lowland
wet through to moist forests and savanna,
with some samples in cooler montane cli-
mates. (c) Lower panels: Plots displayed
within tropical humid and sub-humid climate
space, with plots displayed colour-coded by
continent (see Fig. 2) and symbol size corre-
sponding to total census effort. Note the
important differences in baseline climatic
conditions between continents.
ForestPlots.net et al.
biome space of the terrestrial tropics except for semi-arid biomes
(Fig. 4b). Within each continent coverage has been focused on the moist
tropical lowlands with sampling extending into montane and drier forest
systems most effectively in South America (Fig. 4c). Plots also cover the
complex edaphic variation present in Amazonia (Quesada et al., 2012)
where they encompass landscape-level variability within old-growth
forests (Anderson et al., 2009, 2010). This effective representation of
structurally intact moist forests provides good support for large-scale
inferences from what is, inevitably, a limited sample of the domain. It
is important to note that many tropical countries lack statistical in-
ventories of forests, let alone long-term monitoring or historical base-
lines, so research plots ll critical gaps in global and national
observations.
Yet signicant work remains to increase representativeness, better
understand impacts of geological and edaphic variation, and expand
sampling in remote areas especially in parts of Amazonia, the central
Congo Basin, and New Guinea (c.f. Brearley et al., 2019, Fig. 4 below).
Fuller environmental coverage can help networks address challenges
such as monitoring of protected area effectiveness (Baker et al., 2020)
and providing calibration-validation of Earth Observation space-borne
sensors (Chave et al., 2019). Beyond the lowland humid tropics, spe-
cial effort is also needed for long-term, ground-based monitoring in
particular environments. Expansion is especially required for: (i) sec-
ondary forests and those impacted by disturbance events such as log-
ging, fragmentation, and wildres (e.g. Chazdon et al., 2016; Elias et al.,
2020; Villela et al., 2006); (ii) montane forests, which harbour excep-
tional concentrations of endemism and are at great risk of biodiversity
loss due to deforestation and climate change and therefore represent
urgent conservation opportunities (e.g. Malizia et al., 2020); (iii) Asian
dry forests, and (iv) the wider extent of tropical dry forest and savanna
biomes, which are home to distinctive biotas and signicant carbon
stocks of their own (DRYFLOR, 2016; Norden et al., 2020; Pennington
et al., 2018). ForestPlots.net partner groups are expanding research and
monitoring in such critical areas beyond the structurally intact lowland
forests that have been the main focus of RAINFOR and AfriTRON.
4. Discovery: forest ecology across the tropical continents
RAINFOR, AfriTRON and T-FORCES plots have generated ecological
and biogeographical insights that have only been achievable via large-
scale collaboration. RAINFOR has revealed that Amazonian forests
differ substantially from one another, even those that share essentially
identical climates. For example, basal-area weighted wood density of
northeastern forests is 50% greater than that of southern and western
forests. This reects oristic differences (Baker et al., 2004a, 2009;
Fyllas et al., 2009; ter Steege et al., 2006; Honorio Coronado et al., 2009;
Pati˜
no et al., 2009), which, in turn, are associated with large differences
in forest dynamics. Stem turnover is twice as fast in the west and south as
the east (Phillips et al., 2004) due to younger soils with poorer structure
providing less rooting support (Quesada et al., 2012; Schietti et al.,
2016) and in spite of only modest productivity differences (Malhi et al.,
2004, 2014a). In contrast, biomass in north-eastern Amazonia is higher
than elsewhere due to the reduced mortality risk and hence bigger trees
and denser wood (Baker et al., 2004a, Malhi et al., 2006, Marimon et al.,
2014, Pallqui et al., 2014, Johnson et al., 2016, Alvarez-Davila et al.,
2017, Phillips et al., 2019).
In Africa, AfriTRON plots also show that species-driven differences in
wood density prevail at large scales. In mature forests, soil-related
compositional differences cause signicant variation in basal-area
weighted wood density. Forests on younger and more fertile acrisols
and cambisols have 10 and 20% lighter wood than those on arenosols
and histosols, respectively (Lewis et al., 2013). Similarly to Amazonia,
African forests growing on older, less fertile soils have higher biomass
(Lewis et al., 2013). Local and regional variation in soils and forest at-
tributes are important within both continents but the key difference is
that only Amazonia has clear continental-scale gradients in wood
density, due to the powerful inuence of Andean orogeny in the west.
This leads to young, geologically dynamic landscapes with fertile, less-
developed soils, inuencing speciation, immigration and extinction,
and contrasts with the ancient, stable Brazilian and Guianan Shields of
the east.
Large-scale analysis thus reveals how soils and species help control
the carbon that tropical forests store. This has implications for moni-
toring carbon stocks using remotely-sensed data. In tropical forests
neither soil nor tree composition is easily perceived from space. For
example, RAINFOR plots show that LiDAR-derived biomass estimates of
Amazonian forests are problematic because they do not perceive the
critical large-scale oristic gradients (Mitchard et al., 2014). Accounting
for such limitations by relating plot-derived woody density and allom-
etry to LiDAR sampling shows that plots greatly improve biomass maps
(Mitchard et al., 2014; Avitabile et al., 2016). Thus the role of soils and
species composition in affecting biomass carbon is a key reason why
ground data are essential for mapping forests (Chave et al., 2019). While
Earth Observation has huge benets in terms of spatial coverage and
frequent updates, the incorporation of plot-derived compositional data
greatly improves our understanding of carbon storage patterns over
large scales.
When networks using the same protocols are combined it is also
possible to discover and explore variation between continents too.
Common protocols have revealed major pan-tropical variation in ver-
tical structure, including tree height and height-diameter allometry
(Feldpausch et al., 2011) which have impacts on biomass (Banin et al.,
2012; Feldpausch et al., 2012; Sullivan et al., 2018). African forests
average one-third higher biomass per unit area than Amazon forests
(Lewis et al., 2013), yet have roughly one-third fewer stems >10 cm
diameter per unit area. This may be driven by systematically lower tree
mortality in these forests (Hubau et al., 2020; Sullivan et al., 2020).
Similarly, comparing climatically and edaphically similar forests in
parts of Borneo with northwest Amazonia reveals that Bornean forests
produce much more wood, with trees growing up to 50% more rapidly
than those of Amazonia. This suggests that differences in phylogenetic
Fig. 5. Pantropical forest carbon storage is independent of species richness.
There are no clear within-continent or pantropical relationships between car-
bon stocks and tree species richness per hectare in structurally intact old-
growth tropical forests.
Figure adapted from Sullivan et al. (2017).
ForestPlots.net et al.
composition of tree communities, especially the dominance of the
dipterocarp family in tropical Asia (Corlett and Primack, 2011), deter-
mine the efciency with which atmospheric carbon is converted to
woody carbon (Banin et al., 2014).
Tree species composition and dominance strongly control forest
function within continents too. For example, a recent RAINFOR study
discovered that Amazon woody productivity is enhanced in more
phylogenetically diverse forests (Coelho de Souza et al., 2019). Yet while
Amazonian forests are very diverse, remarkably few species dominate in
terms of stems (ter Steege et al., 2013, research led by the ATDN
network), while biomass stocks and woody productivity are dominated
by a different set of species (Fauset et al., 2015, RAINFOR network).
Evidence also suggests that some of these ‘hyperdominants’ may have
been long favoured by indigenous people as part of wider human in-
uences on old-growth Amazon forests (Levis et al., 2017; Oliveira et al.,
2020). These and other studies show that identity matters. Dominant
species and their evolutionary history thus affect forest ecology and
forest values, whether in terms of storing carbon, converting solar en-
ergy into wood or sustaining whole cultures.
These insights show that two of the dening challenges of the
twenty-rst century, climate change and biodiversity loss, are closely
linked. How then do we best devise conservation strategies to achieve
the targets of biodiversity protection and climate mitigation and adap-
tation? Can we rely for example on carbon conservation via schemes like
REDD+to protect tropical diversity too? The answers to these questions
depend on the relationship between diversity and carbon storage, but
assessing this has been challenging due to the scarcity of inventories in
which both carbon stocks and species identications have been reliably
quantied. By combining RAINFOR, AfriTRON and T-FORCES plots we
found that for tropical trees diversity‑carbon storage relationships
barely exist at all (Sullivan et al., 2017, Fig. 5). For example, South
America, the continent with the richest forests, actually stores the least
carbon per hectare, while within continents there is no association. In-
dependent data from the RAS network support this, showing that strong
carbon-biodiversity relationships are only found in disturbed and sec-
ondary forests but not old-growth (Ferreira et al., 2018). As mature
forests exhibit all possible combinations of tree diversity and carbon
stocks it is clear that both need to be explicitly considered to protect the
climate and biodiversity. In addition, long-term carbon storage is
threatened by defaunation of large-bodied frugivores, often essential for
dispersing large-seeded, heavy-wooded tree species (Peres et al., 2016).
We cannot simply focus on carbon and achieve biodiversity conserva-
tion, and vice versa.
When network data are combined surprisingly large and coherent
continental-level differences emerge (Fig. 6). African forests are
remarkably species-poor at the 1-ha scale whereas South American and
Asian forests are more than twice as rich on average, but also vary much
more in species richness and diversity. The very richest forests in the
world are located in parts of Western Amazonia, vindicating a claim by
Gentry (Gentry, 1988a, 1988b) from more than three decades ago. Af-
rican forests have many fewer stems than their Asian and South Amer-
ican counterparts, but South American forests have considerably less
biomass. In terms of carbon gains Borneo’s forests are outliers, being up
to twice as productive as other forests. Yet it is in South America where
woody carbon turns over fastest. Almost half the carbon in neotropical
trees has been replaced since 1970.
Overall these comparisons reveal remarkable differences between
the tropical forest continents that are not strongly driven by rainfall,
Fig. 6. Tropical continental macroecology.
Remarkable continental differences in species richness, stem density and carbon stocks emerge among lowland tropical moist forests when densely sampled plot
networks are combined. Graphics depict probability densities such that the whole area for each continent sums to 1. Note that the y-axis scale for each variable thus
varies depending on the range of the x-axis: for continents with larger variation in x, the probability density at any point along the y axis is correspondingly smaller.
Analysis adapted from Sullivan et al. (2017, 2020).
ForestPlots.net et al.
temperature or soil (Sullivan et al., 2020). The implication is that other
factors related to the evolutionary and historical happenstance of each
continent matter. We draw three higher level conclusions from this.
First, global-scale ecological modelling ignores biological composition at its
peril. Second, if there was ever any doubt, each continent clearly needs its
own robust research and monitoring programme. And third, each region
likely responds to climate change in its own, idiosyncratic way.
5. Discovery: tropical forest change
The single most signicant scientic impact of these multiple per-
manent plot networks has been to transform our understanding of how
tropical forests function in the Earth system.
As the most diverse and carbon-rich tropical biome, the fate of humid
tropical forests will impact the future of all life on Earth. Until quite
recently it was axiomatic that old-growth tropical forests are at equi-
librium when considered over sufciently large scales, and that any
changes observed at smaller scales are driven by natural disturbance-
recovery processes. However, large-scale imbalances observed in the
global carbon balance have cast doubt on this assumption (e.g. Taylor
and Lloyd, 1992). Over time, network analyses have helped to recast our
understanding of contemporary old-growth tropical forests as being
non-stationary systems. Their carbon, biodiversity and ecosystem pro-
cesses are now widely recognised as dynamic and continually responsive
to multiple anthropogenic drivers (e.g. Lewis et al., 2004b; Pan et al.,
2011; Malhi et al., 2014b; Levis et al., 2017; McDowell et al., 2018; Reis
et al., 2018). Key discoveries at this intersection between global change
science and forest ecology and biodiversity include:
(1) A pantropical increase in tree turnover rates, representing
the rst evidence for a widespread impact of global anthro-
pogenic change on old-growth tropical forests (Phillips and
Gentry, 1994). The nding that these forests were changing was
controversial at the time - let alone the inference that global
drivers were responsible - and contradicted established ecological
orthodoxy. The debate that ensued helped generate new ques-
tions and analyses (e.g. Sheil, 1996; Phillips, 1996; Phillips and
Sheil, 1997) and address potential biases (e.g. Sheil, 1995, Con-
dit, 1997, Lewis et al., 2004a, Gloor et al., 2009, Espirito-Santo
2014, Kohyama et al., 2019). A quarter of a century of research
since then has rejected the notion that ‘intact’ tropical forests are
unaffected by atmospheric changes and reinforced the central
concept that all tropical forests are being inuenced by a suite of
large-scale contemporary anthropogenic drivers.
(2) Biomass dynamics have also accelerated in Amazonia. In
parallel with the increases in stem dynamics, as RAINFOR grew it
became clear that carbon uxes via biomass growth and mortality
were also increasing. Moreover, the increased gains in stems
(recruitment) and biomass (woody productivity) clearly preceded
increases in stem and biomass losses (mortality) (Lewis et al.,
2004b, Phillips et al., 2004, 2008, Brienen et al., 2015, Nogueira
et al., 2019). The mechanism underlying this acceleration of
forest dynamics must therefore involve stimulated productivity
via increased resources for plant growth, rather than direct
stimulation of tree mortality such as by drought (Lewis et al.,
2004).
(3) The Amazon forest carbon sink. In conjunction with faster
growth and turnover, the biomass density of Amazonian forests
has increased (Phillips et al., 1998; Baker et al., 2004b; Pan et al.,
2011). Old-growth Amazonian forests have absorbed (net) at-
mospheric carbon for at least three decades now (Brienen et al.,
2015), providing a true “subsidy from nature” with ux magni-
tude matching or exceeding net losses from neotropical defores-
tation (Aragao et al., 2014; Gatti et al., 2014). Thus, monitoring
networks have shown that most Amazonian nations are on bal-
ance not net emitters of carbon (Espírito-Santo et al., 2014;
Phillips and Brienen, 2017). The location, magnitude and
persistence of this old-growth carbon sink has important impli-
cations for guiding approaches to meeting nationally differenti-
ated targets for controlling climate change (Vicu˜
na Mi˜
nano et al.,
2018).
(4) The African forest carbon sink. The AfriTRON network
discovered a long-term net biomass increase similar in magnitude
to that of the Amazon in the 1990s and early 2000s (Lewis et al.,
2009). The consistency of these results on a second continent
supports the idea that global drivers of change can affect even the
most remote forests. The fact that biomass is increasing across the
entire wood density spectrum of tree species implies that forests
are responding to increasing atmospheric CO
2
concentrations
(Lewis et al., 2009). The long-term increase in carbon stocks of
African forests was recently updated and conrmed, with three
times as many plots showing continued sink strength (Hubau
et al., 2020).
(5) The Pan-Tropical forest carbon sink. Once the T-FORCES
network allowed sufcient plot coverage across remaining Bor-
nean forest, a similar increase in aboveground biomass over
recent decades was revealed (Qie et al., 2017). Thus the three
continental networks discovered that old-growth tropical forests
as a whole have functioned as a long-term sink. Our ground
measurements revealed that more than one billion tonnes of
carbon were sequestered by tropical forests each year over the
1990s and early 2000s, i.e. half the terrestrial global carbon sink
(Pan et al., 2011) and sufcient to signicantly slow climate
change. The fact that the main blocs of remaining tropical forests
are en masse out-of-equilibrium and undergoing biomass in-
creases of similar magnitude implies a common global driver of
growth. Increasing atmospheric CO
2
is the most parsimonious
candidate and is consistent with predictions from rst principles
(e.g., Phillips and Gentry, 1994, Huntingford et al., 2013),
inference from CO
2
fertilization experiments (Terrer et al., 2019),
analyses of the global carbon budget (Ballantyne et al., 2012;
Gaubert et al., 2019), observed greening of forests unaffected by
land-use change (Piao et al., 2019), and recent plot analyses
showing a signicant role of CO
2
(Hubau et al., 2020).
(6) The Amazon sink is slowing. After 30 years of monitoring
Amazonian forests, the RAINFOR plots show that the rate of in-
crease in forest growth is declining. Tree mortality rates have
increased in some regions, leading to a slow decline in the
magnitude of the net biomass accumulation (Brienen et al., 2015;
Phillips and Brienen, 2017). The subsidy from nature provided by
tropical forests may be time-limited.
(7) Recent droughts in Amazonia have had large impacts. Long-
term plots monitored immediately before and soon after droughts
reveal that these forests can switch rapidly from being a major
sink to a source of carbon. Both the 2005 and 2010 Amazon
droughts had a net impact on the order of 1 Pg of carbon, driven
primarily by drought-induced mortality (Phillips et al., 2009,
Lewis et al., 2011; Doughty et al., 2015, Feldpausch et al., 2016).
RAINFOR and GEM have quantied the drought sensitivity of the
world’s biggest rainforest and found that the key process affected
was tree mortality rather than growth or photosynthesis. The
impact on the biomass carbon sink of the 2010 drought and non-
drought years matches independent inferences from measure-
ments of atmospheric [CO
2
] using aircraft (Gatti et al., 2014).
(8) The African and Amazon sinks have diverged. Thirty years of
monitoring AfriTRON plots show that African forests have
continued to function as a carbon sink, although the most
intensively monitored plots suggest that the sink may be
declining (Hubau et al., 2020). When analysed together with
RAINFOR data, within-plot changes over time reveal a common
set of drivers that suggest the sinks will decline, with African
forests lagging behind Amazonian forests by 15–20 years (Hubau
ForestPlots.net et al.
et al., 2020). Changes across both continents are best explained
by a combination of the positive effects of increasing CO
2
in
enhancing productivity and the negative effects of higher tem-
peratures and droughts in suppressing growth and accelerating
mortality, combined with the intrinsic properties of forests
themselves. The time-lag of the African sink saturation is due to
longer carbon residence times in African forests, so that mortality
catches up more slowly than in forests with faster turnover.
Amazonian forests are often harder hit because they are hotter
and can be drought-prone (Hubau et al., 2020). Together, the
pan-tropical plot networks have revealed long-term trends in
carbon storage and determined which drivers matter, which
processes are affected, where they are impacting, and what the
lags are.
(9) The future of the tropical forest carbon sink. Monitoring the
present and recent past of forest behaviour can also reveal likely
future scenarios as the climate continues to change. Our plot
networks provide two powerful and independent lines of evi-
dence. First, the long-term sensitivity to climate emerges from a
space-for-time analysis based on 813 plots across the Earth’s
tropical forests. This shows how maximum temperature and dry
season intensity combine to determine the equilibrium climate
controls on forest carbon, acting on productivity and mortality to
limit forest carbon storage in the long-term (Sullivan et al., 2020).
Forests exhibit remarkable thermal resilience under low amounts
of warming, but in the hottest forests (>32.2 ◦C max. temp.)
biomass carbon drops off rapidly. Most of the biome will exceed
this value with one further degree of warming (approximately
equivalent to a 2 ◦C increase above pre-industrial levels). Second,
analysing recent changes in productivity and mortality as a
function of recent climates, and coupling them with future
climate scenarios, conrms that the carbon sink is likely to
decline (Hubau et al., 2020). A key uncertainty with these latter
projections is the extent to which local resilience due to shallow
water-tables (Sousa et al., 2020) may mitigate effects, and
whether more compositional changes will extend the carbon sink
further if species better-adapted to the new conditions compen-
sate for others’ losses. The analysis by Sullivan et al. (2020)
conrms that lagged species-related resilience is likely as long as
forests do not experience substantial warming.
(10) Tropical forest biodiversity is changing. RAINFOR data show
that an entire group of plants, lianas (woody vines), are
increasing in dominance across Amazonia (Phillips et al., 2002).
Large lianas in turn contribute to higher tree mortality (Phillips
et al., 2005). Tree community composition is changing too. In the
Andes, plots of ABERG, RBA and RedSPP show ‘thermophiliza-
tion’ – as communities become more warm-adapted (e.g Fadrique
et al., 2018). Climate change is inducing large-scale change in
tropical lowland trees too, as wet-adapted taxa in Amazonia face
greater mortality risks from drought (Esquivel-Muelbert et al.,
2017, 2019) while a shift towards drought-deciduous tree species
is observed in west African plots experiencing a multi-decadal
drought (Fauset et al., 2012, Aguirre-Guti´
errez et al., 2019,
2020). In both continents these community responses to drought
coincided with biomass gains. Nonetheless, because of the long
generation times of tropical trees the compositional change has
not kept pace with the drying of Amazonia (Esquivel-Muelbert
et al., 2019). This suggests that further community change is
inevitable, even before accounting for losses driven by defores-
tation and disturbance of remaining forests (Barlow et al., 2016).
Current models lack the capacity to account for variation in
tropical woody plant biodiversity and demographic processes and
their lagged responses to global change drivers.
In sum, highly distributed, long-term monitoring of the world’s
richest forests has profoundly increased our understanding of nature’s
sensitivity to climate change. It has shown that intact forests have been
surprisingly resilient, but that many are now reaching the limits of their
tolerance to global heating and drying. Looking forward, many of the
key uncertainties that remain concern the responses of tropical biodi-
versity itself. This includes the extent to which the great biocomplexity
of tropical forests themselves will provide an effective and timely in-
surance policy in the face of rapidly changing climates. To understand
this, forest monitoring must continue.
6. Challenges and the future of tropical forest monitoring
Large-scale plot networks have not only made a series of crucial
scientic discoveries and advances, but even more profoundly the Social
Research Network model pioneered by RAINFOR since 2000 has inu-
enced how the science itself is being done. Tropical ecology has un-
dergone a remarkable shift from a small cadre of researchers working in
one or two sites to a more globalized and decentralised process with
greatly increased contributions from tropical scientists. This has been
made possible by supporting highly-distributed researchers and eld
sites, establishing mechanisms for shared data management, fostering
an equitable concept of data ownership, and embracing groups who are
often marginalised in research. Importantly, the network model is
nurtured by researchers placing trust in the sharing of hard-won data to
answer big questions and recognising the value of developing trusting
relationships over time. Finally, the growth of interactive multi-site,
multi-cultural science has beneted hugely from standardized eld
and analytical methods that have been agreed upon, formalised and
promoted. The ForestPlots.net experience demonstrates that collabora-
tive, multi-polar structures help ensure breadth and resilience while
supporting and encouraging the leaders of the future.
The transformative power of this approach has now led to the
establishment of multiple plot-centred networks that are reshaping our
understanding of tropical ecosystems. However, these networks face a
number of key challenges to sustain the achievements made and enact
even deeper transformational change, which we set out here.
1. How can networks support leadership in the Global South?
Although no single project can reverse the impact of centuries of
global inequality, tackling the barriers to a more equitable world is
the responsibility of all. Ecology and conservation science remain
biased towards temperate ecosystems in terms of funding and topical
focus (Di Marco et al., 2017; Reboredo Segovia et al., 2020), while
tropical ecology is often detached from policy-making processes and
most high-impact papers are still led from the North. Together with
open data-sharing and long-term collaboration, more leadership of
forest science from tropical countries helps to address these dispar-
ities and achieve more impact on forest and carbon management
(e.g., Vargas et al., 2017; Baker et al., 2020). Supporting tropical
students at different levels up to Ph.D. and mentoring beyond the
doctoral degree is also important. To help, ForestPlots.net has made
shared tools widely available, and especially data management an-
alytic tools that support data contributors as much as users. To
ensure eldwork is valued and leadership in tropical researchers is
fostered, we have developed a Code of Conduct to encourage con-
tributions, support scientists in tropical countries, and promote
mentoring of junior scientists. To oversee this we created a diverse
steering committee that now supports dozens of projects each year
(http://www.forestplots.net/en/join-forestplots/research-projects).
As a result, the proportion of ForestPlots.net research projects and
products led by tropical nationals has greatly increased, with <10%
of publications when RAINFOR began (2000–2004), rising to 35% in
2009 and 50% by 2019. In spite of such gains diversifying leadership
is a long-term process. Ultimately, sustained funding in and by
tropical countries themselves will ensure they not only have strong
training programmes to develop the core eld and analytical skills
that scientists need, but equal opportunities for career development.
ForestPlots.net et al.
2. How should we value and recognise collaboration and leadership?
Most of the obvious reward structures in science - job security, in-
come, grant success, peer reputation and public acclaim – can favour
a ‘me rst’ approach. Credit accrues to individuals, but true collab-
oration involves trust, sharing and encouraging others. Collaboration
is gratifying, but letting go of our egos can be challenging, while in
larger groups there is greater risk that individuals feel their contri-
butions go unnoticed. Likewise, the essential and major effort needed
‘backstage’ in ForestPlots.net to check data, update and develop data
management, and support requests to utilize data, goes unseen. A
partial developmental solution to this involves providing network
contributors the opportunity to lead analyses with the expectation
that these new leaders then support others with their analyses. Another
approach is to reect the diversity of contributions that underpin the
success of networks by using a group author that shares credit among
all, as in the current paper. These steps can promote the recognition
of multiple contributions and development of tomorrow’s leaders.
3. How do we properly value the long-term? Project and thesis time-
scales last from one to ve years, but the lifespans of trees are
measured in decades and centuries. What can seem vitally important
in a hypothesis-driven research grant or a Ph.D. may, in fact, have
little relevance to the longer natural rhythms of nature. What if the
dominant processes governing climate responses of forests turn out
to involve lifetime accumulated ecophysiological stress, tree
demography and species migration? Clearly very long-term research
is essential to decode these processes. Meanwhile, maintaining per-
manent plots is as much an expression of hope in the future as a stake
in an immediate scientic outcome, as rewards may accrue to others
distant in time and space. Indeed, we have all beneted from re-
searchers installing plots from the 1930s onwards. These pioneers
never dreamt that their careful tree measurements and botanical
identications would help reveal the impacts of climate change on
tropical forests, but look what they have achieved! Long-term research
programmes are simply irreplaceable, enabling us to discover, quantify,
identify the causes of, and ultimately tackle environmental change.
4. Can we ensure eldwork and human skills are valued for what they
are? Technology provides many benets to the scientic endeavor,
but there are risks too, particularly in a eld where long-term mea-
surements may be perceived as unfashionable (Ríos-Salda˜
na et al.,
2018). A serious risk is that the tail wags the dog: when technological
advance is an end in itself, it is unlikely that scientic and human
progress will follow. We should never forget the basic truth that
human beings and their skills are essential to measure and identify
tropical trees. It is notable that those measuring, climbing and col-
lecting tropical trees in permanent plots are among the least well-
paid of all actors in the global scientic endeavor. Yet, these true
key workers are irreplaceable as tree measurement in many locations
is completely dependent on such labour and skill (Fig. 7) and, more
broadly, combinations of people and technology provide the best re-
sults (next section). Moreover, because tropical tree oras usually
run into the thousands of species (e.g., >4700 tree species in Peru,
V´
asquez et al., 2018), identication depends on the work of highly
skilled climbers and botanists to collect material from canopies,
make vouchers, and identify and permanently store them in
herbaria. Without physical collections and the immense multi-
cultural knowledge and skills that produce them, identications
are untestable hypotheses whose quality cannot be evaluated. But
with vouchers, we have the names that are essential to test questions
about diversity, composition, functional traits, and biomass.
5. How should we fund proven networks long-term? As the most
pressing concern, this question intersects closely with all of the
above. Few organisations have the vision to support long-term endeavours
where leadership and credit is shared diffusely, many benets accrue after
decades, and where the most exciting discoveries may be unforeseeable.
We recommend the following, potentially transformational changes
to address the challenges and unlock the benets of ambitious, long-
term monitoring of tropical forests:
(i) Science Agencies have the foresight to build long-term research ca-
pacity and consciously adopt the challenge of international
ecosystem monitoring and tropical career development;
(ii) Space Agencies, recognising that tropical eldwork can measure the
things they cannot and validate the attributes that they can, directly
support the labour and skills of tropical forest scientists;
(iii) Development and Conservation Agencies who depend on a robust
understanding of the long-term health of forests, recognise that
high quality, long-term, on-the-ground monitoring of trees and
the skills needed for this are vital for their agenda;
(iv) National and international climate adaptation and mitigation fun-
ders recognise that long-term scientic monitoring of mature
forest carbon uxes is essential for successful nature-based
conservation and forest management, and to achieve
Fig. 7. Accurately measuring and identifying trees in
remote tropical forests requires dedication, skill and
courage.
To measure the diameter of this giant Ceiba (Malva-
ceae) tree in Reserva Amargal (Colombia’s Choc´
o),
three researchers of the COL-TREE network each
needed to climb >10 m. Such techniques can be the
most practical and accurate options for measuring
large trees. Here, like many of our sites, there is no
electric power, let alone a eld station, and chronic
insecurity due to political and social conicts and
narcotrafcking means that aircraft and laser-
scanners are not deployable. Images: Pauline
Kindler, University of Rouen (France).
ForestPlots.net et al.
Box 1
What does it take?
Clearly, long-term, ground-based monitoring of tropical forests requires a sustained global team effort. But just how much does it take to deliver
tropical forest plot data in practice? It requires both skilled labour and funds. So here we address this question in terms of the human effort made
thus far and the nancial investment needed to monitor across continents.
(a) The Human Contribution: Network efforts include not only in-country eld campaigns but much besides. To deliver from conception to
product, high-quality data collected over many years and in dozens of countries requires multiple teams that are well-led and consistently
trained in the proper protocols, quality control, and data management. In RAINFOR and AfriTRON this includes national or local eld-team
members to establish and remeasure plots, others to collect and identify plants and collect and analyse soils, colleagues to organize and
manage the data, and others to sustain and lead the process nationally and globally – not to mention those who support these processes with
essential administration, herbarium assistance, database development, analytical packages, information technology support, technical
training and so on. Naturally some individuals contribute in several ways and roles change over time as lives change. All these local, national
and global efforts ultimately depend on funding.
The average effort in the eld, herbarium, and lab to install a typically remote and diverse 1-ha tropical forest plot and analyse its species and soil
sums to 98 person-days, with an additional effort of 38 person-days to support and sustain these teams and data management. Together a total of
136 person-days are needed on average to deliver high-quality data from a new plot.
Recensusing a plot is usually less demanding (for example soil collection is not repeated and there are fewer plants to identify) but still
considerable: 45 person-days in the eld and herbarium, and 31 person-days to support and sustain the recensus. Therefore, 76 person-days are
required to deliver high quality data from a recensused plot. These estimates represent long-term averages and are based on remeasuring plots within
ve years or less between each census, and assume the plot was installed using standard protocols. Naturally circumstances can vary from site-
to-site and country-to-country.
Thus far our teams have established 4062 plots in tropical forests of which 1816 are recensused, from as little as once up to as many as 40 times
each. The modal size of the 4062 plots is between 0.9 and 1.1 ha but there are smaller plots too (1844 are ≥0.9 ha, and 2216 are <0.9 ha). The
recensused plots tend to be larger: of the 1816 recensused plots, 62% are ≥0.9 ha (1131) and 38% are <0.9 ha (675).
If we conservatively assume that plots ≥0.9 ha (average size =1.2 ha) require 136 days to install and 76 days to recensus, and those <0.9 ha
require half this effort (also likely to be conservative due to xed costs for even the smallest plots), then the total effort to install these plots has
been 196,248 person-days, and recensusing them has taken 357,940 person-days. In total this comes to 1518 years.
As if one remarkably talented and tireless individual had been working continuously since 502 CE.
(b) Cost of Sustained Continental Monitoring: How much does it cost to monitor Earth’s remaining old-growth tropical forests with ground net-
works? This is a critical question given the exceptional ecological value of these systems, the threats they face, and the role they play in
modifying the rate of global climate change.
At rst sight this question appears difcult to answer, or to even agree upon the terms of reference. Scientists would ask and likely argue:
Monitoring what? For whom? With what precision, level of condence, or spatial and temporal resolution? Recognising such difculties, we
take a pragmatic approach and reframe the question. Instead we posit, How much will it cost to monitor tropical forests using all the permanent plots
that have already been remeasured?
This question is tractable practically (these plots represent a known quantity: we know exactly where they are, what most of the species are, and to
a large extent who can actually do the work – each of which is critical), it makes sense scientically (the plots already have a baseline monitoring
period against which we can assess any change, which is essential), and it is justiable quantitatively (using somewhat smaller datasets than this
we have already detected long-term changes in carbon balance, productivity and tree mortality on each continent, reported short-term changes
in response to El Ni˜
no droughts and other climate anomalies, and attributed changes in carbon and biodiversity to climate drivers, all of which
establish proof-of-concept). So here goes:
*There are 1105 remeasured ForestPlots.net plots in tropical forest South America (422 <0.9 ha +683 ≥0.9 ha), 462 in tropical forest Africa
(109 +353), 192 in tropical forest Asia (106 +86) and 32 in tropical forest Australasia (22 +10). With all 1791 plots monitored on a four-year
cycle this requires revisiting 448 plots annually, of which 165 are <0.9 ha and 283 are ≥0.9 ha.
*Recensus costs can vary from site-to-site. Botanical identication is especially challenging in most of South America due to the extraordinary
diversity, while some African forests are exceptionally remote. Employment, social security and health costs vary but are rising almost
everywhere. On average, considering all the direct and indirect human effort required (above) and additional direct costs (including consumables,
equipment, travel, subsistence, insurance, visas, permits, shipping, training, and IT), the current cost to deliver a high-quality tropical recensus
is ≈18,000 USD for plots ≥0.9 ha, and at least half this for plots that are <0.9 ha. That’s about 30 USD per tree.
[Installing plots is a costlier operation as it requires more expert time to collect and identify highly distributed trees. The total cost to properly
install a high-quality tropical forest plot is ≈27,000 USD for a 1 ha plot. When forests are recensused this start-up investment is leveraged as a
contribution: this enables the subsequent monitoring of forest dynamics.]
Thus, the annual delivery cost for a pantropical, practical ground-based recensus programme capable of tracking and attributing forest change to
published standards is estimated as:
(283 18,000 +165 9000) ≈6.6 million US dollars.
This annual investment is sufcient to ensure that ground-measurements track the biome-wide and continent-specic biomass carbon balance of the
world’s remaining tropical moist forests, as well as their climate sensitivity. It also provides ground calibration and validation for remote estimates of
ForestPlots.net et al.
nationally determined contributions (NDCs) to reducing
greenhouse gas emissions for decades to come.
Every one of these user groups requires successful networks with
long-term, research-grade tropical forest plots to discern the status and
change of biodiversity and to assess the stocks and ows of carbon.
7. Achievements, impact and potential
Despite the challenges, tropical forest science has come a very long
way. Until recently, tropical ecology suffered from a massive data
decit. We had plenty of theory and conjecture, but few comparable
observations over time and space to deductively put these ideas to the
test or inductively generate new ones. Networks such as ForestGEO,
RAINFOR, AfriTRON, and the wider ForestPlots community have
contributed much to resolving this. By leveraging a remarkably old tech-
nology, forest plot networks have sparked a modern revolution in tropical
forest science. They provide the means by which we have quantied the
trajectory of tropical forest carbon balance, including its climate sensi-
tivity, and now provide a Pan-Tropical Observatory for tracking these
vital indicators of Earth’s health going forward.
Permanent plots are now the prism through which ecologists address
a rich suite of ecological questions, but they have also changed the way
others see forests. For example, well-identied permanent plots have
proved fertile ground for botanists to discover new tree species and
genera (e.g. Reitsma, 1988, Baker et al., 2017, Wurdack and Farfan-Rios,
2017, V´
asquez et al., 2018, Gosline et al., 2019, V´
asquez and Soto
Shareva, 2020), ethnoecologists to quantify forest people’s values
(Phillips and Gentry, 1993; Lawrence et al., 2005), atmospheric scien-
tists to explore organic volatile production (Harley et al., 2004), eco-
physiologists to assess why trees die (Rowland et al., 2015; McDowell
et al., 2018), modelers to verify ecosystem simulations (Johnson et al.,
2016), and foresters to predict and manage wood production and its
impacts (Berry et al., 2008; Gourlet-Fleury et al., 2013). They provide
critical infrastructure for whole-biodiversity and cross-taxa inventories,
including exploration of cryptic canopy and soil faunal and microbial
biodiversity (e.g., Nakamura et al., 2017). The impacts of these networks
on policy are also growing. In Peru for example, ForestPlots.net,
MonANPeru and RAINFOR have contributed to estimating National
Forest Reference Emission Levels (NREF) since 2016, and our permanent
plots are now being used to validate national contributions to the Paris
Climate Accord via forest carbon sequestration (Vicu˜
na Mi˜
nano et al.,
2018; Baker et al., 2020). In Ghana, plots were needed to quantify his-
torical and current carbon stocks, helping to establish baseline forest
reference levels for the agship Cocoa Forest REDD+Programme (FCPF,
2017). In Gabon stratied-random sampling of high-quality AfriTRON
plots is now used for the National Forest Inventory (Poulsen et al. 2020).
Internationally, RAINFOR, AfriTRON, T-FORCES and 2ndFor provide
the new IPCC default values for old-growth and secondary forest carbon
sequestration to help countries develop their nationally determined
contributions as part of the UNFCCC process (Requena Suarez et al.,
2019).
What of the future? As new technologies for probing forests become
available, the highly distributed standardized long-term plots and net-
works of skilled tropical researchers represent critical infrastructure to
enhance and calibrate new insights as they arise. The benets of working
within established plots go beyond simply having condence in species
identications and hence biomass. By leveraging the wealth of infor-
mation that permanent plots provide, we can increase the scientic
value of new technology. For example, the ability to match individual
trees from laser-scanning surveys to tagged, censused individuals pro-
vides critical information on growth and identity (Disney et al., 2018).
Integrating long-term botanical and ecological records of plots with
terrestrial and airborne laser-scanning in designated super-sites (Chave
et al., 2019) can help overcome limitations of different approaches,
providing greater certainty to biomass estimates (e.g., Schepaschenko
et al., 2019). Hence forest networks can help unlock the value of space-
based efforts to monitor forests. Just as the constellation of Earth-
observing environmental satellites is a public good, the constellation
of forest plots provides highly complementary, critical global infra-
structure. And last, but not least, as intact tropical ecosystems continue
to shrink, burn and fray at the edges, permanent plots provide the
indispensable baseline for understanding biodiversity and ecosystem
processes too. They can be our shining North Star for guiding sorely
needed restoration efforts throughout this century.
So far this effort has relied on the goodwill of highly distributed
colleagues and dozens of grants from many sources (see Acknowledg-
ments). Only long-term funding will ensure that the vital public benets
of plot networks continue to ow. Such support is surprisingly difcult
to obtain (see Box 1). Yet twenty years of hard-won scientic results
show that reliable and highly distributed monitoring is irreplaceable.
They underscore the importance of welcoming all contributors to this
effort, and of valuing the diverse skills needed to understand tropical
biodiversity and its dynamics. Ultimately, we will understand the nature
of tropical forests best when the science is global, local skills are fairly
valued, and the development of tropical scientists is at its heart. Indeed,
we know of no other model capable of achieving this.
CRediT authorship contribution statement
All authors have contributed to ForestPlots.net-associated networks
by leading, collecting or supporting eld data acquisition, or imple-
menting and funding network development, data management, analyses
and outputs. O.L.P. wrote the manuscript with initial contributions from
S.L.L., M.J.S. contributed new analyses, M.J.S., G.L.P. and A.L. helped
prepare the gures, and all authors reviewed the manuscript with many
suggesting valuable edits. O.L.P., T.R.B., G.L.-G. and S.L.L. conceived
ForestPlots.net. R.B., T.R.B., T.F., D.G., E.G., E.H., W.H., A.E.-M., A.L., S.
L.L., K.M., Y.M., G.C.P., O.L.P., B.S-M., L.Q., and M.J.P.S have contrib-
uted tools, funding or management to its development since.
The article is attributed collectively as ForestPlots.net et al., with
individual authors listed alphabetically rst by country of institution
biomass. It further enables us to detect whether the tropical sink is now disappearing as predicted, and where and why, what the consequences
for biodiversity are, and to determine how much intact ecosystems can contribute to countries’ nationally determined contributions (NDCs) to
climate mitigation.
While $6.6 million is a signicant sum it is instructive to compare it to funding required for other large-scale science initiatives. The United
States alone spends $80 million annually (i.e., twelve times as much) on its national forest inventory (Castillo and Alvarez, 2020). Space Agencies
invest from ca. $80 million to 500 million Euros for a single mission to estimate biomass from space for a few years (i.e, one to two orders of
magnitude more). And as we have seen, ground networks ultimately not only transcend the short-term time windows of such missions but add
huge value to them.
In conclusion, the ongoing cost of monitoring Earth’s remaining tropical forests on the ground is extraordinarily small compared to the great
scientic and practical benets it provides. Meanwhile, tropical forests themselves are in greater trouble than ever before, even while providing
tremendous and irreplaceable benets to the people of the world. Now that the capacity to monitor tropical forests is established and proven, it is
incumbent on all of us to ensure this collective effort continues and grows.
ForestPlots.net et al.
and secondly by family name.
Declaration of competing interest
There is no conict of interest.
Acknowledgments
This paper is a product of the RAINFOR, AfriTRON and T-FORCES
networks and the many other partner networks in ForestPlots.net which
support long-term forest science and monitoring across tropical coun-
tries. These initiatives have been supported by numerous people and
grants since their inception. We are particularly indebted to more than
one thousand four hundred eld assistants for their essential help in
establishing and maintaining the plots, as well as highly distributed
rural communities and institutions. For additional assistance we thank
Michel Baisie, Wemo Betian, Vincent Bezard, Mireille Breuer-Ndoundou
Hockemba, Ezequiel Chavez, Douglas Daly, Armandu Daniels, Eduardo
Hase, Muhammad Idhamsyah, Phillipe Jeanmart, Cisquet Keibou
Opepa, Jeanette Kemp, Antonio Lima, Jon Lloyd, Mpanya Lukasu, Sam
Moore, Klaus Scipal and Rodrigo Sierra. We thank Mark Burkitt for help
developing the ForestPlots.net database. We acknowledge the long-term
help provided by national and local government ofces in all countries
where colleagues work in facilitating the permission and documentation
for eldwork, as well as help provided by protected area and other
authorities.
The networks have been supported by multiple grants, most notably
the European Research Council (ERC Advanced Grant 291585 – ‘T-
FORCES’), the Gordon and Betty Moore Foundation (#1656 ‘RAINFOR’,
and #5349 ’MonANPeru’), the David and Lucile Packard Foundation,
the European Union’s Fifth, Sixth, and Seventh Framework Programme
(EVK2-CT-1999-00023 – ‘CARBONSINK-LBA’, 283080 – ‘GEO-
CARBON’, 282664 – ‘AMAZALERT’), the Natural Environment Research
Council (NE/D005590/1 – ‘TROBIT’, NE/F005806/1 – ‘AMAZONICA’,
‘PPFOR’ E/M0022021/1), several NERC Urgency and New Investigators
Grants, the NERC/State of S˜
ao Paulo Research Foundation (FAPESP)
consortium grants ‘BIO-RED’ (NE/N012542/1, 2012/51872-5), ‘ECO-
FOR’ (NE/K016431/1, 2012/51509-8), ‘ARBOLES’ (NE/S011811/1),
‘SEOSAW‘ (NE/P008755/1), ‘SECO’ (NE/T01279X/1), ‘NORDESTE’
(NE/N012550/1, 2015/50488-5), the Royal Society (University
Research Fellowships and Global Challenges Awards) (‘FORAMA’, ICA/
R1/180100), the National Geographic Society, the Centre for Interna-
tional Forestry (CIFOR), Gabon’s National Parks Agency (ANPN), US
National Science Foundation (DEB 1754647), and Colombia’s Colcien-
cias. We thank the National Council for Science and Technology
Development of Brazil (CNPq) for support to the Cerrado/Amazonia
Transition Long-Term Ecology Project (PELD/441244/2016-5), the
PPBio Phytogeography of Amazonia/Cerrado Transition project (CNPq/
PPBio/457602/2012-0), the Goi´
as Research Foundation (FAPEG/PELD:
2017/10267000329), and several PVE and Productivity Grants. Funding
for plots in the Udzungwa Mountains (Tanzania) was obtained from the
Leverhulme Trust under the Valuing the Arc project. Plots in the Dem-
ocratic Republic of Congo were funded by the Belgian Science Policy
Ofce (SD/AR/01A/COBIMFO, BR/132/A1/AFRIFORD, BR/143/A3/
HERBAXYLAREDD, CongoFORCE), the Flemish Interuniversity Council
VLIR-UOS (CD2018TEA459A103, FORMONCO II), and the European
Union (REAFOR, FORETS projects). We acknowledge grant CEBA
(ref. ANR-10-LABX-25-01) and the support of the Forestry Development
Authority of Liberia. We also acknowledge the support of the European
Space Agency. Data from RAINFOR, AfriTRON and T-FORCES are stored
and curated at ForestPlots.net, a cyber-infrastructure initiative devel-
oped at the University of Leeds that unites permanent plot records and
supports scientists from the world’s tropical forests. The development of
ForestPlots.net and curation of data has been funded by several grants
including NE/B503384/1, NE/N012542/1 ‘BIO-RED’, ERC Advanced
Grant 291585 ‘T-FORCES’, NE/F005806/1 ‘AMAZONICA’, NERC New
Investigators Awards, NE/N004655/1, ‘TREMOR’, the Gordon and Betty
Moore Foundation (‘RAINFOR’, ‘MonANPeru’), ERC Starter Grant
758873 ‘TreeMort’, EU Framework 6, a Royal Society University
Research Fellowship, and a Leverhulme Trust Research Fellowship.
The manuscript has been developed with the encouragement of
Richard Primack and Reinmar Seidler and has beneted from the
constructive comments of three reviewers; we thank them all. Finally we
thank our late, great colleagues whose unique contributions helped
make possible all that the networks and ForestPlots.net have achieved
together since the beginning: Samuel Almeida, Elisban Armas, Jos´
e
Armas, Sandra Brown, Kwaku Duah, Gloria Galeano, Alwyn Gentry, Max
Gunther, Moïse Mikame, Norman Myers, Sandra Pati˜
no, John Proctor,
David Smith and Jean-Pierre Veillon.
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