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Funding: Data collection was largely funded by the UK Natural Environment Research Council (NERC) project TREMOR (NE/N004655/1) to D.G., E.G. and O.P., with further funds from Coordenação de Aperfeiçoamento de Pessoal de Nível Superior—Brasil (CAPES, finance code 001) to J.V.T. and a University of Leeds Climate Research Bursary Fund to J.V.T. D.G., E.G. and O.P. acknowledge further support from a NERC-funded consortium award (ARBOLES, NE/S011811/1). This paper is an outcome of J.V.T.’s doctoral thesis, which was sponsored by CAPES (GDE 99999.001293/2015-00). J.V.T. was previously supported by the NERC-funded ARBOLES project (NE/S011811/1) and is supported at present by the Swedish Research Council Vetenskapsrådet (grant no. 2019-03758 to R.M.). E.G., O.P. and D.G. acknowledge support from NERC-funded BIORED grant (NE/N012542/1). O.P. acknowledges support from an ERC Advanced Grant and a Royal Society Wolfson Research Merit Award. R.S.O. was supported by a CNPq productivity scholarship, the São Paulo Research Foundation (FAPESP-Microsoft 11/52072-0) and the US Department of Energy, project GoAmazon (FAPESP 2013/50531-2). M.M. acknowledges support from MINECO FUN2FUN (CGL2013-46808-R) and DRESS (CGL2017-89149-C2-1-R). C.S.-M., F.B.V. and P.R.L.B. were financed by Coordenação de Aperfeiçoamento de Pessoal de Nível Superior—Brasil (CAPES, finance code 001). C.S.-M. received a scholarship from the Brazilian National Council for Scientific and Technological Development (CNPq 140353/2017-8) and CAPES (science without borders 88881.135316/2016-01). Y.M. acknowledges the Gordon and Betty Moore Foundation and ERC Advanced Investigator Grant (GEM-TRAITS, 321131) for supporting the Global Ecosystems Monitoring (GEM) network (gem.tropicalforests.ox.ac.uk), within which some of the field sites (KEN, TAM and ALP) are nested. The authors thank Brazil–USA Collaborative Research GoAmazon DOE-FAPESP-FAPEAM (FAPESP 2013/50533-5 to L.A.) and National Science Foundation (award DEB-1753973 to L. Alves). They thank Serrapilheira Serra-1709-18983 (to M.H.) and CNPq-PELD/POPA-441443/2016-8 (to L.G.) (P.I. Albertina Lima). They thank all the colleagues and grants mentioned elsewhere [8,36] that established, identified and measured the Amazon forest plots in the RAINFOR network analysed here. The authors particularly thank J. Lyod, S. Almeida, F. Brown, B. Vicenti, N. Silva and L. Alves. This work is an outcome approved Research Project no. 19 from ForestPlots.net, a collaborative initiative developed at the University of Leeds that unites researchers and the monitoring of their permanent plots from the world’s tropical forests [61]. The authros thank A. Levesley, K. Melgaço Ladvocat and G. Pickavance for ForestPlots.net management. They thank Y. Wang and J. Baker, respectively, for their help with the map and with the climatic data. The authors acknowledge the invaluable help of M. Brum for kindly providing the comparison of vulnerability curves based on PAD and on PLC shown in this manuscript. They thank J. Martinez-Vilalta for his comments on an early version of this manuscript. The authors also thank V. Hilares and the Asociación para la Investigación y Desarrollo Integral (AIDER, Puerto Maldonado, Peru); V. Saldaña and Instituto de Investigaciones de la Amazonía Peruana (IIAP) for local field campaign support in Peru; E. Chavez and Noel Kempff Natural History Museum for local field campaign support in Bolivia; ICMBio, INPA/NAPPA/LBA COOMFLONA (Cooperativa mista da Flona Tapajós) and T. I. Bragança-Marituba for the research support. Tropical forests face increasing climate risk1,2, yet our ability to predict their response to climate change is limited by poor understanding of their resistance to water stress. Although xylem embolism resistance thresholds (for example, Ψ50) and hydraulic safety margins (for example, HSM50) are important predictors of drought-induced mortality risk3-5, little is known about how these vary across Earth's largest tropical forest. Here, we present a pan-Amazon, fully standardized hydraulic traits dataset and use it to assess regional variation in drought sensitivity and hydraulic trait ability to predict species distributions and long-term forest biomass accumulation. Parameters Ψ50 and HSM50 vary markedly across the Amazon and are related to average long-term rainfall characteristics. Both Ψ50 and HSM50 influence the biogeographical distribution of Amazon tree species. However, HSM50 was the only significant predictor of observed decadal-scale changes in forest biomass. Old-growth forests with wide HSM50 are gaining more biomass than are low HSM50 forests. We propose that this may be associated with a growth-mortality trade-off whereby trees in forests consisting of fast-growing species take greater hydraulic risks and face greater mortality risk. Moreover, in regions of more pronounced climatic change, we find evidence that forests are losing biomass, suggesting that species in these regions may be operating beyond their hydraulic limits. Continued climate change is likely to further reduce HSM50 in the Amazon6,7, with strong implications for the Amazon carbon sink. Publisher PDF

Aim: The latitudinal biodiversity gradient is considered a first-order biogeographical pattern for most taxonomic groups. Latitudinal variation in plant diversity is not always consistent, and this could be related to the particular characteristics of different forest types. In this study, we compare latitudinal changes in floristic diversity (alpha diversity), composition (beta diversity) and dominance across different tropical forest types: floodplain, terra firme and submontane forests. Location: Western Amazonia (Ecuador, Peru and Bolivia). Taxon: Woody plants. Methods: We inventoried 1978 species and 31,203 individuals of vascular plants with a diameter at breast height ≥ 2.5 cm in 118 0.1-ha plots over an 1800 km latitudinal gradient in three different forest types. The relationships between alpha diversity, latitude and forest type were analysed using generalised linear mixed models. Semi-parametric permutational multivariate analysis of variance was used to investigate the effects of latitude and forest type on beta diversity. Dominant species abundances were correlated with non-metric multidimensional scaling ordination axes to reflect their contributions in shaping changes in beta diversity. Results: Alpha diversity increased towards equatorial latitudes in terra firme and submontane forests but remained relatively constant in floodplains. Beta diversity of all forest types changed with latitude, although less clearly in floodplains. Also, in floodplain forests, there were fewer dominant species contributing to beta diversity and more species homogeneous along the gradient. Main Conclusions: Latitudinal diversity patterns are manifested in alpha and beta diversity since latitude summarizes climatic and edaphic changes. However, we found different responses of each forest type. In floodplain forests, inundation regime is a stronger predictor than latitude, limiting floristic diversity and composition. Changes in dominant species abundance over gradients explained species composition, but floodplain forests harboured more homogeneous dominant species than well drained forests. It is key to study environmental trends and habitat characteristics of each forest type to understand their species diversity and dominance patterns

Plot-based monitoring has yielded much information on the taxonomic diversity and carbon (C) storage in tropical lowland forests of the Amazon basin. This has resulted in an improved understanding of the relationship between lowland forest biomass dynamics and global change drivers, such as climate change and atmospheric CO2 concentration. Much less attention has been paid to the mountain ecosystems of South America that comprise montane forests and alpine vegetation (páramo, puna, high Andean grasslands, wetlands, and alpine heath). This vegetation complex provides a variety of ecosystem services and forms a natural laboratory along various physiographic, geological and evolutionary history/biogeography, and land use history gradients. Here, we review existing empirical understanding and model-based approaches to quantify the contribution of mountain ecosystems to ecosystem service provision in the rapidly changing socioecological setting of the South American mountains. The objective of this paper is to outline a broad road map for the implementation of mountain vegetation into dynamic global vegetation models (DGVM) for use in Earth System Models (ESM), based on our current understanding of their structure and function and of their responsiveness to global change drivers. We also identify treeline processes, critical in mountain ecosystems, as key missing elements in DGVMs/ESMs, and thus explore in addition a treeline model. Stocktaking of the availability of empirical data was undertaken from eight research sites along the Andes and in south-eastern Brazil. Out of eight sites, two (one each in Venezuela and Brazil) had some climate, ecological and ecophysiological data potentially suitable to parametrise a DGVM. Tree biomass data were available for six sites. A preliminary assessment of the Joint UK Land Environment Simulator (JULES) DGVM was made to identify gaps in available data and their impacts on model parametrisation and calibration. Additionally, the potential climate-determined elevation of the treeline was modelled to check the DGVM for its ability to identify the transition between the montane forest and alpine vegetation. Outcomes of the evaluation of the JULES land surface model identified the following key processes in montane forests: temperature-related decrease in net primary production, respiration, and allocation to above-ground biomass and increase in soil C stocks with elevation. There was a variable agreement between simulated biomass and those derived from field measurements via allometric equations. We identified major gaps between data availability and the needs for process-based modelling of South American mountain vegetation and its dynamics in DGVMs. To bridge this gap, we propose a transdisciplinary network, composed of members of the theoretical/modelling and empirical scientific communities, to study the natural dynamics of mountain ecosystems and their responses to global change drivers locally, regionally and at the continental scale, within a social-ecological system framework. The work presented here forms the basis for the design of data collection from field measurements and instrumental monitoring stations to parametrise and verify DGVMs. The network is designed to collaborate with and complement existing long-term research initiatives in the region and will adopt existing standard field protocols. Complementary protocols will ensure compatibility between field data collection and data needed for process-based and empirical models.

Territórios Indígenas (TIs) na Amazônia protegem aproximadamente 24.5 gigatoneladas de carbono (GtC) acima do solo, atuam como barreiras significativas contra o desmatamento e a degradação florestal, e funcionam como importantes amortecedores contra as mudanças climáticas. TIs demarcadas apresentam desmatamento significativamente menor do que terras não reconhecidas oficialmente, demonstrando a importância de se demarcar TIs tanto para proteger os meios de subsistência e as culturas dos povos nativos da Amazônia, quanto para conservar suas florestas e rios.

Territorios indígenas (ITs, en sus siglas en inglés) en la Amazonia protegen aproximadamente 24,GtC sobre el suelo, funcionan como barreras significativas contra la deforestación y la degradación del bosque, y sirven como una defensa importante contra el cambio climático. Los ITs demarcados tienen significativamente menos deforestación en comparación con tierras no reconocidas, demostrando la importancia de demarcar ITs para proteger los sustentos y la cultura de los indígenas Amazónicos y para conservar sus bosques y ríos.

Indigenous territories (ITs) in the Amazon protect approximately 24.5 GtC aboveground, act as significant barriers to deforestation and forest degradation, and serve as an important buffer against climate change. Demarcated ITs have significantly less deforestation than unrecognized lands, demonstrating the importance of demarcating ITs to both protect the livelihoods and cultures of the Amazon’s native peoples and to conserve its forests and rivers.

Este capítulo discutirá los impactos observados y pronosticados del cambio climático en los ecosistemas terrestres y acuáticos amazónicos. Nos centraremos en los impactos sobre la biodiversidad, los servicios ecosistémicos, el ciclo del carbono, la pesca y las emisiones de quema de biomasa.

En este capítulo resumimos información sobre los ecosistemas amazónicos y sus funciones ecológicas, con un enfoque principal en los árboles. Comenzamos con una breve descripción de los tipos de vegetación de los Andes, seguida de una descripción más detallada de los tipos de vegetación terrestre de las tierras bajas amazónicas y concluimos con los vastos humedales incluidos en el área. Continuamos con un análisis de las principales funciones de los ecosistemas (p. ej., terrestres y acuáticos), con énfasis en la productividad y el secuestro de carbono. El objetivo de este capítulo es revelar la enorme variación de los tipos de vegetación, su diversidad y funcionamiento, y cómo esto es determinado por la dinámica del suelo, el clima y las inundaciones.

To know the quantity of fine root biomass is crucial to understanding ecosystem structure and function. Soil characteristics and fertility are mainly determined by fine root dynamics, the turnover of this material is a major contribution of organic matter to soil structure and mineral nutrient cycles, and also the main source of carbon storage. Many studies of forests are mainly estimates of above-ground biomass. Here we report on differential patterns of fine root biomass allocation in Peruvian forests. Peru is divided into three large sub-regions, Amazon, Andean, and coast. These different ecosystems have also around 84 of the 103 ecosystems types and 28 of the 32 climates on the planet. A field study was conducted installing one-hectare permanent plots in each sub-region, this research was part of an intensive monitoring effort of the carbon cycle and functional traits in primary and secondary forests. To evaluate fine root biomass, 1 m2 cross-section pits were set up in the plots where soil samples were collected every 10 cm up to 1 m depth and every 25 cm up to 2 m depth. Roots were retrieved and sorted into different diameter categories ≤0.5, 0.5 - 2.5, 2.5 - 5, and> 5 cm. Samples were rinsed with tap water over a 500-um sieve to loosen the soil and facilitate root sorting and to ensure that the sieve was fine enough to retain the finer roots. The roots after sorting were weighed fresh and then dried at 80°C for 48 hours, weighed to the nearest 0.0001 g, and stored in plastic vials for chemical analysis.Total root biomass measurements displayed strong regional differences. Coastal dry forest at 370 to 422 m in elevation, where a one ha plot can support 651-681 stems (> 10 cm dbh) had root biomass values ranging from 7960 kg ha-1 to 8130 kg/ha-1. Andean forest plots at 1780 m.a.s.l., with 586 stems contained 17020 kg ha-1 and Amazonian forest at 415 m.a.s.l., with 689 stems, had 33410 kg ha-1 fine root biomass. Our results support the hypothesis that large root biomass in tropical forests is related to ecosystem type, climatic variables (temperature and moisture), and nutrients. The low bulk density and fine root biomass in tropical forests are inversely related to temperature and moisture. Fine-root turnover decreased with soil depth, which can also have important implications for the soil carbon stock and C cycling.

Peru and Chile occupy second place in South America in area devoted to olive cultivation. Although small by Mediterranean standards, the 21,000 ha in each country represent a significant recent expansion of olive cultivation, 500 years after its introduction from Europe. The main climatic characteristic of olive cultivation in Peru is the coastal desert environment with moderate temperatures (12-28 oC), almost nil precipitation and high atmospheric water content in the winter season. There is still insufficient information about olive physiology and water management under these climatic conditions. This report is part of a long-term study of water and carbon fluxes in a drip-irrigated olive grove in sandy soil, located in the Pisco province in Peru (13°45'03.25" S, 76°09'36.77" W at 74 m elevation). Due to the absence of precipitation during the main growing season, plants depend on the local aquifer and drip irrigation for growth and yields. We installed an eddy covariance system in September of 2019 in a 9 m tower over a 5 m canopy height. The canopy covered 60% of the surface, the rest being sandy soil with very limited grass cover. The flux footprint of the system covered 3 ha for 80% of the information gathered. Peak average hourly water flux from the grove to the atmosphere in the summer season took place at 1 pm, with values of 1.8 m3 ha-1 h-1. Average daily fluxes ranged from 5 m3 ha-1 day-1 in August (winter) to 20 m3 ha-1 day-1 in February (summer). EddyPro-calculated ET values are essentially similar and represent 41% of ETo as calculated by the Penman-Monteith equation and 58.6% using a crop coefficient correction. Drip irrigation was set at 63 m3 ha-1 day-1 during the growing season (October through April) and reduced to half that amount in the winter. Optimization of water usage in relation to productivity has been pursued by monitoring photosynthetic efficiency and transpiration with an Li 6800 system in sun and shade leaves of the canopy along with use of Ekomatik digital dendrometer monitoring as a proxy for sap flow.

The divergence between the disappearance of primary forests and the appearance of secondary forests indicates a set of circumstances that simultaneously converge in what we called the society-agriculture-forest complex. Such circumstances vary between places and over time and are associated with internal factors-factors originating within the reference system-and external factors-factors originating outside the borders of the reference system-restrict the use of standard strategies for any reality. We present a quantitative model that helps to understand the relationships of the society-agriculture-forest complex as a whole. This comprehensive understanding will allow a clearer discussion of the positive and negative consequences of prioritizing actions on any of the system components. Our model establishes a set of quantitative relationships among: (i) the requirements of food and timber products for society to maintain its structure and functionality, (ii) the level of openness of the society with respect to other societies for the exchange of resources, and (iii) the interface between the economic productive systems and the ecological productive systems. To test the model, the case of Huayopata (Peru) was studied. Findings suggest that the abandonment of agricultural production and, particularly, of tea favors the appearance of secondary forests. However, projects by the Congress of Peru to reactivate the production of tea without adequate technological support to improve the current processes that use firewood for boilers would put the forestry system at risk. In addition, a potential worker 'pull factor' could reconfigure the food system and impact on the local agricultural sector.The online version contains supplementary material available at 10.1007/s10668-022-02457-6.

This chapter describes the diversity of plants and ecosystems in the lowland Amazon and discusses how complex regional gradients in climate and soil conditions drive regional variability in species composition, vegetation dynamics, carbon stocks, and productivity. The Amazon river network and its role in connecting aquatic and terrestrial ecosystems through organisms and nutrient exchanges is also emphasized.

This chapter presents observed and predicted impacts of climate change on Amazonian ecosystems, focusing on biodiversity, ecosystem services, carbon cycling, fisheries, and emissions from biomass burning. It also considers climate and land-use change feedbacks and highlights knowledge gaps to better understand these complex interactions.