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  • 1
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    The White Horse Press | The White Horse Press
    Publication Date: 2023-09-14
    Description: This is the first chapter in Timothy Killeen's meticulously researched two-volume study of the challenges facing the fight to preserve the Amazon rainforest. A comprehensive work that will be essential reading for anyone with an interest in this critically important subject.
    Keywords: Nature ; Environmental Conservation & Protection ; Nature ; Natural Resources ; Ecosystems & Habitats ; Forests & Rainforests ; bic Book Industry Communication::R Earth sciences, geography, environment, planning::RN The environment::RNK Conservation of the environment ; bic Book Industry Communication::R Earth sciences, geography, environment, planning::RN The environment::RNF Environmental management ; bic Book Industry Communication::W Lifestyle, sport & leisure::WN Natural history::WNW The Earth: natural history general
    Language: English
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  • 2
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    The White Horse Press | The White Horse Press
    Publication Date: 2024-02-08
    Description: Vital reading for all those interested in the conservation of the world’s most important ecosystem. In a lucid style backed by encyclopaedic knowledge, Killeen unpicks the extremely complex ecological and socio-political threads that comprise the recent history and the vital future of the Pan Amazon region. The fight to save the Amazon is a fight for sustainability that is emblematic of the entire future of human co-existence with Nature on Earth. Killeen is an authoritative and impassioned guide, eschewing soundbites in favour of a clearsighted and highly nuanced picture of the realities on the ground. Only in understanding present realities and how they came to pass, he argues, can we proceed hopefully into the future. Events of the last ten years are discussed in detail, because future events will have to build upon – or modify – the cultural and economic forces driving events in the Pan Amazon. Nonetheless, the text provides a longer historical perspective to show how policies create legacies that reverberate over decades, long after they have been recognised as being fundamentally flawed.
    Keywords: Nature ; Environmental Conservation & Protection ; Nature ; Natural Resources ; Social Science ; Sociology ; bic Book Industry Communication::R Earth sciences, geography, environment, planning::RN The environment::RNK Conservation of the environment ; bic Book Industry Communication::R Earth sciences, geography, environment, planning::RN The environment::RNF Environmental management ; bic Book Industry Communication::J Society & social sciences::JH Sociology & anthropology::JHB Sociology
    Language: English
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  • 3
    Electronic Resource
    Electronic Resource
    s.l. : American Chemical Society
    Environmental science & technology 14 (1980), S. 1230-1234 
    ISSN: 1520-5851
    Source: ACS Legacy Archives
    Topics: Chemistry and Pharmacology , Energy, Environment Protection, Nuclear Power Engineering
    Type of Medium: Electronic Resource
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  • 4
    Electronic Resource
    Electronic Resource
    s.l. : American Chemical Society
    Analytical chemistry 51 (1979), S. 2180-2188 
    ISSN: 1520-6882
    Source: ACS Legacy Archives
    Topics: Chemistry and Pharmacology
    Type of Medium: Electronic Resource
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  • 5
    ISSN: 1365-2486
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Biology , Energy, Environment Protection, Nuclear Power Engineering , Geography
    Notes: Uncertainty in biomass estimates is one of the greatest limitations to models of carbon flux in tropical forests. Previous comparisons of field-based estimates of the aboveground biomass (AGB) of trees greater than 10 cm diameter within Amazonia have been limited by the paucity of data for western Amazon forests, and the use of site-specific methods to estimate biomass from inventory data. In addition, the role of regional variation in stand-level wood specific gravity has not previously been considered. Using data from 56 mature forest plots across Amazonia, we consider the relative roles of species composition (wood specific gravity) and forest structure (basal area) in determining variation in AGB.Mean stand-level wood specific gravity, on a per stem basis, is 15.8% higher in forests in central and eastern, compared with northwestern Amazonia. This pattern is due to the higher diversity and abundance of taxa with high specific gravity values in central and eastern Amazonia, and the greater diversity and abundance of taxa with low specific gravity values in western Amazonia. For two estimates of AGB derived using different allometric equations, basal area explains 51.7% and 63.4%, and stand-level specific gravity 45.4% and 29.7%, of the total variation in AGB. The variation in specific gravity is important because it determines the regional scale, spatial pattern of AGB. When weighting by specific gravity is included, central and eastern Amazon forests have significantly higher AGB than stands in northwest or southwest Amazonia. The regional-scale pattern of species composition therefore defines a broad gradient of AGB across Amazonia.
    Type of Medium: Electronic Resource
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  • 6
    ISSN: 1365-2486
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Biology , Energy, Environment Protection, Nuclear Power Engineering , Geography
    Notes: The net primary production of tropical forests and its partitioning between long-lived carbon pools (wood) and shorter-lived pools (leaves, fine roots) are of considerable importance in the global carbon cycle. However, these terms have only been studied at a handful of field sites, and with no consistent calculation methodology. Here we calculate above-ground coarse wood carbon productivity for 104 forest plots in lowland New World humid tropical forests, using a consistent calculation methodology that incorporates corrections for spatial variations in tree-size distributions and wood density, and for census interval length. Mean wood density is found to be lower in more productive forests. We estimate that above-ground coarse wood productivity varies by more than a factor of three (between 1.5 and 5.5 Mg C ha−1 a−1) across the Neotropical plots, with a mean value of 3.1 Mg C ha−1 a−1. There appear to be no obvious relationships between wood productivity and rainfall, dry season length or sunshine, but there is some hint of increased productivity at lower temperatures. There is, however, also strong evidence for a positive relationship between wood productivity and soil fertility. Fertile soils tend to become more common towards the Andes and at slightly higher than average elevations, so the apparent temperature/productivity relationship is probably not a direct one. Coarse wood productivity accounts for only a fraction of overall tropical forest net primary productivity, but the available data indicate that it is approximately proportional to total above-ground productivity. We speculate that the large variation in wood productivity is unlikely to directly imply an equivalent variation in gross primary production. Instead a shifting balance in carbon allocation between respiration, wood carbon and fine root production seems the more likely explanation.
    Type of Medium: Electronic Resource
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  • 7
    Publication Date: 2024-04-20
    Keywords: Abrupt Climate Changes and Environmental Responses; Accumulation model; ACER; Calendar age; Calendar age, maximum/old; Calendar age, minimum/young; Charcoal; Classical age-modeling approach, CLAM (Blaauw, 2010); DEPTH, sediment/rock; Laguna_Bella_Vista; Sample ID; Type of age model; Unit
    Type: Dataset
    Format: text/tab-separated-values, 92 data points
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  • 8
    Publication Date: 2024-04-20
    Keywords: Abrupt Climate Changes and Environmental Responses; Accumulation model; ACER; Calendar age; Calendar age, maximum/old; Calendar age, minimum/young; Charcoal; Classical age-modeling approach, CLAM (Blaauw, 2010); DEPTH, sediment/rock; Laguna_Chaplin; Sample ID; Type of age model; Unit
    Type: Dataset
    Format: text/tab-separated-values, 149 data points
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  • 9
    Publication Date: 2024-04-20
    Keywords: Abrupt Climate Changes and Environmental Responses; Acalypha; Accumulation model; ACER; Alchornea; Allophylus; Alnus; Alternanthera; Amaioua; Amanoa; Amaranthus; Anadenanthera; Apocynaceae; Arecaceae; Asteraceae; Astronium fraxinifolium; Astronium urundeuva; Bauhinia; Byrsonima/Machaerium; Calendar age; Calendar age, maximum/old; Calendar age, minimum/young; Cecropia; Celtis; cf. Annona; cf. Anthurium; cf. Apeiba tibourbou; cf. Apiaceae; cf. Casearia; cf. Casearia sylvestris; cf. Corchorus; cf. Couratari; cf. Heistera; cf. Hyptis; cf. Lycianthes; cf. Machaerium; cf. Microtea; cf. Polygala; cf. Pouteria; cf. Psychotria; cf. Rapanea; cf. Simarouba amara; cf. Stachytarpheta; cf. Theobroma; cf. Trichilia; cf. Tristerix; cf. Veronia; cf. Zanthoxylum; Chamaesyce; Classical age-modeling approach, CLAM (Blaauw, 2010); Clitoria; Combretaceae/Melastomataceae; Conceveiba cordata; Connarus; Counting, palynology; Croton; Cupania/Matayba; Cuphea carthagenensis; Curatella americana; Cyperaceae; DEPTH, sediment/rock; Didymopanax distractiflorus/D. vinosus; Echinodorus; Elaeoluma; Erythroxylum; Faramea; Flacourtiaceae; Gallesia; Genipa; Heliotropium; Ilex; Isoetes; Laguna_Chaplin; Leguminosae; Ludwigia; Macrolobium; Magonia; Malpighiaceae; Malvaceae; Mauritia/Mauritiella; Meliaceae; Mimosa; Moraceae/Urticaceae; Myrtaceae; Paullinia/Roupala; Peperomia; Piper; Poaceae; Podocarpus; Pollen indeterminata; Polygalaceae; Polygonum acuminatum; Polypodiaceae; Posoqueria latifolia; Randia; Rapanea; Rhamnidium elaeocarpum; Rheedia; Sagittaria; Sample ID; Sapindaceae; Sapium; Sapotaceae; Schizolobium amazonicum; Scoparia; Sebastiania; Senna multijuga; Serjania; Solanum; Spondias; Tapirira guianensis; Trema; Trigonia; Tynanthus; Type of age model; Typha; Unknown; Voyria
    Type: Dataset
    Format: text/tab-separated-values, 6443 data points
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  • 10
    Publication Date: 2024-04-20
    Keywords: Abrupt Climate Changes and Environmental Responses; Acalypha; Accumulation model; ACER; Alchornea; Alnus; Alternanthera; Amanoa; Amaranthaceae; Anadenanthera; Annonaceae; Aparisthmium; Apeiba tibourbou; Apocynaceae; Arecaceae; Asteraceae; Astronium fraxinifolium; Astronium urundeuva; Byrsonima/Dalbergia/Machaerium; Calendar age; Calendar age, maximum/old; Calendar age, minimum/young; Cecropia; Celtis; cf. Anacardiaceae; cf. Annonaceae/Rubiaceae; cf. Aspidosperma; cf. Begonia; cf. Elaeoluma; cf. Faramea; cf. Flacourtiaceae; cf. Polygala; cf. Pouteria; cf. Psychotria; cf. Sclerolobium; cf. Stachytarpheta; cf. Talisia; cf. Trichilia; cf. Vernonia; Chamaesyce; Classical age-modeling approach, CLAM (Blaauw, 2010); Combretaceae/Melastomataceae; Copaifera; Counting, palynology; Croton; Cupania/Matayba; Cuphea; Curatella americana; Cyperaceae; DEPTH, sediment/rock; Didymopanax distractiflorus/D. vinosus; Elaeoluma glabrescens; Eryngium; Erythroxylum; Gallesia; Genipa; Heliocarpus americanus; Hyptis; Ilex; Ipomoea; Isoetes; Laguna_Bella_Vista; Leguminosae; Ludwigia; Macrolobium; Magonia pubescens; Malpighiaceae; Mauritia/Mauritiella; Meliaceae; Meliaceae/Sapotaceae; Mimosa; Moraceae/Urticaceae; Myrsine; Myrtaceae; Paullinia/Roupala; Piper; Poaceae; Podocarpus; Pollen indeterminata; Polygalaceae; Polygonum acuminatum; Polypodiaceae; Posoqueria latifolia; Psittacanthus; Psychotria; Sagittaria; Sample ID; Sapium; Sapotaceae; Sebastiania; Simarouba amara; Solanum; Spondias; Symphonia; Tapirira; Trema; Type of age model; Typha; Unknown
    Type: Dataset
    Format: text/tab-separated-values, 3424 data points
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