Trajectory and digital reconstitution of a canoe of Paulista Museum - USP

In this article, we intend to elaborate the exhibition trajectory of a canoe’s bow belonging to Paulista Museum collection from its entry into the institution in 1924 to the present day, reflecting on the construction of the monsoon memory in the museum along the time. The interdisciplinary activities carried out among Paulista Museum - USP, the Plant Anatomy Laboratory of the Institute of Biosciences - USP and the Naval Engineering Department of the Polytechnic School - USP will also be approached in order to better understand the constitution of the canoe, now musealized, through the results obtained from the historical research, the conservation works, the processes of wood anatomical identification and short-range photogrammetry.  Nesse artigo, pretende-se elaborar a trajetória expositiva do beque de proa de uma canoa pertencente ao acervo do Museu Paulista desde seu ingresso na instituição, em 1924, até os dias atuais, refletindo sobre a construção da memória das monções no museu ao longo do tempo. Também serão abordadas as atividades interdisciplinares realizadas entre o Museu Paulista, o Laboratório de Anatomia Vegetal do Instituto de Biociências – USP e o Departamento de Engenharia Naval da Escola Politécnica – USP, a fim de melhor compreender a constituição do canoão, agora musealizado, por meio dos resultados obtidos a partir da pesquisa histórica, dos trabalhos de conservação, dos processos de identificação anatômica da madeira e de fotogrametria de curto alcance

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Assessment of climate change impacts in the last 500 years through dendroclimatological and isotopic studies from trees at the Parque Nacional Cavernas do Peruaçu region

As mudanças climáticas causam grandes impactos nas florestas mundiais e, consequentemente nos ciclos biogeoquímicos. Entender as consequências dessas alterações antrópicas na região tropical é um desafio já que os registros instrumentais são limitados a poucas décadas. Para isso, os anéis de crescimento fornecem excelentes registros com resolução anual de variações climáticas atuais e anteriores às alterações humanas, mas poucas cronologias robustas para inferências climáticas são disponíveis nos trópicos. Assim, esta tese explorou um novo local e uma nova espécie para estudos dendrocronológicos visando avaliar o efeito de mudanças climáticas em florestas sazonalmente secas no centro leste do Brasil, um dos hot spots de aumento de temperatura na região tropical. Nesta tese foi: testada uma nova metodologia para aprimorar a identificação dos anéis de crescimento; construídas cronologias da largura e de isótopos estáveis de oxigênio de Amburana cearensis no Parque Nacional Cavernas do Peruaçu (PNCP); as quais foram analisadas em conjunto com outra espécie da Mata Seca do PNCP e espeleotemas da mesma região para avaliar os efeitos de mudanças no clima no crescimento hoje e 500 anos atrás. Com cronologias perfeitamente datadas e com forte sinal climático, vimos que as árvores de A. cearensis e C. fissilis crescem reguladas pela quantidade de chuva na estação de crescimento, e as condições de alta demanda evaporativa nos últimos anos ainda não afetam o crescimento dessas populações. Isso é corroborado com dados de amostras subfósseis e espeleotemas que mostram que eventos de aumento abrupto na demanda evaporativa durante a Pequena Idade do Gelo também não afetaram o crescimento de A. cearensis. Esses resultados poderão auxiliar cientistas a desenvolver cronologias com espécies de difícil interpretação da anatomia da madeira; auxiliar no desenvolvimento de novas cronologias tropicais; e entender os efeitos das mudanças climáticas no crescimento de espécies de matas tropicais secas. Os dados produzidos também podem apoiar o desenvolvimento de modelos globais de resposta da vegetação para entender o efeito de mudanças climáticas no funcionamento das florestas sazonalmente secas tropicais.Climate change affects forests and biogeochemical cycles globaly. Assessing the effects in tropical forests is chalenging because instrumental records are constrained. Thus, tree rings proxies offer excelent anually resolved records of recent and pre-industrial climate variability, however few robusts chronologies are available for climate inferences in the tropics. Therefore, this thesis explored a new site in central-eastern Brazil, a hot spot of global warming in the tropics and a new tree species for dendrochronological investigations about the effects of climate change in a Seasonally Dry Tropical Forest (SDTF). In this work: we tested a new method for improving tree-ring identification; established Amburana cearensis tree-ring width and oxygen isotopes ratio (δ18O) chronologies at the National Park Cavernas do Peruaçu (PNCP); which were analysed with records of another representative species in the SDTF and speleothems to assess the effects of climate change in tree growth now and 500 year ago. Using the perfectly dated chronologies, with strong climate signal, we observed that trees of A. cearensis and C. fissilis grow regulated by rainfall amount during the growing season and the high evaporative demands in the recent years do not affect their growth yet. These findings are corroborated by data from subfossil samples and speleothem records that show another period of abrupt increase in evaporative demands during the Little Ice Age that did not leave traces in Amburana cearensis trees growth. Our results can aid scientists to develop new tree-ring chronologies with species that have complex wood anatomy; aid the development of new tropical chronologies; and understand the effects of climate change in SDTF trees growth. The data produced can also support the development of global vegetation models of SDTF responses to climate change