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, and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space. While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes, vast areas of the tropics remain understudied. In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity, but it remains among the least known forests in America and is often underrepresented in biodiversity databases. To worsen this situation, human-induced modifications 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, 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

Efeito de composto orgânico na produção da batata-doce (Ipomoea batatas (L.) Lam., na incidência de plantas daninhas e na eficiência do diuron

O experimento foi realizado em condições de campo na Fazenda Experimental da EPAMIG, em Ponte Nova-MG, no período de janeiro a julho de 1995, com o objetivo de avaliar o efeito de doses do composto orgânico produzido com dejeto de suínos na forma líquida e bagaço de canada-açúcar, na produção de batata-doce, cultivar Brazlândia Rosada, na incidência de plantas daninhas e na “eficiência do diuron. Utilizou-se o delineamento em blocos ao acaso, no esquema fatorial, com quatro repetições e quatro testemunhas capinadas, com O, 30, 60 e 90 um de composto orgânico. Avaliaram-se os efeitos das doses O, 30, 60 e 90 t/ha de composto orgânico, combinadas com 0, 800, 1.600 e 2.400 g/ha de diuron. Verificou-se incremento da biomassa fresca das plantas daninhas causado pelo aumento das doses de composto orgânico. A cultura de batata-doce respondeu positivamente ao "aumento das doses do composto orgânico com incremento na produção de raízes extra A, extra, total e comercial. O diuron foi seletivo para a cultura de batata-doce, com melhores resultados nas doses 2.400 g/ha, tanto para produção de raízes quanto para controle de plantas daninhas. Os tratamentos que receberam capina e os tratamentos que apresentaram melhor controle de plantas daninhas pelo diuron tiveram produção semelhante de raízes. Houve correlação negativa entre biomassa fresca das plantas daninhas e as principais características de produção avaliadas da batata-doce.This experiment was carried out under field conditions at the Experimental Farm located in Ponte Nova, state of Minas Gerais, Brazil, during January-July 1995, aiming to evaluate the eífects of doses of organic matter produced with liquid swine manure and crushed-sugar cane on the yield of sweet potato cv. Brazlândia Rosada, weed incidence and diuron eHiciency. A randomized block design in a factorial scheme with four replicates and four weeded controls, with 0, 30, 60 and 90 Um of the organic compound were used. The effects of doses of 0, 30, 60 and 90 t/ha organic matter combined/with 0, 800, l,600 and 2,400 g/ha diuron were evaluated. The weed fresh biomass increased as a Emotion of the increasing doses of organic matter. The sweet potato crop responded positively to the increase of organic matter doses with increment in extra A, extra, total and commercial roots. Diuron was selective for the sweet potato crop with beuer results in the 2,400 g/ha doses for both root yield and weed control. The root yield was similar in the treatments which received wwding and the ones which presented a better control of weeds by the diuron herbicide. There was a negative correlation between weeds and the main yield characteristics of the sweet potato crop

Efeitos de dejeto de suínos na incidência de plantas daninhas e na eficiência do herbicida metribuzin na cultura da batata-doce

O experimento foi realizado em condições de campo, na Fazenda Experimental da EPAMIG, em Ponte Nova-MG, no período de janeiro a julho de 1995, com o objetivo de avaliar o efeito de doses de dejeto de suínos na forma líquida, sobre a produção de batata-doce, cultivar Paulista, na incidência de plantas daninhas e na eficiência de controle de espécies de plantas daninhas pelo metribuzin. Utilizou-se o delineamento em blocos ao acaso, no esquema fatorial, com quatro repetições. Foram avaliados os efeitos das doses 0, 20, 40 e 60 m3 ha-1 de dejeto de suínos combinadas com 0, 300, 600 e 900 g ha-1 de metribuzin. Houve incremento linear de biomassa fresca das plantas daninhas de folhas largas, plantas de folhas estreitas e total de plantas daninhas em função do aumento das doses dejeto de suínos. O metribuzin foi seletivo para a cultura de batata-doce, não sendo observado nenhum sintoma visível de fitotoxicidade à cultura e eficiente no controle das principais plantas daninhas presentes na área. A produção máxima de raízes comerciais (22,94 t ha-1) foi obtida com o metribuzin na dose 810,17 g ha-1. Isto representou cerca de 89% superior ao peso obtido pela testemunha sem tratos culturais. Esta produtividade foi semelhante àquela observada nos tratamentos que receberam três cultivos. As plantas daninhas interferiram negativamente nas principais características avaliadas de produção da batata-doce. A cultura da batata-doce respondeu positivamente a adubação com dejeto líquido de suínos, com aumento linear da produção de raízes das classes extra A, comercial e total. Verificou-se também que houve correlação negativa entre plantas daninhas e as principais características de produção da cultura de batata-doce.This study was carried out under field conditions during the period from January to July 1995 at EPAMIG Experimental Farm, in Ponte Nova/MG, aiming to evaluate the effects liquid swine manure doses on the yield of sweet potato cv Paulista, weed incidence and the weed control efficiency by metribuzin. A randomized block design in the factorial scheme with four replication was used. The effects of 0, 20, 40 and 60 m3 ha-1 doses of swine manure combined with metribuzin 0, 300, 600 and 900 g ha-1 and four weeded controls fertilized with 0, 20, 40 and 60 m3 ha-1 of swine manure were evaluated. A linear increment in fresh biomass was observed on large leaves weeds, narrow leaves and total weeds as a function of the increase in swine manure doses. Metribuzin was selective for the sweet potato crop, and no apparent sign of toxicity to this culture was observed. The maximum commercial root yield was obtained using 810.17 g ha-1 of ametribuzin dose (22.94 t ha-1, approximately 89% above the weight obtained by the control without cultivation tracts). This productivity was similar to that observed in the treatments which received three cultivations. The weeds interfered negatively with the main characteristics evaluated in the sweet potato yield. The sweet potato crop answered positively to the fertilization with liquid swine manure presenting a linear increase in root production of the extra A, commercial and total classes. Also it was verified the occurrence of a negative correlation between weeds and the main yield characteristics in the sweet potato cropping