Análise de crescimento e assimilação de nitrogênio em plantas de milho (Zea mays L.)

Plantas de milho (Zea mays L.) apresentam elevada demanda por nitrogênio para seu crescimento e desenvolvimento. Neste trabalho objetivou-se avaliar respostas de crescimento em plantas de milho (Z. mays L.) submetidas a diferentes doses de nitrato e glutamina. Foram utilizadas sementes das cultivares BRS Planalto e BR5202 Pampa, semeadas em vasos de polietileno aclimatadas em casa de vegetação, onde aos 10 dias após a emergência iniciaram-se os tratamentos com nitrato e glutamina em diferentes doses (0,00; 0,10; 10,00 mM) fornecidas em cinco parcelas. Aos 30 dias após a emergência foi realizada uma única coleta do material. Utilizou-se o delineamento estatístico inteiramente ao acaso, com seis repetições. As características de crescimento analisadas demonstraram sempre maiores valores para as maiores concentrações das fontes de nitrogênio utilizadas. A cultivar BR5202 Pampa respondeu melhor em relação às características de crescimento analisadas

Efeito da salinidade na germinação de sementes de pinhão manso

Objetivou-se, na presente pesquisa, avaliar o comportamento da germinação em sementes de pinhão manso (Jatropha curcas L.) quando submetidas a níveis crescentes de salinidade da água utilizada para embebição. Para tanto, o teste de geminação foi realizado com quatro repetições de 25 sementes para cada tratamento. Os tratamentos foram dispostos em delineamento inteiramente casualizado em esquema fatorial 6 x 2 (seis níveis de salinidade da água 0,6; 2,1; 3,6; 5,1; 6,6 e 8,1 dS m-1, e duas procedências de sementes, nativas dos municípios de Patos e Itaporanga, PB). A semeadura foi realizada em sistema rolo (papel germitest), umedecidos com volumes da solução salina (mL), equivalentes a 2,5 vezes o peso do papel seco (g). Os tratamentos foram instalados em câmara de germinação do tipo BOD (Biological Organism Development) sob uma temperatura de 25 ºC em regime de escuro. Avaliou-se a germinação com contagens diárias, do 1º ao 14º dia do início do teste. Constatou-se um comprometimento no desempenho germinativo das sementes devido a condições de aumento da salinidade, porém as sementes oriundas de plantas nativas do município de Patos, mostraram-se mais tolerantes

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

Análise de crescimento e assimilação de nitrogênio em plantas de milho (Zea mays L.)

Plantas de milho (Zea mays L.) apresentam elevada demanda por nitrogênio para seu crescimento e desenvolvimento. Neste trabalho objetivou-se avaliar respostas de crescimento em plantas de milho (Z. mays L.) submetidas a diferentes doses de nitrato e glutamina. Foram utilizadas sementes das cultivares BRS Planalto e BR5202 Pampa, semeadas em vasos de polietileno aclimatadas em casa de vegetação, onde aos 10 dias após a emergência iniciaram-se os tratamentos com nitrato e glutamina em diferentes doses (0,00; 0,10; 10,00 mM) fornecidas em cinco parcelas. Aos 30 dias após a emergência foi realizada uma única coleta do material. Utilizou-se o delineamento estatístico inteiramente ao acaso, com seis repetições. As características de crescimento analisadas demonstraram sempre maiores valores para as maiores concentrações das fontes de nitrogênio utilizadas. A cultivar BR5202 Pampa respondeu melhor em relação às características de crescimento analisadas

Análise de crescimento e assimilação de nitrogênio em plantas de milho, Zea mays L.

Corn plants (Zea mays L.) have high demand for nitrogen for their growth and development. In this study aimed to evaluate growth responses in corn plants (Zea mays L.) exposed to different doses of nitrate and glutamine. Were used seed of BRS Plateau and BR5202 Pampa, sown in polyethylene pots acclimatized in a greenhouse, where at 10 days after emergence began treatments with nitrate and glutamine in different doses (0.00, 0.10; 10.00 mM) provided in five installments. At 30 days after emergence was made a single collection of material. We used a completely randomized statistical delineation with six replications. Growth characteristics analyzed always showed higher values for higher concentrations of nitrogen sources used. The cultivar BR5202 Pampa responded better in relation to growth traits analyzed.Plantas de milho (Zea mays L.) apresentam elevada demanda por nitrogênio para seu crescimento e desenvolvimento. Neste trabalho objetivou-se avaliar respostas de crescimento em plantas de milho (Z. mays L.) submetidas a diferentes doses de nitrato e glutamina. Foram utilizadas sementes das cultivares BRS Planalto e BR5202 Pampa, semeadas em vasos de polietileno aclimatadas em casa de vegetação, onde aos 10 dias após a emergência iniciaram-se os tratamentos com nitrato e glutamina em diferentes doses (0,00; 0,10; 10,00 mM) fornecidas em cinco parcelas. Aos 30 dias após a emergência foi realizada uma única coleta do material. Utilizou-se o delineamento estatístico inteiramente ao acaso, com seis repetições. As características de crescimento analisadas demonstraram sempre maiores valores para as maiores concentrações das fontes de nitrogênio utilizadas. A cultivar BR5202 Pampa respondeu melhor em relação às características de crescimento analisadas

Seminário de Dissertação (2024)

Página da disciplina de Seminário de Dissertação (MPPP, UFPE, 2022) Lista de participantes == https://docs.google.com/spreadsheets/d/1mrULe1y04yPxHUBaF50jhaM1OY8QYJ3zva4N4yvm198/edit#gid=

NEOTROPICAL ALIEN MAMMALS: a data set of occurrence and abundance of alien mammals in the Neotropics

Biological invasion is one of the main threats to native biodiversity. For a species to become invasive, it must be voluntarily or involuntarily introduced by humans into a nonnative habitat. Mammals were among first taxa to be introduced worldwide for game, meat, and labor, yet the number of species introduced in the Neotropics remains unknown. In this data set, we make available occurrence and abundance data on mammal species that (1) transposed a geographical barrier and (2) were voluntarily or involuntarily introduced by humans into the Neotropics. Our data set is composed of 73,738 historical and current georeferenced records on alien mammal species of which around 96% correspond to occurrence data on 77 species belonging to eight orders and 26 families. Data cover 26 continental countries in the Neotropics, ranging from Mexico and its frontier regions (southern Florida and coastal-central Florida in the southeast United States) to Argentina, Paraguay, Chile, and Uruguay, and the 13 countries of Caribbean islands. Our data set also includes neotropical species (e.g., Callithrix sp., Myocastor coypus, Nasua nasua) considered alien in particular areas of Neotropics. The most numerous species in terms of records are from Bos sp. (n = 37,782), Sus scrofa (n = 6,730), and Canis familiaris (n = 10,084); 17 species were represented by only one record (e.g., Syncerus caffer, Cervus timorensis, Cervus unicolor, Canis latrans). Primates have the highest number of species in the data set (n = 20 species), partly because of uncertainties regarding taxonomic identification of the genera Callithrix, which includes the species Callithrix aurita, Callithrix flaviceps, Callithrix geoffroyi, Callithrix jacchus, Callithrix kuhlii, Callithrix penicillata, and their hybrids. This unique data set will be a valuable source of information on invasion risk assessments, biodiversity redistribution and conservation-related research. There are no copyright restrictions. Please cite this data paper when using the data in publications. We also request that researchers and teachers inform us on how they are using the data