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

Análise da variabilidade genética aditiva de características de crescimento na raça Nelore Additive genetic variability analysis in the growth characteristics of Nellore breed

Foram utilizados dados de cinqüenta e um rebanhos participantes do Programa de Melhoramento Genético da Raça Nelore (PMGRN), distribuídos nos estados de Goiás (GO), Mato Grosso do Sul (MS), Mato Grosso (MT), Minas Gerais (MG), São Paulo (SP), Maranhão (MA) e Bahia (BA). Foram obtidas estimativas de parâmetros genéticos para os pesos padronizados aos 120 (P120), 455 (P455) e 550 (P550) dias de idade. Análises unicaráter e bicaráter foram realizadas por modelo animal usando o aplicativo MTDFREML. Para P120 foi utilizado um modelo que incluiu como efeitos fixos, grupo de contemporâneos e classe de idade da vaca ao parto, e como aleatórios, os efeitos genéticos direto, materno e de ambiente permanente da vaca. Para P455 e P550, o modelo utilizado incluiu os mesmos efeitos fixos e o efeito genético direto do animal. ANas análises unicaráter, as estimativas de herdabilidade direta foram 0,29, 0,51 e 0,47 para P120, P455 e P550, respectivamente. Nas análises bicaráter, observaram-se coeficientes de herdabilidade direta de 0,50 e 0,58 para P120, 0,50 e 0,53 para P455 e 0,44 e 0,49 para P550. As correlações genéticas estimadas entre P120 e P455, P120 e P550 e P455 e P550, foram 0,92, 0,93 e 0,96, respectivamente. As estimativas de herdabilidade obtidas para P455 e as correlações genéticas deste peso com P120 e P550 sugerem que a avaliação genética pode ser feita aos 15 meses de idade em substituição aos 18 meses.<br>The data were obtained from 51 herds to participate in the Nelore Catttle Breeding Program (NCBP) from the states of Goiás (GO), Mato Grosso do Sul (MS), Mato Grosso (MT), Minas Gerais (MG), São Paulo (SP), Maranhão (MA) and Bahia (BA). Were used to estimative genetic parameters for standardized weights at 120 (P120), 455 (P455) and 550 (550) days of age. Univariate and bivariate analysis were performed by animal model using MTDFREML program. For P120 was used a model that included contemporary groups and cow age at calving as fixed effects, and direct genetic, maternal genetic and permanent environment effects as random effects. For P455 and P550 were utilized the same model but without maternal direct and permanent environment effects. The estimates of heritability direct from univariate analysis were: 0.29, 0.51 and 0.47 for P120, P455 and P550, respectively. In the bivariate analyses the direct heritability values were of high magnitude. The genetic correlation between P120 and P455, P120 and P550 and P455 and P550 were 0.92, 0.93 and 0.96, respectively. The values of the heritability coefficients estimated for the trait P455 and genetic correlation that characteristic with others indicate that the genetic evaluation could be made at the 15 months of age