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

Comparação de modelos não lineares mistos para análise de curva de lactação em caprinos leiteiros

Knowledge on lactation curve is essential to validate the genetics, nutritional and reproductive adopted management, since it allows the evaluation of animals before the end of yielding, saving resources. By comparing the shape of curves among different groups of animals (genetic group, ages, herds and other treatments of interest), it is possible to access the effectiveness of the lactations, thus providing information for selection of the more productive groups. The study of lactation curves can be more attractive by using nonlinear mixed models since it is possible to make inferences when milk collections may be irregular in time; when there is incomplete group structure; when the adjacent evaluations are more closely correlated than the others; and when the response of individuals as a function of time has increasing variance. We aimed to fit and compare fifteen nonlinear mixed models to describe lactation curve of dairy goats as well as to estimate heritability and genetic correlations for the parameters of the selected model. The dataset was provided by the Caprine sector of the Universidade Federal de Viçosa. After checking the data consistency, we used 3,856 milk yield test-day records from 535 first lactations of Saanen and Alpine goats (including crosses). In order to identify the best nonlinear mixed model, different information criteria (AIC, AICc, AICu, BIC, cAIC and AIC3) were used here. Based on these criteria, the Wood model presented the best goodness of fit, being their parameters used as phenotypic observations for genetic evaluation of lactation curves. Additionally, the Wood model was integrated to calculate the total milk yield (TMY) that was also included in the genetic analysis. For this, a multi-trait mixed model was fitted by considering as traits the TMY and the a, b and c parameters of Wood model. The heritability estimates for TMY, a, b and c were 0.31, 0.17, 0.11 and 0,08, respectively. The genetic correlation between TMY and the parameters a, b and c were, 0.28, 0.22 and 0.17. Based on these results, the trait TMY can be indicated as selection criterion in dairy goats breeding programs, however the parameters of Wood model are not recommended to this aim.O conhecimento sobre a curva de lactação é essencial para validar o manejo genético, nutricional e reprodutiva adotada, por permitir a avaliação de animais precocemente, gerando economia. Ao comparar a forma das curvas entre diferentes grupos de animais (grupo genético, idades, rebanhos), é possível avaliar a eficácia das lactações, proporcionando informações para a seleção dos grupos mais produtivos. Torna-se mais interessante o estudo das curvas de lactação ao usar modelos mistos não lineares, pois é possível fazer inferências mesmo com coletas de leite irregulares; quando há estrutura de grupo incompleta; quando as avaliações adjacentes estão mais correlacionadas do que as demais; e quando a resposta dos indivíduos em função do tempo tem variação crescente. Pretedeu-se ajustar e comparar modelos não lineares mistos para descrever a curva de lactação de cabras leiteiras, bem como estimar herdabilidade e correlações genéticas para os parâmetros do modelo selecionado. Os dados são do setor caprinos da Universidade Federal de Viçosa, após verificar a consistência dos dados, utilizou-se 3.856 registros de produção de leite das 535 primeiras lactações de Saanen e cabras alpinas (incluindo cruzados). Para identificar o melhor modelo, utilizou-se diferentes critérios de informação (AIC, AICc, AICu, BIC, cAIC e AIC3). Com base nos critérios, o modelo de Wood apresentou a melhor qualidade de ajuste, sendo seus parâmetros utilizados como observações fenotípicas para avaliação genética de curvas de lactação. Além disso, o modelo de Wood foi integrado para calcular a produção total do leite (TMY) que também foi incluído na análise genética. Para isso, um modelo misto multicaracterístico foi ajustado ao considerar como características a produção total e os parâmetros a, b e c do modelo de Wood. As estimativas de herdabilidade para TMY, a, b e c foram 0,31, 0,17, 0,11 e 0,08, respectivamente. A correlação genética entre TMY e os parâmetros a, b e c foram 0,28, 0,22 e 0,17. Com base nesses resultados, a característica TMY pode ser critério de seleção porém, os parâmetros do modelo de Wood não são recomendados para este fim.Coordenação de Aperfeiçoamento de Pessoal de Nível Superio

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

Genetic evaluation of lactation persistency and total milk yield in dairy goats

Lactation persistency (LP) has been neglected over time in genetic evaluations of dairy goats. The main reason for this is the difficulty to infer about the lactation curve shape. However, some lactations models such as Wood seem to be appropriate to provide persistency estimates under biological viewpoints. The aim of this study was to fit the Wood lactation model as well as to calculate and evaluate LP as selection criteria in dairy goat breeding programs through genetic parameters estimates. A total of 23,265 first lactation test day milk yield observations from 900 animals were used. The Wood random regression model was primarily fitted to estimate the lactation curve parameters (a, b and c), and then LP and total milk yield (TMY). Posteriorly, a multi-trait animal model was fitted considering simultaneously LP and TMY. The heritability estimates were 0.31 and 0.04 for TMY and LP, respectively. Based on the low LP heritability, selection based only on this trait might be inefficient. In conclusion, the results of this study suggests that selecting for high milk yields might result in high persistency since the genetic correlation between LP and TMY was moderate (0.39)

Bayesian Models combining Legendre and B-spline polynomials for genetic analysis of multiple lactations in Gyr cattle

We aimed with this study to combine Legendre polynomials (LEG) and linear B-splines (BSP) to describe simultaneously the first and second lactation of Gyr dairy cattle under a multiple-trait random regression models (MTRRM) framework. Additionally we proposed the application of self-organizing map to define the classes of residual variances under these models. A total of 26,438 and 23,892 milk yield test-day records were used, respectively, for the first and second lactations of 3253 Gyr cows. Two preliminary MTRRM analyses considering 10 residual classes were performed: the first one was based on LEG for systematic and random effects for both lactations; and the second one was based on BSP. Three classes were defined by using a self-organizing map: from 6 to 35; 36–185 and 186–305 days in milk. After definition of residual variance classes, a total of 16 MTRRM combining LEG and BSP were compared. The MTRRM based on BSP to describe the systematic effects of the first and second lactation, BSP to describe the random effects of the first lactation and LEG to describe the random effects of the second lactation (BSP-BSP-BSP-LEG) outperformed all other models. From the BSP-BSP-BSP-LEG model, heritability estimates for milk yield over time ranged from 0.1107 to 0.2902, and from 0.2036 to 0.3967, for the first and second lactation, respectively. In general, additive genetic correlation estimates between days in milk within each lactation and between lactations had medium magnitude (mean of genetic correlations were 0.6630, 0.6226 and 0.4749 for the first, second and between both lactations, respectively). We concluded that combining different functions under a MTRRM framework is a feasible alternative for genetic modeling of lactation curves in Gyr dairy cattle

NEOTROPICAL XENARTHRANS: a data set of occurrence of xenarthran species in the Neotropics

Xenarthrans—anteaters, sloths, and armadillos—have essential functions for ecosystem maintenance, such as insect control and nutrient cycling, playing key roles as ecosystem engineers. Because of habitat loss and fragmentation, hunting pressure, and conflicts with domestic dogs, these species have been threatened locally, regionally, or even across their full distribution ranges. The Neotropics harbor 21 species of armadillos, 10 anteaters, and 6 sloths. Our data set includes the families Chlamyphoridae (13), Dasypodidae (7), Myrmecophagidae (3), Bradypodidae (4), and Megalonychidae (2). We have no occurrence data on Dasypus pilosus (Dasypodidae). Regarding Cyclopedidae, until recently, only one species was recognized, but new genetic studies have revealed that the group is represented by seven species. In this data paper, we compiled a total of 42,528 records of 31 species, represented by occurrence and quantitative data, totaling 24,847 unique georeferenced records. The geographic range is from the southern United States, Mexico, and Caribbean countries at the northern portion of the Neotropics, to the austral distribution in Argentina, Paraguay, Chile, and Uruguay. Regarding anteaters, Myrmecophaga tridactyla has the most records (n = 5,941), and Cyclopes sp. have the fewest (n = 240). The armadillo species with the most data is Dasypus novemcinctus (n = 11,588), and the fewest data are recorded for Calyptophractus retusus (n = 33). With regard to sloth species, Bradypus variegatus has the most records (n = 962), and Bradypus pygmaeus has the fewest (n = 12). Our main objective with Neotropical Xenarthrans is to make occurrence and quantitative data available to facilitate more ecological research, particularly if we integrate the xenarthran data with other data sets of Neotropical Series that will become available very soon (i.e., Neotropical Carnivores, Neotropical Invasive Mammals, and Neotropical Hunters and Dogs). Therefore, studies on trophic cascades, hunting pressure, habitat loss, fragmentation effects, species invasion, and climate change effects will be possible with the Neotropical Xenarthrans data set. Please cite this data paper when using its data in publications. We also request that researchers and teachers inform us of how they are using these data

NEOTROPICAL CARNIVORES: a data set on carnivore distribution in the Neotropics

Mammalian carnivores are considered a key group in maintaining ecological health and can indicate potential ecological integrity in landscapes where they occur. Carnivores also hold high conservation value and their habitat requirements can guide management and conservation plans. The order Carnivora has 84 species from 8 families in the Neotropical region: Canidae; Felidae; Mephitidae; Mustelidae; Otariidae; Phocidae; Procyonidae; and Ursidae. Herein, we include published and unpublished data on native terrestrial Neotropical carnivores (Canidae; Felidae; Mephitidae; Mustelidae; Procyonidae; and Ursidae). NEOTROPICAL CARNIVORES is a publicly available data set that includes 99,605 data entries from 35,511 unique georeferenced coordinates. Detection/non-detection and quantitative data were obtained from 1818 to 2018 by researchers, governmental agencies, non-governmental organizations, and private consultants. Data were collected using several methods including camera trapping, museum collections, roadkill, line transect, and opportunistic records. Literature (peer-reviewed and grey literature) from Portuguese, Spanish and English were incorporated in this compilation. Most of the data set consists of detection data entries (n = 79,343; 79.7%) but also includes non-detection data (n = 20,262; 20.3%). Of those, 43.3% also include count data (n = 43,151). The information available in NEOTROPICAL CARNIVORES will contribute to macroecological, ecological, and conservation questions in multiple spatio-temporal perspectives. As carnivores play key roles in trophic interactions, a better understanding of their distribution and habitat requirements are essential to establish conservation management plans and safeguard the future ecological health of Neotropical ecosystems. Our data paper, combined with other large-scale data sets, has great potential to clarify species distribution and related ecological processes within the Neotropics. There are no copyright restrictions and no restriction for using data from this data paper, as long as the data paper is cited as the source of the information used. We also request that users inform us of how they intend to use the data

Brazilian Flora 2020: Leveraging the power of a collaborative scientific network

International audienceThe shortage of reliable primary taxonomic data limits the description of biological taxa and the understanding of biodiversity patterns and processes, complicating biogeographical, ecological, and evolutionary studies. This deficit creates a significant taxonomic impediment to biodiversity research and conservation planning. The taxonomic impediment and the biodiversity crisis are widely recognized, highlighting the urgent need for reliable taxonomic data. Over the past decade, numerous countries worldwide have devoted considerable effort to Target 1 of the Global Strategy for Plant Conservation (GSPC), which called for the preparation of a working list of all known plant species by 2010 and an online world Flora by 2020. Brazil is a megadiverse country, home to more of the world's known plant species than any other country. Despite that, Flora Brasiliensis, concluded in 1906, was the last comprehensive treatment of the Brazilian flora. The lack of accurate estimates of the number of species of algae, fungi, and plants occurring in Brazil contributes to the prevailing taxonomic impediment and delays progress towards the GSPC targets. Over the past 12 years, a legion of taxonomists motivated to meet Target 1 of the GSPC, worked together to gather and integrate knowledge on the algal, plant, and fungal diversity of Brazil. Overall, a team of about 980 taxonomists joined efforts in a highly collaborative project that used cybertaxonomy to prepare an updated Flora of Brazil, showing the power of scientific collaboration to reach ambitious goals. This paper presents an overview of the Brazilian Flora 2020 and provides taxonomic and spatial updates on the algae, fungi, and plants found in one of the world's most biodiverse countries. We further identify collection gaps and summarize future goals that extend beyond 2020. Our results show that Brazil is home to 46,975 native species of algae, fungi, and plants, of which 19,669 are endemic to the country. The data compiled to date suggests that the Atlantic Rainforest might be the most diverse Brazilian domain for all plant groups except gymnosperms, which are most diverse in the Amazon. However, scientific knowledge of Brazilian diversity is still unequally distributed, with the Atlantic Rainforest and the Cerrado being the most intensively sampled and studied biomes in the country. In times of “scientific reductionism”, with botanical and mycological sciences suffering pervasive depreciation in recent decades, the first online Flora of Brazil 2020 significantly enhanced the quality and quantity of taxonomic data available for algae, fungi, and plants from Brazil. This project also made all the information freely available online, providing a firm foundation for future research and for the management, conservation, and sustainable use of the Brazilian funga and flora