27 research outputs found

    Sampling effort and information quality provided by rare and common species in estimating assemblage structure

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    Reliable biological assessments are essential to answer ecological and management questions but require well-designed studies and representative sample sizes. However, large sampling effort is rarely possible, because it demands large financial resources and time, restricting the number of sites sampled, the duration of the study and the sampling effort at each site. In this context, we need methods and protocols allowing cost-effective surveys that would, consequently, increase the knowledge about how biodiversity is distributed in space and time. Here, we assessed the minimal sampling effort required to correctly estimate the assemblage structure of stream insects sampled in near-pristine boreal and subtropical regions. We used five methods grouped into two different approaches. The first approach consisted of the removal of individuals 1) randomly or 2) based on a count threshold. The second approach consisted of simplification in terms of 1) sequential removal from rare to common species; 2) sequential removal from common to rare species; and 3) random species removal. The reliability of the methods was assessed using Procrustes analysis, which indicated the correlation between a reduced matrix (after removal of individuals or species) and the complete matrix. In many cases, we found a strong relationship between ordination patterns derived from presence/absence data (the extreme count threshold of a single individual) and those patterns derived from abundance data. Also, major multivariate patterns derived from the complete data matrices were retained even after the random removal of more than half of the individuals. Procrustes correlation was generally high ( > 0.8), even with the removal of 50% of the species. Removal of common species produced lower correlation than removal of rare species, indicating higher importance of the former to estimate resemblance between assemblages. Thus, we conclude that sampling designs can be optimized by reducing the sampling effort at a site. We recommend that such efforts saved should be redirected to increase the number of sites studied and the duration of the studies, which is essential to encompass larger spatial, temporal and environmental extents, and increase our knowledge of biodiversity.peerReviewe

    Sperm Oxidative Stress Is Detrimental to Embryo Development: A Dose-Dependent Study Model and a New and More Sensitive Oxidative Status Evaluation

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    Our study aimed to assess the impact of sperm oxidative stress on embryo development by means of a dose-dependent model. In experiment 1, straws from five bulls were subjected to incubation with increasing H2O2 doses (0, 12.5, 25, and 50 ΌM). Motility parameters were evaluated by Computed Assisted System Analysis (CASA). Experiment 2 was designed to study a high (50 ΌM) and low dose (12.5 ΌM) of H2O2 compared to a control (0 ΌM). Samples were incubated and further used for in vitro fertilization. Analyses of motility (CASA), oxidative status (CellROX green and 2’-7’ dichlorofluorescein diacetate), mitochondrial potential (JC-1), chromatin integrity (AO), and sperm capacitation status (chlortetracycline) were performed. Embryos were evaluated based on fast cleavage (30 h.p.i.), cleavage (D=3), development (D=5), and blastocyst rates (D=8). We observed a dose-dependent deleterious effect of H2O2 on motility and increase on the percentages of positive cells for CellROX green, capacitated sperm, and AO. A decrease on cleavage and blastocyst rates was observed as H2O2 increased. Also, we detected a blockage on embryo development. We concluded that sperm when exposed to oxidative environment presents impaired motility traits, prooxidative status, and premature capacitation; such alterations resulting in embryo development fail

    Sperm Oxidative Stress Is Detrimental to Embryo Development: A Dose-Dependent Study Model and a New and More Sensitive Oxidative Status Evaluation

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    Our study aimed to assess the impact of sperm oxidative stress on embryo development by means of a dose-dependent model. In experiment 1, straws from five bulls were subjected to incubation with increasing H 2 O 2 doses (0, 12.5, 25, and 50 M). Motility parameters were evaluated by Computed Assisted System Analysis (CASA). Experiment 2 was designed to study a high (50 M) and low dose (12.5 M) of H 2 O 2 compared to a control (0 M). Samples were incubated and further used for in vitro fertilization. Analyses of motility (CASA), oxidative status (CellROX green and 2'-7' dichlorofluorescein diacetate), mitochondrial potential (JC-1), chromatin integrity (AO), and sperm capacitation status (chlortetracycline) were performed. Embryos were evaluated based on fast cleavage (30 h.p.i.), cleavage ( = 3), development ( = 5), and blastocyst rates ( = 8). We observed a dose-dependent deleterious effect of H 2 O 2 on motility and increase on the percentages of positive cells for CellROX green, capacitated sperm, and AO. A decrease on cleavage and blastocyst rates was observed as H 2 O 2 increased. Also, we detected a blockage on embryo development. We concluded that sperm when exposed to oxidative environment presents impaired motility traits, prooxidative status, and premature capacitation; such alterations resulting in embryo development fail

    A comparative analysis reveals weak relationships between ecological factors and beta diversity of stream insect metacommunities at two spatial levels.

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    The hypotheses that beta diversity should increase with decreasing latitude and increase with spatial extent of a region have rarely been tested based on a comparative analysis of multiple datasets, and no such study has focused on stream insects. We first assessed how well variability in beta diversity of stream insect metacommunities is predicted by insect group, latitude, spatial extent, altitudinal range, and dataset properties across multiple drainage basins throughout the world. Second, we assessed the relative roles of environmental and spatial factors in driving variation in assemblage composition within each drainage basin. Our analyses were based on a dataset of 95 stream insect metacommunities from 31 drainage basins distributed around the world. We used dissimilarity-based indices to quantify beta diversity for each metacommunity and, subsequently, regressed beta diversity on insect group, latitude, spatial extent, altitudinal range, and dataset properties (e.g., number of sites and percentage of presences). Within each metacommunity, we used a combination of spatial eigenfunction analyses and partial redundancy analysis to partition variation in assemblage structure into environmental, shared, spatial, and unexplained fractions. We found that dataset properties were more important predictors of beta diversity than ecological and geographical factors across multiple drainage basins. In the within-basin analyses, environmental and spatial variables were generally poor predictors of variation in assemblage composition. Our results revealed deviation from general biodiversity patterns because beta diversity did not show the expected decreasing trend with latitude. Our results also call for reconsideration of just how predictable stream assemblages are along ecological gradients, with implications for environmental assessment and conservation decisions. Our findings may also be applicable to other dynamic systems where predictability is low

    Photography-based taxonomy is inadequate, unnecessary, and potentially harmful for biological sciences

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    The question whether taxonomic descriptions naming new animal species without type specimen(s) deposited in collections should be accepted for publication by scientific journals and allowed by the Code has already been discussed in Zootaxa (Dubois & NemĂ©sio 2007; Donegan 2008, 2009; NemĂ©sio 2009a–b; Dubois 2009; Gentile & Snell 2009; Minelli 2009; Cianferoni & Bartolozzi 2016; Amorim et al. 2016). This question was again raised in a letter supported by 35 signatories published in the journal Nature (Pape et al. 2016) on 15 September 2016. On 25 September 2016, the following rebuttal (strictly limited to 300 words as per the editorial rules of Nature) was submitted to Nature, which on 18 October 2016 refused to publish it. As we think this problem is a very important one for zoological taxonomy, this text is published here exactly as submitted to Nature, followed by the list of the 493 taxonomists and collection-based researchers who signed it in the short time span from 20 September to 6 October 2016

    Pervasive gaps in Amazonian ecological research

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    Pervasive gaps in Amazonian ecological research

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    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

    AI is a viable alternative to high throughput screening: a 318-target study

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    : High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNetÂź convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNetÂź model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery
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