Estimates of live-tree carbon stores in the Pacific Northwest are sensitive to model selection

<p>Abstract</p> <p>Background</p> <p>Estimates of live-tree carbon stores are influenced by numerous uncertainties. One of them is model-selection uncertainty: one has to choose among multiple empirical equations and conversion factors that can be plausibly justified as locally applicable to calculate the carbon store from inventory measurements such as tree height and diameter at breast height (DBH). Here we quantify the model-selection uncertainty for the five most numerous tree species in six counties of northwest Oregon, USA.</p> <p>Results</p> <p>The results of our study demonstrate that model-selection error may introduce 20 to 40% uncertainty into a live-tree carbon estimate, possibly making this form of error the largest source of uncertainty in estimation of live-tree carbon stores. The effect of model selection could be even greater if models are applied beyond the height and DBH ranges for which they were developed.</p> <p>Conclusions</p> <p>Model-selection uncertainty is potentially large enough that it could limit the ability to track forest carbon with the precision and accuracy required by carbon accounting protocols. Without local validation based on detailed measurements of usually destructively sampled trees, it is very difficult to choose the best model when there are several available. Our analysis suggests that considering tree form in equation selection may better match trees to existing equations and that substantial gaps exist, in terms of both species and diameter ranges, that are ripe for new model-building effort.</p

Promising System for Selecting Healthy In Vitro–Fertilized Embryos in Cattle

Conventionally, in vitro–fertilized (IVF) bovine embryos are morphologically evaluated at the time of embryo transfer to select those that are likely to establish a pregnancy. This method is, however, subjective and results in unreliable selection. Here we describe a novel selection system for IVF bovine blastocysts for transfer that traces the development of individual embryos with time-lapse cinematography in our developed microwell culture dish and analyzes embryonic metabolism. The system can noninvasively identify prognostic factors that reflect not only blastocyst qualities detected with histological, cytogenetic, and molecular analysis but also viability after transfer. By assessing a combination of identified prognostic factors—(i) timing of the first cleavage; (ii) number of blastomeres at the end of the first cleavage; (iii) presence or absence of multiple fragments at the end of the first cleavage; (iv) number of blastomeres at the onset of lag-phase, which results in temporary developmental arrest during the fourth or fifth cell cycle; and (v) oxygen consumption at the blastocyst stage—pregnancy success could be accurately predicted (78.9%). The conventional method or individual prognostic factors could not accurately predict pregnancy. No newborn calves showed neonatal overgrowth or death. Our results demonstrate that these five predictors and our system could provide objective and reliable selection of healthy IVF bovine embryos