Effects of wild and farm-grown macroalgae on the growth of juvenile South African abalone Haliotis midae Linnaeus

The effect of various macroalgal diets on the growth of grow-out (>20 mm shell length) South African abalone Haliotis midae was investigated on a commercial abalone farm. The experiment consisted of four treatments: fresh kelp blades (Ecklonia maxima (Osbeck) Papenfuss) (c. 10% protein); farmed, protein-enriched Ulva lactuca Linnaeus (c. 26% protein) grown in aquaculture effluent; wild U. lactuca (c. 20% protein); and a combination diet of kelp blades + farmed U. lactuca. Abalone grew best on the combination diet (0.423 ± 0.02% weight d^?1 SGR [specific growth rate]; 59.593 ± 0.02 ?m d^?1 DISL [daily increment in shell length]; 1.093 final CF [condition factor]) followed by the kelp only diet (0.367 ± 0.02% weight d^?1 SGR; 53.148 ± 0.02 ?m d^?1 DISL; 1.047 final CF), then the farmed, protein-enriched U. lactuca only diet (0.290 ± 0.02% weight d^?1 SGR; 42.988 ± 0.03 um d”¹ DISL; 1.013 final CF) that in turn outperformed the wild U. lactuca only diet (-0.079 ± 0.01% weight d^?1 SGR; 3.745 ± 0.02 ?m d”^?1 DISL; 0.812 final CF). The results suggest that protein alone could not have accounted for the differences produced by the varieties of U. lactuca and that the gross energy content is probably important.     

Adjustment for exploratory cut-off selection in randomized clinical trials with survival endpoint

Defining the target population based on predictive biomarkers plays an important role during clinical development. After establishing a relationship between a biomarker candidate and response to treatment in exploratory phases, a subsequent confirmatory trial ideally involves only subjects with high potential of benefiting from the new compound. In order to identify those subjects in case of a continuous biomarker, a cut-off is needed. Usually, a cut-off is chosen that resulted in a subgroup with a large observed treatment effect in an exploratory trial. However, such a data-driven selection may lead to overoptimistic expectations for the subsequent confirmatory trial. Treatment effect estimates, probability of success, and posterior probabilities are useful measures for deciding whether or not to conduct a confirmatory trial enrolling the biomarker-defined population. These measures need to be adjusted for selection bias. We extend previously introduced Approximate Bayesian Computation techniques for adjustment of subgroup selection bias to a time-to-event setting with cut-off selection. Challenges in this setting are that treatment effects become time-dependent and that subsets are defined by the biomarker distribution. Simulation studies show that the proposed method provides adjusted statistical measures which are superior to naïve Maximum Likelihood estimators as well as simple shrinkage estimators.     

Comparison of complex modeling strategies for prediction of a binary outcome based on a few,highly correlated predictors

Motivated by a clinical prediction problem, a simulation study was performed to compare different approaches for building risk prediction models. Robust prediction models for hospital survival in patients with acute heart failure were to be derived from three highly correlated blood parameters measured up to four times, with predictive ability having explicit priority over interpretability. Methods that relied only on the original predictors were compared with methods using an expanded predictor space including transformations and interactions. Predictors were simulated as transformations and combinations of multivariate normal variables which were fitted to the partly skewed and bimodally distributed original data in such a way that the simulated data mimicked the original covariate structure. Different penalized versions of logistic regression as well as random forests and generalized additive models were investigated using classical logistic regression as a benchmark. Their performance was assessed based on measures of predictive accuracy, model discrimination, and model calibration. Three different scenarios using different subsets of the original data with different numbers of observations and events per variable were investigated. In the investigated setting, where a risk prediction model should be based on a small set of highly correlated and interconnected predictors, Elastic Net and also Ridge logistic regression showed good performance compared to their competitors, while other methods did not lead to substantial improvements or even performed worse than standard logistic regression. Our work demonstrates how simulation studies that mimic relevant features of a specific data set can support the choice of a good modeling strategy.     

C1188D mutation abolishes specific recognition between MLL1-CXXC domain and CpG site by inducing conformational switch of flexible N-terminal

Mixed lineage leukemia protein (MLL1 protein) recognizes the CpG site via its CXXC domain and is frequently associated with leukemia. The specific recognition is abolished by C1188D mutation, which also prevents MLL-related leukemia. In this paper, multiple molecular dynamic (MD) simulations were performed to investigate the mechanism of recognition and influences of C1188D mutation. Started from fully dissociated DNA and MLL1-CXXC domain, remarkably, the center of mass (COM) of MLL1-CXXC domain quickly concentrates on the vicinity of the CpG site in all 53 short MD simulations. Extended simulations of the wild type showed that the native complex formed in 500 ns among 4 of 53 simulations. In contrast, the C1188D mutant COM distributed broadly around the DNA and the native complex was not observed in any of the extended simulations. Simulations on the apo MLL1-CXXC domain further suggest that the wild type protein remained predominantly in an open form that closely resembles its structure in the native complex whereas C1188D mutant formed predominantly compact structures in which the N- terminal bends to D1188. This conformational switch hinders the formation of encounter complex, thus abolishes the recognition. Our study also provides clues to the study mechanism of recognition, by the CXXC domain from proteins like DNA methyltransferase and ten-eleven translocation enzymes.     

Noninvasive tool for optical online monitoring of individual biomass concentrations in a defined coculture

Cocultures bear great potential in the conversion of complex substrates and process intensification, as well as, in the formation of unique components only available due to inter-species interactions. Dynamic data of coculture composition is necessary for understanding and optimizing coculture systems. However, most standard online determined parameters measure the sum of all species in the reactor system. The kinetic behavior of the individual species remains unknown. Up to now, different offline methods are available to determine the culture composition, as well as the online measurement of fluorescence of genetically modified organisms. To avoid any genetic modification, a noninvasive online monitoring tool based on the scattered light spectrum was developed for microtiter plate cultivations. To demonstrate the potential, a coculture consisting of the bacterium Lactococcus lactis and the yeast Kluyveromyces marxianus was cultivated. Via partial least squares regression of scattered light spectra, the online determination of the individual biomass concentrations without further sampling and analyses is possible. The results were successfully validated by a Coulter counter-analysis, taking advantage of the different cell sizes of both organisms. The findings prove the applicability of the new method to follow in detail the dynamics of a coculture.     

Continental estimates of forest cover and forest cover changes in the dry ecosystems of Africa between 1990 and 2000

Aim

This study provides regional estimates of forest cover in dry African ecoregions and the changes in forest cover that occurred there between 1990 and 2000, using a systematic sample of medium‐resolution satellite imagery which was processed consistently across the continent.

Location

The study area corresponds to the dry forests and woodlands of Africa between the humid forests and the semi‐arid regions. This area covers the Sudanian and Zambezian ecoregions.

Methods

A systematic sample of 1600 Landsat satellite imagery subsets, each 20 km × 20 km in size, were analysed for two reference years: 1990 and 2000. At each sample site and for both years, dense tree cover, open tree cover, other wooded land and other vegetation cover were identified from the analysis of satellite imagery, which comprised multidate segmentation and automatic classification steps followed by visual control by national forestry experts.

Results

Land cover and land‐cover changes were estimated at continental and ecoregion scales and compared with existing pan‐continental, regional and local studies. The overall accuracy of our land‐cover maps was estimated at 87%. Between 1990 and 2000, 3.3 million hectares (Mha) of dense tree cover, 5.8 Mha of open tree cover and 8.9 Mha of other wooded land were lost, with a further 3.9 Mha degraded from dense to open tree cover. These results are substantially lower than the 34 Mha of forest loss reported in the FAO's 2010 Global Forest Resources Assessment for the same period and area.

Main conclusions

Our method generates the first consistent and robust estimates of forest cover and change in dry Africa with known statistical precision at continental and ecoregion scales. These results reduce the uncertainty regarding vegetation cover and its dynamics in these previously poorly studied ecosystems and provide crucial information for both science and environmental policies.     

Environmental correlates of annual survival differ between two ecologically similar and congeneric owls

Understanding how survival is affected by the environment is essential to gain insight into population dynamics and the evolution of life‐history traits as well as to identify environmental selection pressures. However, we still have little understanding of the relative effect of different environmental factors and their interactions on demographic traits and population dynamics. Here we used two long‐term, individual‐based datasets on Tawny Owl Strix aluco (1981–2010) and Ural Owl S. uralensis (1986–2010) to undertake capture‐mark‐recapture analysis of annual survival of adult females in response to three biologically meaningful environmental variables and their two‐way interactions. Despite the similar ecology of these two species, their survival was associated with different and uncorrelated environmental drivers. The main correlate of Tawny Owl survival was an inverse association with snow depth (winter severity). For Ural Owl, high food (vole) abundance improved survival during years with deep snow, but was less important during years with little snow. In addition, Ural Owl survival was strongly density‐dependent, whereas Tawny Owl survival was not. Our findings advise caution in extrapolating demographic inferences from one species to another, even when they are very closely related and ecologically similar. Analyses including only one or few potential environmental drivers of a species' survival may lead to incomplete conclusions because survival may be affected by several factors and their interactions.     

Neogene origins and implied warmth tolerance of Amazon tree species

Tropical rain forest has been a persistent feature in South America for at least 55 million years. The future of the contemporary Amazon forest is uncertain, however, as the region is entering conditions with no past analogue, combining rapidly increasing air temperatures, high atmospheric carbon dioxide concentrations, possible extreme droughts, and extensive removal and modification by humans. Given the long‐term Cenozoic cooling trend, it is unknown whether Amazon forests can tolerate air temperature increases, with suggestions that lowland forests lack warm‐adapted taxa, leading to inevitable species losses. In response to this uncertainty, we posit a simple hypothesis: the older the age of a species prior to the Pleistocene, the warmer the climate it has previously survived, with Pliocene (2.6–5 Ma) and late‐Miocene (8–10 Ma) air temperature across Amazonia being similar to 2100 temperature projections under low and high carbon emission scenarios, respectively. Using comparative phylogeographic analyses, we show that 9 of 12 widespread Amazon tree species have Pliocene or earlier lineages (>2.6 Ma), with seven dating from the Miocene (>5.6 Ma) and three >8 Ma. The remarkably old age of these species suggest that Amazon forests passed through warmth similar to 2100 levels and that, in the absence of other major environmental changes, near‐term high temperature‐induced mass species extinction is unlikely.     

The extent of edge effects in fragmented landscapes: Insights from satellite measurements of tree cover

Due to deforestation, intact tropical forest areas are increasingly transformed into a mixture of remaining forest patches and human modified areas. These forest fragments suffer from edge effects, which cause changes in ecological and ecosystem processes, undermining habitat quality and the offer of ecosystem services. Even though detailed and long term studies were developed on the topic of edge effects at local scale, understanding edge effect characteristics in fragmented forests on larger scales and finding indicators for its impact is crucial for predicting habitat loss and developing management options. Here we evaluate the spatial and temporal dimensions of edge effects in large areas using remote sensing. First we executed a neighborhood pixel analysis in 11 LANDSAT Tree Cover (LTC) scenes (180 × 185 km each, 8 in the tropics and 3 in temperate forested areas) using tree cover as an indicator of habitat quality and in relation to edge distance. Second, we executed a temporal analysis of LTC in a smaller area in the Brazilian Amazon forest where one larger forest fragment (25,890 ha) became completely fragmented in 5 years. Our results show that for all 11 scenes pixel neighborhood variation of LTC is much higher in the vicinity of forest edges, becoming lower towards the forest interior. This analysis suggests a maximum distance for edge effects and can indicate the location of unaffected core areas. However, LTC patterns in relation to fragment edge distance vary according to the analyzed region, and maximum edge distance may differ according to local conditions. Our temporal analysis illustrates the change in tree cover patterns after 5 years of fragmentation, becoming on average lower close to the edge (between 50 and 100 m). Although it is still unclear which are the main causes of LTC edge variability within and between regions, LANDSAT Tree Cover could be used as an accessible and efficient discriminator of edge and interior forest habitats in fragmented landscapes, and become invaluable for deriving qualitative spatial and temporal information of ecological and ecosystem processes.     

农林废弃物混配基质的理化性质及其对油茶幼苗生长效应的综合评价

以腐熟的甘蔗渣( SB)、木薯皮( CP)、花生壳( PS)和火炭灰( BA)及园土( GS)为原料,按照不同体积比配制成9种混配基质,并以等体积比泥炭和园土混配基质为对照,对各基质的理化性质及基质中油茶( Camellia oleifera Abel)幼苗的生长状况进行比较;在对基质理化指标和油茶幼苗的壮苗指数进行线性回归分析和通径分析的基础上,采用主成分分析和综合评价法对各基质的育苗效果进行综合评价。结果表明：9种农林废弃物混配基质的容重、总孔隙度和毛管孔隙度分别为0.23~0.47 g·cm-3、60.90%~67.23%和46.53%~58.27%, pH 6.72~pH 7.14,各基质的速效氮含量、速效磷含量、速效钾含量、pH值、电导率和通气孔隙度均高于或显著高于对照,容重则显著低于对照。在不同基质中油茶幼苗的茎粗、单株叶片数、叶长、叶宽、叶绿素相对含量( SPAD)、单株茎叶干质量、单株根干质量和壮苗指数均存在一定差异,而株高和根冠比却无显著差异;其中S9混配基质也V( SB)：V( CP)：V( BA)=2：1：1页中幼苗的大部分生长指标较高,表现出明显的生长优势。线性回归和通径分析结果显示：除通气孔隙度外,基质的其他8个理化指标基本涵盖了影响幼苗壮苗指数的关键因素;其中,速效钾含量是对壮苗指数直接影响最大的负相关因子,而速效磷含量、电导率和总孔隙度对壮苗指数则有较大的正向直接作用,并且三者通过速效钾含量对壮苗指数产生较大的负向间接作用;此外,基质容重对壮苗指数也有一定的负向直接作用。综合评价结果显示：S9和S7混配基质也V( SB)：V( BA)：V( GS)=4：3：3页对油茶育苗效果的综合得分较高,分别为14.363和14.337,建议将S9混配基质作为油茶育苗的首选替代基质,S7混配基质作为备选基质。