水曲柳幼苗根系对土壤养分和水分空间异质性的反应

通过沙培试验方法,研究了温室条件下水曲柳幼苗在施肥和浇水区,非施肥和非浇水区中根系生长,生物量分布,地下部分与地上部分关系,细根直径等特征。结果表明,土壤养分和水分的空间异质性对水曲柳幼苗根系生长和分布有明显影响。在施肥区和浇水区根系生长快,密度大,生物量高,而在非施肥和非浇水区根系生长受到抑制,根系密度小,生物量低,与非施肥区相比,施肥区细根直径下降,有利于根系对养分和水分的运输,但是在非浇水区     

Variable Selection and the Coexistence of Multiple mimetic forms of the Butterfly Heliconius numata

Polymorphism in aposematic animals and coexistence of multiple mimicry rings within a habitat are not predicted by classical Müllerian mimicry. The butterfly Heliconius numata Cramer (Lepidoptera: Nymphalidae; Heliconiinae) is both polymorphic and aposematic. The polymorphism is due to variation at a single locus (or `supergene') which determines colour patterns involved in Müllerian mimicry. We sampled 11 sites in a small area (approx. 60×30km) of North-eastern Peru for H. numata and its co-mimics in the genus Melinaea and Athyrtis (Ithomiinae), and examined the role of temporal and spatial heterogeneity in the maintenance of polymorphism. Colour-patterns of Melinaea communities, which constitute the likely `mimetic environment' for H. numata, are differentiated on a more local scale than morphs of H. numata, but the latter do show a strong and significant response to local selection for colour-pattern. In contrast, analysis of enzyme polymorphism in H. numata across the region revealed no spatial structure, which is consistent with a high mobility of this species. Differences in spatial variability in the two taxa may have caused H. numata to become polymorphic, while temporal variability, not significant in this study, probably has a lesser effect. The mimetic polymorphism is therefore explained by means of multiple selection-migration clines at a single locus, a similar process to that which explains narrow hybrid zones between geographic races of other Heliconius butterflies. This revised version was published online in July 2006 with corrections to the Cover Date.     

DTFLOW: Inference and Visualization of Single-cell Pseudotime Trajectory Using Diffusion Propagation

One of the major challenges in single-cell data analysis is the determination of cellular developmental trajectories using single-cell data. Although substantial studies have been conducted in recent years, more effective methods are still strongly needed to infer the developmental processes accurately. This work devises a new method, named DTFLOW, for determining the pseudotemporal trajectories with multiple branches. DTFLOW consists of two major steps: a new method called Bhattacharyya kernel feature decomposition(BKFD) to reduce the data dimensions, and a novel approach named Reverse Searching on k-nearest neighbor graph(RSKG) to identify the multi-branching processes of cellular differentiation. In BKFD, we first establish a stationary distribution for each cell to represent the transition of cellular developmental states based on the random walk with restart algorithm, and then propose a new distance metric for calculating pseudotime of single cells by introducing the Bhattacharyya kernel matrix. The effectiveness of DTFLOW is rigorously examined by using four single-cell datasets. We compare the efficiency of DTFLOW with the published state-of-the-art methods. Simulation results suggest that DTFLOW has superior accuracy and strong robustness properties for constructing pseudotime trajectories. The Python source code of DTFLOW can be freely accessed at https://github.com/statway/DTFLOW.     

Getting out alive: how predators affect the decision to metamorphose

Metamorphosis has intrigued biologists for a long time as an extreme form of complex life cycles that are ubiquitous in animals. While investigated from a variety of perspectives, the ecological focus has been on identifying and understanding the ecological factors that affect an individual’s decision on when, and at what size, to metamorphose. Predation is a major factor that affects metamorphic decisions and a recent review by Benard (Annu Rev Ecol Evol Syst 35:651–673, 2004)) documented how predator cues induce metamorphic changes relative to model predictions. Importantly, however, real predators affect larval prey via several mechanisms beyond simple induction. In this paper, I contrast the leading models of metamorphosis, provide an overview of the multiple ways that predators can directly and indirectly affect larval growth and development (via induction, thinning, and selection), and identify how each process should affect the time to and size at metamorphosis. With this mechanistic foundation established, I then turn to the well-studied model system of larval amphibians to synthesize studies on: (1) caged predators (which cause only induction), and (2) lethal predators (which cause induction, thinning, and selection). Among the caged-predator studies, the chemical cues emitted by predators rarely induce a smaller size at metamorphosis or a shorter time to metamorphosis, which is in direct contrast to theoretical predictions but in agreement with Benard’s (Annu Rev Ecol Evol Syst 35:651–673, 2004) review based on a considerably smaller dataset. Among the lethal-predator studies, there is a diversity of outcomes depending upon the relative importance of induction versus thinning with the relative importance of the two processes appearing to change with larval density. Finally, I review the persistent effects of larval predators after metamorphosis including both phenotypic and fitness effects. At the end, I outline a number of future directions to allow researchers to continue gaining insight into how predators affect the metamorphic decisions of their prey. Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Biomass responses to elevated CO<Subscript>2</Subscript>, soil heterogeneity and diversity: an experimental assessment with grassland assemblages

While it is well-established that the spatial distribution of soil nutrients (soil heterogeneity) influences the competitive ability and survival of individual plants, as well as the productivity of plant communities, there is a paucity of data on how soil heterogeneity and global change drivers interact to affect plant performance and ecosystem functioning. To evaluate the effects of elevated CO₂, soil heterogeneity and diversity (species richness and composition) on productivity, patterns of biomass allocation and root foraging precision, we conducted an experiment with grassland assemblages formed by monocultures, two- and three-species mixtures of Lolium perenne, Plantago lanceolata and Holcus lanatus. The experiment lasted for 90 days, and was conducted on microcosms built out of PVC pipe (length 38 cm, internal diameter 10 cm). When nutrients were heterogeneously supplied (in discrete patches), assemblages exhibited precise root foraging patterns, and had higher total, above- and belowground biomass. Greater aboveground biomass was observed under elevated CO₂. Species composition affected the below:aboveground biomass ratio and interacted with nutrient heterogeneity to determine belowground and total biomass. Species richness had no significant effects, and did not interact with either CO₂ or nutrient heterogeneity. Under elevated CO₂ conditions, the two- and three-species mixtures showed a clear trend towards underyielding. Our results show that differences among composition levels were dependent on soil heterogeneity, highlighting its potential role in modulating diversity–productivity relationships. Electronic supplementary material Supplementary material is available in the online version of this article at and is accessible to authorized users.     

Spatial variation in vegetation structure coupled to plant available water determined by two-dimensional soil resistivity profiling in a Brazilian savanna

Tropical savannas commonly exhibit large spatial heterogeneity in vegetation structure. Fine-scale patterns of soil moisture, particularly in the deeper soil layers, have not been well investigated as factors possibly influencing vegetation patterns in savannas. Here we investigate the role of soil water availability and heterogeneity related to vegetation structure in an area of the Brazilian savanna (Cerrado). Our objective was to determine whether horizontal spatial variations of soil water are coupled with patterns of vegetation structure across tens of meters. We applied a novel methodological approach to convert soil electrical resistivity measurements along three 275-m transects to volumetric water content and then to estimates of plant available water (PAW). Structural attributes of the woody vegetation, including plant position, height, basal circumference, crown dimensions, and leaf area index, were surveyed within twenty-two 100-m² plots along the same transects, where no obvious vegetation gradients had been apparent. Spatial heterogeneity was evaluated through measurements of spatial autocorrelation in both PAW and vegetation structure. Comparisons with null models suggest that plants were randomly distributed over the transect with the greatest mean PAW and lowest PAW heterogeneity, and clustered in the driest and most heterogeneous transect. Plant density was positively related with PAW in the top 4 m of soil. The density-dependent vegetation attributes that are related to plot biomass, such as sum of tree heights per plot, exhibited spatial variation patterns that were remarkably similar to spatial variation of PAW in the top 4 m of soil. For PAW below 4 m depth, mean vegetation attributes, such as mean height, were negatively correlated with PAW, suggesting greater water uptake from the deep soil by plants of larger stature. These results are consistent with PAW heterogeneity being an important structuring factor in the plant distribution at the scale of tens of meters in this ecosystem.     

Modelling Recolonization of Second-Growth Forest Stands by the North American Red Squirrel Tamiasciurus hudsonicus

In this paper, we present a model for source–sink population dynamics where the locations of source and sink habitats change over time. We do this in the context of the population dynamics of the North American red squirrel, Tamiasciurus hudsonicus, within a forest environment subject to harvesting and regrowth. Harvested patches of forest are initially sinks, then eventually become source habitat again as the forest regrows. At the same time, each harvested patch is gradually recolonized by squirrels from other forest patches. We are interested in the interaction of forest harvesting dynamics with squirrel population dynamics. This depends on the harvesting schedule, and on the choices squirrels make when deciding whether to settle in a mature forest patch or in a recently harvested patch. We find that the time it takes for a second-growth forest patch to be recolonized at the mature forest level is longer than the time required for the habitat quality to be restored to the mature forest level. We also notice that recolonization pressure decreases squirrel populations in neighbouring patches. The connectivity between forest patches and the cutting schedule used also affect the time course of recolonization and steady-state population levels.     

Making Sense in Time: Remote Sensing and the Challenges of Temporal Heterogeneity in Social Analysis of Environmental Change—cases from Malawi

This article contributes to the encouraging recent trend toward more critical examination of the linkages between remote sensing and social analysis of environmental change. Using two case studies from Malawi, we explain the importance of thinking about temporal scale when using remote sensing data. Specifically, from our on-the-ground research, we came to appreciate three important issues: (1) multiple causation and multiple temporal scales operating simultaneously—making inference of casual relations between particular social factors and observed land use changes difficult; (2) ‘visible’ vs. ‘invisible’ processes and events; and (3) ‘continuous’ vs. ‘punctuated’ social and environmental processes. We observe that in each case, social differentiation is key to understanding which temporal frames are most relevant in understanding observed land use dynamics. We conclude that, while these are not entirely new observations, research on the applications of remote sensing in social analysis of environmental change could be enriched by more rigorous examination of linkages between environmental change, temporal scale, and the social relations (including social differentiation) that can help to explain how and why particular temporal frames are most salient.