Trophic control of mesopredators in terrestrial ecosystems: top‐down or bottom‐up?

It has been argued that widespread extinctions of top predators have changed terrestrial ecosystem structures through mesopredator release, where increased abundances of medium-sized predators have detrimental effects on prey communities. This top-down concept has received much attention within conservation biology, but few studies have demonstrated the phenomenon. The concept has been criticized since alternative explanations involving bottom-up impacts from bioclimatic effects on ecosystem productivity and from anthropogenic habitat change are rarely considered. We analyse the response of a mesopredator (the red fox) to declines in top predators (wolf and Eurasian lynx) and agricultural expansion over 90 years in Sweden, taking bioclimatic effects into account. We show a top-down mesopredator release effect, but ecosystem productivity determined its strength. The impacts of agricultural activity were mediated by their effects on top predator populations. Thus, both top-down and bottom-up processes need to be understood for effective preservation of biodiversity in anthropogenically transformed ecosystems.     

Leaf structure and specific leaf mass: the alpine desert plants of the Eastern Pamirs, Tadjikistan

This study examines interrelationships between eight leaf attributes (specific leaf mass, area, dry mass, lamina thickness, mesophyll cell number per cm², mesophyll cell volume, chloroplast volume, and number of chloroplasts per mesophyll cell) in field-grown plants of 94 species from the Eastern Pamir Mountains, at elevations between 3800 and 4750 m. Unlike most other mountain areas, the Eastern Pamirs, Karakorum system, Tadjikistan provide localities where low temperatures and radiation combine with moisture stress at high altitudes. For all the attributes measured, significant differences were found between plants with different mesophyll types. Leaves with dorsiventral palisade structure (dorsal palisade, ventral spongy mesophyll cells) had thicker leaves with larger but fewer mesophyll cells, containing more and larger chloroplasts. These differences in mesophyll type are reflected in differences in the total surface of mesophyll cells per unit leaf area ( A _mes/ A ) or volume ( A _mes/ V ). Plants with isopalisade leaf structure (palisade cells under both dorsal and ventral surfaces) are more commonly xerophytes and their increased values of A _mes/ A and A _mes/ V decrease CO₂ mesophyll resistance, which is an important adaptation to drought. Path analysis shows the critical importance of mesophyll cell volume in leading to the covariance between the different leaf attributes and hence to specific leaf mass (SLM), even though mesophyll cell volume is not itself strongly correlated with SLM. This is because mesophyll cell volume increases SLM through its effects on leaf thickness and chloroplast number per cell, but decreases SLM through its negative effect on mesophyll cell density.     

Isolation by distance,resistance and/or clusters? Lessons learned from a forest‐dwelling carnivore inhabiting a heterogeneous landscape

Landscape genetics provides a valuable framework to understand how landscape features influence gene flow and to disentangle the factors that lead to discrete and/or clinal population structure. Here, we attempt to differentiate between these processes in a forest‐dwelling small carnivore [European pine marten (Martes martes)]. Specifically, we used complementary analytical approaches to quantify the spatially explicit genetic structure and diversity and analyse patterns of gene flow for 140 individuals genotyped at 15 microsatellite loci. We first used spatially explicit and nonspatial Bayesian clustering algorithms to partition the sample into discrete clusters and evaluate hypotheses of ‘isolation by barriers’ (IBB). We further characterized the relationships between genetic distance and geographical (‘isolation by distance’, IBD) and ecological distances (‘isolation by resistance’, IBR) obtained from optimized landscape models. Using a reciprocal causal modelling approach, we competed the IBD, IBR and IBB hypotheses with each other to unravel factors driving population genetic structure. Additionally, we further assessed spatially explicit indices of genetic diversity using sGD across potentially overlapping genetic neighbourhoods that matched the inferred population structure. Our results revealed a complex spatial genetic cline that appears to be driven jointly by IBD and partial barriers to gene flow (IBB) associated with poor habitat and interspecific competition. Habitat loss and fragmentation, in synergy with past overharvesting and possible interspecific competition with sympatric stone marten (Martes foina), are likely the main factors responsible for the spatial genetic structure we observed. These results emphasize the need for a more thorough evaluation of discrete and clinal hypotheses governing gene flow in landscape genetic studies, and the potential influence of different limiting factors affecting genetic structure at different spatial scales.     

Parental provisioning behaviour plays a key role in linking personality with reproductive success

Repeatable behavioural traits (‘personality’) have been shown to covary with fitness, but it remains poorly understood how such behaviour–fitness relationships come about. We applied a multivariate approach to reveal the mechanistic pathways by which variation in exploratory and aggressive behaviour is translated into variation in reproductive success in a natural population of blue tits, Cyanistes caeruleus. Using path analysis, we demonstrate a key role for provisioning behaviour in mediating the link between personality and reproductive success (number of fledged offspring). Aggressive males fed their nestlings at lower rates than less aggressive individuals. At the same time, their low parental investment was associated with increased female effort, thereby positively affecting fledgling production. Whereas male exploratory behaviour was unrelated to provisioning behaviour and reproductive success, fast-exploring females fed their offspring at higher rates and initiated breeding earlier, thus increasing reproductive success. Our findings provide strong support for specific mechanistic pathways linking components of behavioural syndromes to reproductive success. Importantly, relationships between behavioural phenotypes and reproductive success were obscured when considering simple bivariate relationships, underlining the importance of adopting multivariate views and statistical tools as path analysis to the study of behavioural evolution.     

结构方程模型及其在生态学中的应用

基于多变量统计方法同时研究自然系统内多个因子之间的相互关系, 是阐释复杂的自然系统的一个重要手段。相比传统的多变量统计法, 结构方程模型基于研究者的先验知识预先设定系统内因子间的依赖关系, 不仅能够判别各因子之间的关系强度(路径系数), 还能对整体模型进行拟合和判断, 从而能更全面地了解自然系统。由于结构方程模型只在近年才被应用到生态学的数据分析中, 因此该文试图对其作一简略介绍, 包括结构方程模型的定义和变量类型, 结合事例研究展现结构方程模型分析的一般步骤、在生态学中的应用以及相关软件的介绍等。望能为相关研究人员提供直观的认识, 加强结构方程模型在生态学数据分析中的应用。     

Effects of sample size,number of markers,and allelic richness on the detection of spatial genetic pattern

The influence of study design on the ability to detect the effects of landscape pattern on gene flow is one of the most pressing methodological gaps in landscape genetic research. To investigate the effect of study design on landscape genetics inference, we used a spatially‐explicit, individual‐based program to simulate gene flow in a spatially continuous population inhabiting a landscape with gradual spatial changes in resistance to movement. We simulated a wide range of combinations of number of loci, number of alleles per locus and number of individuals sampled from the population. We assessed how these three aspects of study design influenced the statistical power to successfully identify the generating process among competing hypotheses of isolation‐by‐distance, isolation‐by‐barrier, and isolation‐by‐landscape resistance using a causal modelling approach with partial Mantel tests. We modelled the statistical power to identify the generating process as a response surface for equilibrium and non‐equilibrium conditions after introduction of isolation‐by‐landscape resistance. All three variables (loci, alleles and sampled individuals) affect the power of causal modelling, but to different degrees. Stronger partial Mantel r correlations between landscape distances and genetic distances were found when more loci were used and when loci were more variable, which makes comparisons of effect size between studies difficult. Number of individuals did not affect the accuracy through mean equilibrium partial Mantel r, but larger samples decreased the uncertainty (increasing the precision) of equilibrium partial Mantel r estimates. We conclude that amplifying more (and more variable) loci is likely to increase the power of landscape genetic inferences more than increasing number of individuals.