The timing of flowering is an important driver of species distribution and community assembly patterns.However,we still have much to learn about the factors that shape flowering diversity(i.e.,number of species flowering per period)in plant communities.One potential explanation of flowering diversity is the mid-domain effect,which states that geometric constraints on species ranges within a bounded domain(space or time)will yield a mid-domain peak in diversity regardless of ecological factors.Here,we determine whether the mid-domain effect explains peak flowering time(i.e.,when most species of communities are flowering)across China.We used phenological data of 16,267 herbaceous and woody species from the provincial Flora in China and species distribution data from the Chinese Vascular Plant Distribution Database to determine relationships between the observed number of species flowering and the number of species flowering as predicted by the mid-domain effect model,as well as between three climatic variables(mean minimum monthly temperature,mean monthly precipitation,and mean monthly sunshine duration).We found that the mid-domain effect explained a significant proportion of the temporal variation in flowering diversity across all species in China.Further,the mid-domain effect explained a greater proportion of variance in flowering diversity at higher latitudes than at lower lati-tudes.The patterns of flowering diversity for both herbaceous and woody species were related to both the mid-domain effect and environmental variables.Our findings indicate that including geometric constraints in conjunction with abiotic and biotic predictors will improve predictions of flowering di-versity patterns.

森林径级结构是树木生长、竞争、死亡等过程的综合反映,也是估算森林生物量、判断森林演替阶段与健康状态以及预测森林碳汇潜力的基础依据.林学领域早期对径级结构的研究以统计描述为主,多采用常见的概率分布函数来拟合样地尺度上径级结构的动态变化,缺乏对其形成机制的阐释.随着宏观生态学的发展,最大熵原理、中心极限定理等被用于解释大尺度上发现的相对一致的森林径级结构,但这类模型侧重概率统计,对具体生态学过程的分析仍然欠缺.2000年以来,在原始成熟森林中发现的径级结构的幂律特征催生了一系列理论研究,包括代谢尺度理论、林窗演替理论等.这些理论尝试从树木个体大小和资源利用之间的关系,以及树木对资源的竞争过程来演绎径级结构达到稳态时幂律特征的形成机制.种群统计平衡理论为稳态径级结构的分析提供了一般性框架,揭示了不同的树木生长速率和死亡率如何导致径级结构特征的变化;在此基础上,种群统计最优性假设为径级结构的分析提供了新的视角.数学层面上,转移矩阵、积分投影、偏微分方程等都是径级结构动力学分析的有力工具,但由于这类数学模型的时间动态解析求解较为困难,研究中通常预先假定森林处于理想的结构平衡状态.而在实际情况下,结构非平衡往往是森林的常态,也是森林碳库变化与碳汇潜力估算的基础.为了更好预测全球变化背景下的森林动态趋势,应明确环境因子对径级相关的树木生长速率、死亡率的影响,并发展径级结构动态特征的解析方法.

2022年5-10月,利用夹夜法和陷阱法对四川西岭雪山小型兽类群落的海拔梯度变化进行了研究,在海拔1 000～4 600 m设置 102 个样方,捕获小型兽类32种884只.以400 m海拔梯度分析小型兽类群落:随海拔梯度升高,群落第一优势种形成了从北社鼠Niviventer confucianus(海拔1 000～1 800 m),转变成中华姬鼠Apodemus draco(海拔 1 800～3 400 m),再到松田鼠属未定名种Neodon sp.(海拔3 400 m以上)的替换现象;物种多样性垂直分布格局为中峰格局,物种丰富度在海拔1 800～3 400 m最高;发现松田鼠属Neodon一新物种,确认壮鼩鼹Uropsilus ro-bustus Wan,2015新种地位成立.本研究强调了对完整海拔梯度进行全面抽样调查的重要性,从而能够较为客观地反映真实的生物多样性海拔分布格局.

Background:Although the species-urban green area relationship (SARu) has been analyzed worldwide, the global consistency of its parameters, such as the fit and the slope of models, remains unexplored. Moreover, the SARu can be explained by 20 different models. Therefore, our objective was to evaluate which models provide a better explanation of SARus and, focusing on the power model, to evaluate the global heterogeneity in its fit and slope. Methods: We tested the performance of multiple statistical models in accounting for the way in which species richness increases with area, and examined whether variability in model form was associated with various methodo-logical and environmental factors. Focusing on the power model, we analyzed the global heterogeneity in the fit and slope of the models through a meta-analysis. Results: Among 20 analyzed models, the linear model provided the best fit to the most datasets, was the top ranked model according to our efficiency criterion, and was the top overall ranked model. The Kobayashi and power models were the second and third overall ranked models, respectively. The number of green areas and the minimum number of species within a green area were the only significant variables explaining the variation in model form and perfor-mance, accounting for less than 10% of the variation. Based on the power model, there was a consistent overall fit (r2 = 0.50) and positive slope of 0.20 for the species richness increase with area worldwide. Conclusions: The good fit of the linear model to our SARu datasets contrasts with the non-linear SAR frequently found in true and non-urban habitat island systems; however, this finding may be a result of the small sample size of many SARu datasets. The overall power model slope of 0.20 suggests low levels of isolation among urban green patches, or alternatively that habitat specialist and area sensitive species have already been extirpated from urban green areas.

Attributing biological explanations to observed ecogeographical and ecological patterns require eliminating potential statistical and sampling artifacts as alternative explanations of the observed patterns.Here,we assess the role of sample size,statistical power,and geographic inclusivity on the general validity and statistical significance of relationships between body size and latitude for 3 well-studied species of turtles.We extend those analyses to emphasize the importance of using statistically robust data in determining macroecological patterns.We examined intraspecific trends in body size with latitude in Chelydra serpentina,Chrysemys picta,and Trachemys scripta using Pearson's correlations,diagnostic tests for influential points,and resampling.Existing data were insufficient to ascertain a latitudinal trend in body size for C.serpentina or T.scripta.There was a significant relationship for C.picta,however,resampling analyses show that,on average,16 of the 23 available independent populations were needed to demonstrate a significant relationship and that at least 20 of 23 populations were required to obtain a statistically powerful correlation between body size and latitude.Furthermore,restricting the latitudes of populations resampled shows that body size trends of C.picta were largely due to leveraging effects of populations at the edge of the species range.Our results suggest that broad inferences regarding ecological trends in body size should be made with caution until underlying (intraspecific) patterns in body size can be statistically and conclusively demonstrated.

Species richness is one of the focuses of the preponderance of ecological studies.Latitudinal and altitudinal gradients of species richness are two well-known macroecological patterns.Most studies on the macroecology of species richness and its determinants are mainly focused on a single scale,although a few include multiple scales.Across multiple scales,we can better understand the diversity gradients and the potential causes.Here,we gathered the maps of distribution for 212 species of Chinese lizards from published studies,and to describe the overall Chinese lizard richness patterns.We studied the relationships between the latitudinal and altitudinal patterns of species richness among Chinese lizards at the assemblage level.We further tested the relationship between lizard richness and environmental factors among multiple studied scales(large scale:1.5°×1.5°,medium scale:1°×1°,and small scale:0.5°×0.5°).Regions with higher species richness occurs in in south China,and we found negative latitudinal richness gradients.We found a low-altitude plateau pattern between species richness and altitude,and lizard richness decreased with altitude above 2500 m.Lizard richness was positively correlated with temperature and net primary productivity,but negatively correlated with actual evapotranspiration,temperature,and precipitation seasonality at all three scales.However,lizard species richness was positively correlated with heterogeneity only at the 1° scale.Based on the results across multiple scales,we confirmed that the species richness patterns of Chinese lizards were driven by multiple factors,which consistent with the predictions of the ambient energy,seasonality,and productivity hypotheses.However,the relationship between lizard richness and heterogeneity differed among studied scales owing to the different levels of altitude heterogeneity within grids at different scales.