广东省南昆山伯乐树群落特征及其保护策略

在广东省南昆山自然保护区内调查了中国特有珍稀植物伯乐树种群的分布格局、龄级结构和伴生群落的物种组成.结果表明:该种群的分布范围狭窄且集中;龄级不完整,Ⅱ、Ⅲ级幼树少见,结构呈衰退型;伴生群落呈典型的亚热带植物区系的特点,其组成不稳定、优势种不显著.建议将伯乐树幼树作为就地保护的重点,适当去除周围的罗浮槭、羊角杜鹃和黄樟等速生树种,以创造有光照和水肥条件的生境;对于Ⅳ级以上成株,应注意拟赤杨和华润楠等空间生态位相近树种的数量和密度,适当疏剪枝条,以帮助成株占据较好的空间位;同时再积极引入异龄的伯乐树幼苗,促进种群恢复和发展.     

基于MaxEnt模型预测中国兰属植物的分布格局及主导气候因子(附表)

兰属(Cymbidium)中，除了兔耳兰C.lancifolium以外的所有种均被列为国家重点保护野生植物。为探究其在未来气候条件下的潜在分布格局，该研究基于兰属植物已知的分布点和19个气候因子，利用最大熵(MaxEnt)模型和地理信息系统(ArcGIS)模拟兰属以及其中20种兰属植物在9种不同气候情景(当代以及未来2030s、2050s、2070s和2090s 4个时间段各两种温室气体排放情景)下的潜在分布格局。结果表明：(1)最干旱季降水量(Bio17)、年降水量(Bio12)和温度季节性变化(Bio4)是影响兰属植物地理分布格局的主导气候因子。(2)不同兰属植物在未来情景下的适生区表现出不同的变化趋势，并且影响其分布的主导气候因子也有所不同。其中，冬凤兰(C.dayanum)等8个物种的适生区面积整体呈扩张趋势，而西藏虎头兰(C.tracyanum)等12个物种的适生区面积整体则呈缩减趋势。该研究结果为兰属植物就地保护与迁地保护提供了重要参考，对兰属等濒危野生植物的保护具有积极意义。     

Phylogeography of Podocarpus matudae (Podocarpaceae): pre‐Quaternary relicts in northern Mesoamerican cloud forests

Aim Cloud forests of northern Mesoamerica represent the northern and southern limit of the contact zone between species otherwise characteristic of North or South America. Several phylogeographic studies featuring temperate conifer species have improved our understanding of species responses to environmental changes. In contrast, conifer species that presumably colonized northern Mesoamerica from South America are far less studied. A phylogeographic study of Podocarpus matudae (Podocarpaceae) was conducted to identify any major evolutionary divergences or disjunctions across its range and to determine if its current distribution is associated with pre‐Quaternary climatic and/or long‐distance dispersal events. Location Northern Mesoamerica (Mexico and Guatemala). Methods Sixteen populations (157 individuals) of P. matudae were screened for variation at two plastid DNA markers. The intra‐specific phylogenetic relationships among haplotypes were reconstructed using Bayesian inference. Population genetic analyses were undertaken to gain insight into the evolutionary history of these populations. To test whether genetic divergence among populations occurred at different time‐scales plastid DNA sequence data and fossil‐ and coalescent‐based calibrations were integrated. Results The combination of plastid markers yielded 11 haplotypes. Differentiation among populations based on DNA variation (G_ST) (0.707, SE 0.0807) indicated a clear population structure in P. matudae. Differentiation for ordered alleles (N_ST) (0.811, SE 0.0732) was higher than that for G_ST, indicating phylogeographical structure in P. matudae. Most of the total variation (81.3%, P < 0.0001) was explained by differences among populations. The estimated divergence time between the unique haplotypes from a Guatemalan population and the two most common haplotypes from the Sierra Madre Oriental in Mexico was between 10 and 20 Ma, and further haplotype divergence in the poorly resolved clade of the Sierra Madre Oriental occurred between 3 and 0.5 Ma. Main conclusions Divergence estimations support the hypothesis that extant Podocarpus matudae populations are pre‐Quaternary relicts. This finding is consistent with fossil and pollen data that support a Miocene age for temperate floristic elements in Mesoamerican cloud forests, whereas further haplotype divergence within the Sierra Madre Oriental, Chiapas and Guatemala occurred more recently, coinciding with Pleistocene cloud forest refugia.     

Assessing the impact of deforestation and climate change on the range size and environmental niche of bird species in the Atlantic forests,Brazil

Aim Habitat loss and climate change are two major drivers of biological diversity. Here we quantify how deforestation has already changed, and how future climate scenarios may change, environmental conditions within the highly disturbed Atlantic forests of Brazil. We also examine how environmental conditions have been altered within the range of selected bird species. Location Atlantic forests of south‐eastern Brazil. Methods The historical distribution of 21 bird species was estimated using Maxent . After superimposing the present‐day forest cover, we examined the environmental niches hypothesized to be occupied by these birds pre‐ and post‐deforestation using environmental niche factor analysis (ENFA). ENFA was also used to compare conditions in the entire Atlantic forest ecosystem pre‐ and post‐deforestation. The relative influence of land use and climate change on environmental conditions was examined using analysis of similarity and principal components analysis. Results Deforestation in the region has resulted in a decrease in suitable habitat of between 78% and 93% for the Atlantic forest birds included here. Further, Atlantic forest birds today experience generally wetter and less seasonal forest environments than they did historically. Models of future environmental conditions within forest remnants suggest generally warmer conditions and lower annual variation in rainfall due to greater precipitation in the driest quarter of the year. We found that deforestation resulted in a greater divergence of environmental conditions within Atlantic forests than that predicted by climate change. Main conclusions The changes in environmental conditions that have occurred with large‐scale deforestation suggest that selective regimes may have shifted and, as a consequence, spatial patterns of intra‐specific variation in morphology, behaviour and genes have probably been altered. Although the observed shifts in available environmental conditions resulting from deforestation are greater than those predicted by climate change, the latter will result in novel environments that exceed temperatures in any present‐day climates and may lead to biotic attrition unless organisms can adapt to these warmer conditions. Conserving intra‐specific diversity over the long term will require considering both how changes in the recent past have influenced contemporary populations and the impact of future environmental change.     

The influence of light and temperature on the germination of two Ugandan medicinal trees

For reasons of the problems of establishment of some Ugandan trees in certain environments, we investigated the influence of temperature and light on germination and seedling growth of two locally threatened medicinal trees, Hallea rubrostipulata and Sarcocephalus latifolius, to facilitate their establishment. Field and controlled laboratory experiments were carried out to investigate the species germination requirements and seedling growth. Both species needed light to germinate. Hallea rubrostipulata had a temperature optimum of 25°C with 79% germination, while for S. latifolius, the total germination after 28 days was close to 60% at temperatures from 20 to 35°C. Seedlings of S. latifolius survived well at 35°C, while those of H. rubrostipulata died at this high temperature. Conversely, seedling of S. latifolius died at the low temperature of 15°C. However, in field experiment S. latifolius failed to germinate in the available degraded environments, probably because of predation and because the soil is not able to retain water long enough to support seedling growth. We, therefore, conclude that in this part of Uganda, nursery assistance is needed to establish healthy populations of Sarcocephalus and many other endangered trees.     

Levels of endemism are not necessarily biased by the co-presence of species with different range sizes: a case study of Vilenkin and Chikatunov's models

Aim  To illustrate problems in the methods proposed by B. Vilenkin and V. Chikatunov to study levels of endemism and species–area relationships.
Location  The study used data on the distribution of tenebrionid beetles (Coleoptera, Tenebrionidae) on the Aegean Islands (Greece).
Methods  A total of 32 islands and 170 taxa (species and subspecies) were included in this study. Levels of endemism were evaluated both as the proportion of endemic taxa, and according to the methods proposed by Vilenkin and Chikatunov, which are based on the number of non-endemic taxa and various relationships with area. A model of the species–area relationship proposed by these authors was also analysed.
Results  The number of endemic taxa was positively correlated with the number of taxa with different distribution types, but this positive correlation did not influence the estimation of the level of endemism. In fact, the commonly used estimate of endemicity as a percentage was strongly correlated with the endemism values calculated according to the method of Vilenkin and Chikatunov. The usual power function fitted the species–area relationship as well as the most complicated method of Vilenkin and Chikatunov.
Main conclusions  As hypothesized by Vilenkin and Chikatunov, the number of endemic taxa was influenced both by the number of taxa of other biogeographical ranks, and by an island's area. However, explanations for the positive relationship between the number of endemic taxa and taxa of different biogeographical ranks are equivocal. Importantly, this relationship did not necessarily influence the level of endemism, which could be expressed adequately by percentages. The method proposed by Vilenkin and Chikatunov to estimate the species–area relationship cannot be clearly justified on theoretical grounds and is of questionable practical utility.     

EVOLUTION OF GENERALISTS AND SPECIALISTS IN SPATIALLY HETEROGENEOUS ENVIRONMENTS

Quantitative genetic models are used to investigate the evolution of generalists and specialists in a coarse-grained environment with two habitat types when there are costs attached to being a generalist. The outcomes for soft and hard selection models are qualitatively different. Under soft selection (e.g., for juvenile or male-reproductive traits) the population evolves towards the single peak in the adaptive landscape. At equilibrium, the population mean phenotype is a compromise between the reaction that would be optimal in both habitats and the reaction with the lowest cost. Furthermore, the equilibrium is closer to the optimal phenotype in the most frequent habitat, or the habitat in which selection on the focal trait is stronger. A specialist genotype always has a lower fitness than a generalist, even when the costs are high. In contrast, under hard selection (e.g., for adult or female-reproductive traits) the adaptive landscape can have one, two, or three peaks; a peak represents a population specialized to one habitat, equally adapted to both habitats, or an intermediate. One peak is always found when the reaction with the lowest cost is not much different from the optimal reaction, and this situation is similar to the soft selection case. However, multiple peaks are present when the costs become higher, and the course of evolution is then determined by initial conditions, and the region of attraction of each peak. This implies that the evolution of specialization and phenotypic plasticity may not only depend on selection regimes within habitats, but also on contingent, historical events (migration, mutation). Furthermore, the evolutionary dynamics in changing environments can be widely different for populations under hard and soft selection. Approaches to measure costs in natural and experimental populations are discussed.     

The distribution of genetic variation in Norway spruce (Picea abies Karst.) populations in the western Alps

Aim  In order to look for a possible centre of survival for the Norway spruce ( Picea abies Karst.) in the south-western Alps, six natural populations of this area were investigated by means of genetic markers in order to assess the degree and the distribution of genetic diversity within the species.
Location  Western and South-western Alps.
Methods  Populations were genotyped using seven simple sequence repeat (SSR) markers. Basic population genetics parameters were estimated and the amount of genetic differentiation calculated.
Results  A large amount of variability was found (0.59 <  H _e < 0.67); genetic differentiation as measured by F _ST was 0.05, close to other similar studies; no isolation by distance was detected by a Mantel test. Analysis of molecular variance confirmed a high degree of variability within populations and a low degree of variability among populations. Finally, the number of populations from which those observed could have arisen was estimated by Bayesian analysis.
Main conclusions  The results presented here suggest that the present populations derive their genetic make-up from three inferred clusters. The possible existence in this area of a relict/refuge population during the last glaciation is discussed.     

Spatial genetic structure of a small rodent in a heterogeneous landscape

Gene flow in natural populations may be strongly influenced by landscape features. The integration of landscape characteristics in population genetic studies may thus improve our understanding of population functioning. In this study, we investigated the population genetic structure and gene flow pattern for the common vole, Microtus arvalis, in a heterogeneous landscape characterised by strong spatial and temporal variation. The studied area is an intensive agricultural zone of approximately 500 km² crossed by a motorway. We used individual-based Bayesian methods to define the number of population units and their spatial borders without prior delimitation of such units. Unexpectedly, we determined a single genetic unit that covered the entire area studied. In particular, the motorway considered as a likely barrier to dispersal was not associated with any spatial genetic discontinuity. Using computer simulations, we demonstrated that recent anthropogenic barriers to effective dispersal are difficult to detect through analysis of genetic variation for species with large effective population sizes. We observed a slight, but significant, pattern of isolation by distance over the whole study site. Spatial autocorrelation analyses detected genetic structuring on a local scale, most probably due to the social organisation of the study species. Overall, our analysis suggests intense small-scale dispersal associated with a large effective population size. High dispersal rates may be imposed by the strong spatio-temporal heterogeneity of habitat quality, which characterises intensive agroecosystems.