Long‐term population dynamics of a coral reef gastropod and responses to disturbance

The age‐specific density of the red‐lipped stromb Strombus luhuanus (Mollusca: Gastropoda) was monitored over 13 years (1981–1993) at four locations on the intertidal reef flat at Heron Island, Great Barrier Reef. Densities were highly variable, but there were persistent, location‐specific differences in population density, age structure and adult body size, the latter indicating that the populations were not extensively linked by adult movement. There was relatively high recruitment at most locations in 1984, 1989 and 1993, each occurring approximately 2 years after El Niño/Southern Oscillation events, although recruit density during these years varied in both space and time. The studied strombs experienced three disturbance events: (i) experimental harvesting at two locations (1984–1985); (ii) siltation from a harbour dredging operation (1987–1988); and (iii) a severe cyclone (1992). Resilience to harvesting at a local scale (0.5–2 ha) was high: density had recovered within a year, due to immigration of adults and older juveniles. Strombus luhuanus responded much more strongly to broad‐scale changes to its environment than to localized harvesting. After dredging, there was a progressive density decline coupled with low recruitment at two locations, and a later decline at a third location, followed by a recruitment‐driven rebound after the cyclone. Generalized environmental effects of siltation and the cyclone were also reflected in substantial changes in algal cover. Long‐term variations in environmental conditions probably cause high temporal variation over large spatial scales through effects on the survival of larvae or recruits. Localized short‐term field monitoring of such species would give a misleading picture of key factors affecting population dynamics.     

Diversity and distribution of reptiles in Romania

The reptile fauna of Romania comprises 23 species, out of which 12 species reach here the limit of their geographic range. We compiled and updated a national database of the reptile species occurrences from a variety of sources including our own field surveys, personal communication from specialists, museum collections and the scientific literature. The occurrence records were georeferenced and stored in a geodatabase for additional analysis of their spatial patterns. The spatial analysis revealed a biased sampling effort concentrated in various protected areas, and deficient in the vast agricultural areas of the southern part of Romania. The patterns of species richness showed a higher number of species in the warmer and drier regions, and a relatively low number of species in the rest of the country. Our database provides a starting point for further analyses, and represents a reliable tool for drafting conservation plans.     

Mate detection success of maleClethrionomys rufocanus in relation to the spatial distribution of sexually receptive females

Summary Mate detection success of male grey-sided voles,Clethrionomys rufocanus, in relation to the spatial distribution of sexually receptive females was studied in an experimental island population. The spatiotemporal distribution of receptive females was controlled by containing females in small, mobile wire-mesh cages, whereas the response by free-ranging males was monitored by means of radiotelemetry. Males were on average more successful in finding oestrous females when females were spatially clumped than when females were spatially overdispersed. In addition, the variance (CV) in male mate detecting success was highest when females had an overdispersed spatial distribution. These results are consistent with predictions from a theoretical model (Ims, 1988b) analysing the effect of mate distribution on male mating success, and with empirical results on prey detection success of predators searching for prey.     

Influences of temporal independence of data on modelling species distributions

Modelling species distributions has been widely used to understand present and future potential distributions of species, and can provide adaptation and mitigation information as references for conservation and management under climate change. However, various methods of data splitting to develop and validate functions of the models do not get enough attention, which may mislead the interpretation of predicted results. We used the Taiwanese endemic birds to test the influences of temporal independence of datasets on model performance and prediction. Training and testing data were considered to be independent if they were collected during different survey periods (1993–2004 and 2009–2010). The results indicated no significant differences of six model performance measures (AUC, kappa, TSS, accuracy, sensitivity, and specificity) among the combinations of training and testing datasets. Both species- and grid cell-based assessments differed significantly between predictions by the annual and pooled training data. We also found an average of 85.8% similarity for species presences and absences in different survey periods. The remaining dissimilarity was mostly caused by species observed in the late survey period but not in the early one. The method of data splitting, yielding training and testing data, is critical for resulting model species distributions. Even if similar model performance exists, different methods can lead to different species distributional maps. More attention needs to be given to this issue, especially when amplifying these models to project species distributions in a changing world.     

Modelling biomass of mountainous grasslands by including a species composition map

High mountain grasslands offer multiple goods and services to society but are severely threatened by improper land use practices such as abandonment or rapid intensification. In order to reduce abandonment and strengthen the common extensive agricultural practice a sustainable land use management of high mountain grasslands is needed. A spatially detailed yield assessment helps to identify possible meadows or, on the contrary, areas with a low carrying capacity in a region, making it easier to manage these sites. Such assessments are rarely available for remote and inaccessible areas. Remotely sensed vegetation indices are able to provide valuable information on grassland properties. These indices tend, however, to saturate for high biomass. This affects their applicability to assessments of high-yield grasslands.The main aim of this study was to model a spatially explicit grassland yield map and to test whether saturation issues can be tackled by consideration of plant species composition in the modelling process. The high mountain grassland of the subalpine belt (1800 – 2500 m a.s.l.) in the Kazbegi region, Greater Caucasus, Georgia, was chosen as test site for its strong species composition and yield gradients.We first modelled the species composition of the grassland described as metrically scaled gradients in the form of ordination axes by random forest regression. We then derived vegetation indices from Rapid Eye imagery, and topographic variables from a digital elevation model, which we used together with the multispectral bands as predictive variables. For comparison, we performed two yield models, one excluding the species composition maps and one including the species composition map as predictors. Moreover, we performed a third individual model, with species composition as predictors and a split dataset, to produce the final yield map.Three main grassland types were found in the vegetation analysis: Hordeum violaceum-meadows, Gentianella caucasea-grassland and Astragalus captiosus-grassland. The three random forest regression models for the ordination axes explained 64%, 33% and 46% of the variance in species composition. Independent validation of modelled ordination scores against a validation data set resulted in an R² of 0.64, 0.32 and 0.46 for the first, second and third axes, respectively. The model based on species composition resulted in a R² = 0.55, whereas the benchmark model showed weaker relationships between yield and the multispectral reflectance, vegetation indices, and topographical parameters (R² = 0.42). The final random forest yield model used to derive the yield map resulted in 62% variance explained and an R² = 0.64 between predicted and observed biomass. The results further indicate that high yields are generally difficult to predict with both models.The benefit of including a species composition map as a predictor variable for grassland yield lies in the preservation of ecologically meaningful features, especially the occurrence of high yielding vegetation type of Hordeum violaceum meadows is depicted accurately in the map. Even though we used a gradient based design, sharp boundaries or immediate changes in productivity were visible, especially in small structures such as arable fields or roads (Fig. 6b), making it a valuable tool for sustainable land use management. The saturation effect however, was mitigated by using species composition as predictor variables but is still present at high yields.     

荒漠灌丛土壤动物分布及其生态功能

在干旱、半干旱荒漠生态系统中,灌丛作为一种重要的植被类型,其独特的形态和生理适应特性能够有效促进退化生态系统结构与功能的恢复。土壤动物是荒漠生态系统中不可或缺的重要组成部分,对促进灌丛"肥岛"演变具有重要的生态作用,有利于灌丛生态功能的发挥及退化生态系统的恢复。近年来,国内外学者对荒漠灌丛微生境土壤动物的研究逐步深入,取得大量的研究成果。在此基础上,首先综述荒漠灌丛微生境土壤动物群落分布和生态功能,总结灌丛与土壤动物分布间作用关系的数学模型,针对荒漠灌丛土壤动物研究中存在的问题提出了未来可能的研究方向和建议。     

Rice straw decomposition in rice-field soil

Rice straw, buried in a rice-field during the dry season decomposed at a rate of 0.0075 day-1. Seventy five percent of the biomass, 70 percent carbon, 50 percent nitrogen and 30 percent phosphorus remained after 139 days of decomposition. Rice straw decomposition furnished 33% N and 8% P of the total nitrogen and phosphorus provided by man.