Colonization and extinction of land planarians (Platyhelminthes,Tricladida) in a Brazilian Atlantic Forest regrowth remnant

Long-term assessments of species assemblages are valuable tools for detecting species ecological preferences and their dispersal tracks, as well as for assessing the possible effects of alien species on native communities. Here we report a 50-year-long study on population dynamics of the four species of land flatworms (Platyhelminthes, Tricladida, Terricola) that have colonized or become extinct in a 70-year-old Atlantic Forest regrowth remnant through the period 1955–2006. On the one hand, the two initially most abundant species, which are native to the study site, Notogynaphallia ernesti and Geoplana multicolor have declined over decades and at present do not exist in the forest remnant. The extinction of these species is most likely related with their preference for open vegetation areas, which presently do not exist in the forest remnant. On the other hand, the neotropical Geoplaninae 1 and the exotic Endeavouria septemlineata were detected in the forest only very recently. The long-term study allowed us to conclude that Geoplaninae 1 was introduced into the study area, although it is only known from the study site. Endeavouria septemlineata, an active predator of the exotic giant African snail, is originally known from Hawaii. This land flatworm species was observed repeatedly in Brazilian anthropogenic areas, and this is the first report of the species in relatively well preserved native forest, which may be evidence of an ongoing adaptive process. Monitoring of its geographic spread and its ecological role would be a good practice for preventing potential damaging effects, since it also feeds on native mollusk fauna, as we observed in lab conditions. Júlio Pedroni: Granted by CNPQ–Brazil.     

Factors influencing seasonal and monthly changes in the group size of chital or axis deer in southern India

Chital or axis deer (Axis axis) form fluid groups that change in size temporally and in relation to habitat. Predictions of hypotheses relating animal density, rainfall, habitat structure, and breeding seasonality, to changes in chital group size were assessed simultaneously using multiple regression models of monthly data collected over a 2 yr period in Guindy National Park, in southern India. Over 2,700 detections of chital groups were made during four seasons in three habitats (forest, scrubland and grassland). In scrubland and grassland, chital group size was positively related to animal density, which increased with rainfall. This suggests that in these habitats, chital density increases in relation to food availability, and group sizes increase due to higher encounter rate and fusion of groups. The density of chital in forest was inversely related to rainfall, but positively to the number of fruiting tree species and availability of fallen litter, their forage in this habitat. There was little change in mean group size in the forest, although chital density more than doubled during the dry season and summer. Dispersion of food items or the closed nature of the forest may preclude formation of larger groups. At low densities, group sizes in all three habitats were similar. Group sizes increased with chital density in scrubland and grassland, but more rapidly in the latter—leading to a positive relationship between openness and mean group size at higher densities. It is not clear, however, that this relationship is solely because of the influence of habitat structure. The rutting index (monthly percentage of adult males in hard antler) was positively related to mean group size in forest and scrubland, probably reflecting the increase in group size due to solitary males joining with females during the rut. The fission-fusion system of group formation in chital is thus interactively influenced by several factors. Aspects that need further study, such as interannual variability, are highlighted.     

Climatic sensitivity of species’ vegetative and reproductive phenology in a Hawaiian montane wet forest

Understanding how tropical tree phenology (i.e., the timing and amount of seed and leaf production) responds to climate is vital for predicting how climate change may alter ecological functioning of tropical forests. We examined the effects of temperature, rainfall, and photosynthetically active radiation (PAR) on seed phenology of four dominant species and community-level leaf phenology in a montane wet forest on the island of Hawaiʻi using monthly data collected over ~ 6 years. We expected that species phenologies would be better explained by variation in temperature and PAR than rainfall because rainfall at this site is not limiting. The best-fit model for all four species included temperature, rainfall, and PAR. For three species, including two foundational species of Hawaiian forests (Acacia koa and Metrosideros polymorpha), seed production declined with increasing maximum temperatures and increased with rainfall. Relationships with PAR were the most variable across all four species. Community-level leaf litterfall decreased with minimum temperatures, increased with rainfall, and showed a peak at PAR of ~ 400 μmol/m²s⁻¹. There was considerable variation in monthly seed and leaf production not explained by climatic factors, and there was some evidence for a mediating effect of daylength. Thus, the impact of future climate change on this forest will depend on how climate change interacts with other factors such as daylength, biotic, and/or evolutionary constraints. Our results nonetheless provide insight into how climate change may affect different species in unique ways with potential consequences for shifts in species distributions and community composition.     

Lysine Succinylation of VBS Contributes to Sclerotia Development and Aflatoxin Biosynthesis in Aspergillus flavus

Aspergillus flavus is a common saprophytic and pathogenic fungus, and its secondary metabolic pathways are one of the most highly characterized owing to its aflatoxin (AF) metabolite affecting global economic crops and human health. Different natural environments can cause significant variations in AF synthesis. Succinylation was recently identified as one of the most critical regulatory post-translational modifications affecting metabolic pathways. It is primarily reported in human cells and bacteria with few studies on fungi. Proteomic quantification of lysine succinylation (Ksuc) exploring its potential involvement in secondary metabolism regulation (including AF production) has not been performed under natural conditions in A. flavus. In this study, a quantification method was performed based on tandem mass tag labeling and antibody-based affinity enrichment of succinylated peptides via high accuracy nano-liquid chromatography with tandem mass spectrometry to explore the succinylation mechanism affecting the pathogenicity of naturally isolated A. flavus strains with varying toxin production. Altogether, 1240 Ksuc sites in 768 proteins were identified with 1103 sites in 685 proteins quantified. Comparing succinylated protein levels between high and low AF-producing A. flavus strains, bioinformatics analysis indicated that most succinylated proteins located in the AF biosynthetic pathway were downregulated, which directly affected AF synthesis. Versicolorin B synthase is a key catalytic enzyme for heterochrome B synthesis during AF synthesis. Site-directed mutagenesis and biochemical studies revealed that versicolorin B synthase succinylation is an important regulatory mechanism affecting sclerotia development and AF biosynthesis in A. flavus. In summary, our quantitative study of the lysine succinylome in high/low AF-producing strains revealed the role of Ksuc in regulating AF biosynthesis. We revealed novel insights into the metabolism of AF biosynthesis using naturally isolated A. flavus strains and identified a rich source of metabolism-related enzymes regulated by succinylation.     

Carbon emissions performance of commercial logging in East Kalimantan,Indonesia

Adoption of reduced‐impact logging (RIL) methods could reduce CO₂ emissions by 30–50% across at least 20% of remaining tropical forests. We developed two cost effective and robust indices for comparing the climate benefits (reduced CO₂ emissions) due to RIL. The indices correct for variability in the volume of commercial timber among concessions. We determined that a correction for variability in terrain slope was not needed. We found that concessions certified by the Forest Stewardship Council (FSC, N = 3), when compared with noncertified concessions (N = 6), did not have lower overall CO₂ emissions from logging activity (felling, skidding, and hauling). On the other hand, FSC certified concessions did have lower emissions from one type of logging impact (skidding), and we found evidence of a range of improved practices using other field metrics. One explanation of these results may be that FSC criteria and indicators, and associated RIL practices, were not designed to achieve overall emissions reductions. Also, commonly used field metrics are not reliable proxies for overall logging emissions performance. Furthermore, the simple distinction between certified and noncertified concessions does not fully represent the complex history of investments in improved logging practices. To clarify the relationship between RIL and emissions reductions, we propose the more explicit term ‘RIL‐C’ to refer to the subset of RIL practices that can be defined by quantified thresholds and that result in measurable emissions reductions. If tropical forest certification is to be linked with CO₂ emissions reductions, certification standards need to explicitly require RIL‐C practices.     

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.