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.     

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.     

Dissipative particle dynamics simulation of a gold nanoparticle system

Dissipative particle dynamics (DPD) was carried out to study systems containing gold atoms, organic ether (oligohydroquinonyl ether terminated with a thiol group) and organic solvents. The components in the simulated system are very different in size and chemical nature. Our simulation showed that the reproduction of the macroscopic experimental phase separation, properly dividing the polymeric molecule into beads, selecting the size of gold bead, and choosing the appropriate interaction parameters between beads are crucial. In addition, the solvent effect was the dominant factor for the formation of spherical aggregates of Au atoms and organic ether molecules. We report the interaction strengths between the solvent and gold clusters. Our work has demonstrated that DPD methods can be applied to the study of complex meso-scale systems.     

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.     

Evolutionary history of Scinax treefrogs on land‐bridge islands in south‐eastern Brazil

Aim We investigated how Pleistocene refugia and recent (c. 12,000 years ago) sea level incursions shaped genetic differentiation in mainland and island populations of the Scinax perpusillus treefrog group. Location Brazilian Atlantic Forest, São Paulo state, south‐eastern Brazil. Methods Using mitochondrial and microsatellite loci, we examined population structure and genetic diversity in three species from the S. perpusillus group, sampled from three land‐bridge islands and five mainland populations, in order to understand the roles of Pleistocene forest fragmentation and sea level incursions on genetic differentiation. We calculated metrics of relatedness and genetic diversity to assess whether island populations exhibit signatures of genetic drift and isolation. Two of the three island populations in this study have previously been described as new species based on a combination of distinct morphological and behavioural characters, thus we used the molecular datasets to determine whether phenotypic change is consistent with genetic differentiation. Results Our analyses recovered three distinct lineages or demes composed of northern mainland São Paulo populations, southern mainland São Paulo populations, and one divergent island population. The two remaining island populations clustered with samples from adjacent mainland populations. Estimates of allelic richness were significantly lower, and estimates of relatedness were significantly higher, in island populations relative to their mainland counterparts. Main conclusions Fine‐scale genetic structure across mainland populations indicates the possible existence of local refugia within São Paulo state, underscoring the small geographic scale at which populations diverge in this species‐rich region of the Atlantic Coastal Forest. Variation in genetic signatures across the three islands indicates that the populations experienced different demographic processes after marine incursions fragmented the distribution of the S. perpusillus group. Genetic signatures of inbreeding and drift in some island populations indicate that small population sizes, coupled with strong ecological selection, may be important evolutionary forces driving speciation on land‐bridge islands.     

Palaeocommunity Dynamics and Behavioral Analysis of Conichnus: Bhuj Formation (Lower Cretaceous),Kachchh-India

A palaeocommunity of large Conichnus conicus, a conical, cone-in-cone shaped burrow, created by sea anemones, occurs in medium-grained, crossbedded, well-sorted sandstone in the middle part of the Cretaceous Guneri Member of the Bhuj Formation in India. The trace fossil Conichnus is considered to be a common element of the Skolithos ichnofacies and is interpreted to reflect equilibrium movement in response to substrate aggradation. In the present study, three different varieties of Conichnus conicus are distinguished based on morphology and internal fabric. Community dynamics and burrowing behavior are revealed by inter-burrow relationships, burrow initiation levels and sedimentology. Three types of behavior are envisaged: retrusive equilibrium, protrusive equilibrium response, and escape behavior. Palaeocommunity dynamics show that the tracemakers consisted of only adult organisms that initiated burrows during neap tides and are adapted to feed effectively during weak flow conditions. The occurrence of Conichnus palaeocommunity in the Guneri Member indicates the tidal conditions in a fully marine setting. Results presented herein may aid in the understanding of palaeocommunity dynamics in other shallow marine sequences.