Precipitation on abscised leaves modulates leaf‐mining beetle (Trachys yanoi) survivorship and population dynamics

1. We clarified the effects of early leaf abscission on the survivorship of the leaf‐mining beetle Trachys yanoi Y. Kurosawa (Coleoptera: Buprestidae) and the underlying mechanism in relation to weather conditions in Japan. Trachys yanoi is an insect pest of zelkova trees [Zelkova serrata (Thunb.) Makino (Rosales: Ulmaceae)]. Larvae burrow into zelkova leaves and feed on leaf tissue, causing early leaf abscission. 2. This study investigated the relationship between the beetle population and weather conditions over 10 years in a zelkova forest. The effects of moisture and temperature on adult emergence from early abscised leaves were examined in the laboratory and in the field. 3. The beetle population in the studied forest was negatively affected by high precipitation levels when the beetles still inhabited early abscised leaves. Fewer adults emerged from early abscised leaves under wet conditions than under dry conditions, in both laboratory and field tests. 4. These results demonstrate that early leaf abscission plays an important role in leaf‐mining beetle survivorship and population dynamics, and that the amount of precipitation when leaf‐mining beetles still inhabit early abscised leaves modulates this effect. 5. Because precipitation when leaf‐mining beetles still inhabit early abscised leaves was mainly driven by an East Asian rainy season front, the beetle population dynamics were affected by the activity of the front.     

Large-scale isolation, fractionation, and purification of soluble starch-synthesizing enzymes: starch synthase and branching enzyme from potato tubers

Soluble starch-synthesizing enzymes, starch synthase (SSS) and starch-branching enzyme (SBE), were isolated, fractionated, and purified from white potato tubers (Solanum tuberosum) on a large scale. Five steps were used: potato tuber extract from 2 kg of peeled potatoes, two acetone precipitations, and two fractionations on a large ultrafiltration polysulfone hollow fiber 100 kDa cartridge. Three kinds of fractions were obtained: (1) mixtures of SSS and SBE; (2) SSS, free of SBE; and (3) SBE, free of SSS. Contaminating enzymes (amylase, phosphorylase, and disproportionating enzyme) and carbohydrates were absent from the 2nd acetone precipitate and from the column fractions, as judged by the Molisch test and starch triiodide test. Activity yields of 122% (300,000-400,000 units) of SSS fractions and 187% (40,000-50,000 units) of SBE fractions were routinely obtained from the cartridge. Addition of 0.04% (w/v) polyvinyl alcohol 50 K and 1 mM dithiothreitol to the glycine buffer (pH 8.4) gave long-term stability and higher yields of SSS and SBE, due to activation of inactive enzymes. Several SSS and SBE fractions from the two fractionations had very high specific activities, indicating high degrees of purification. Polyacrylamide gel electrophoresis of selected SSS and SBE fractions gave two to five SSS and/or SBE activity bands, corresponding to the one to five protein bands present in the 2nd acetone precipitate.     

Brassica juncea can improve selenite and selenate abatement in selenium contaminated soils through the aid of its rhizospheric bacterial population

Brassica juncea was grown in a soil spiked with selenium oxyanions (selenite and selenate) in order to verify the contribution of both plants and rhizospheric bacteria to the abatement of soluble forms of the metalloid. A mass balance of selenium was calculated in pots and the different chemical species of this contaminant were measured. Evidence gained suggests that selenium oxyanions were reduced into less bioavailable forms thank to a marked contribution of the soil bacterial population. Rhizobacteria resulted particularly elicited by the presence of B. juncea which directly participated in selenium decontamination through either phytoextraction or putative volatilisation. Moreover, these microbes colonizing B. juncea root system were monitored by both culture dependent and culture independent methods (i.e. DGGE analysis). Finally, bacterial isolates were tested in vitro for their resistance to selenium oxyanions.     

Consequences of climate and body size on the foraging performance of seed‐eating ants

1. Changes in climatic factors could have major effects on the foraging performance of animals. To date, however, no study has attempted to examine the concurrent effect of different climatic factors on foraging performance of individual organisms. 2. In the present study, this issue was addressed by studying changes in foraging performance of seed‐eating ant colonies of the genus Messor in response to variation in precipitation and ambient temperature along a macroecological gradient. In addition, we examined the way three colony‐level attributes, foraging distance, forager number, and variance in worker‐size, could affect foraging performance in those ants. Foraging performance was measured as size matching, i.e. the correlation between forager size and load size. The study was carried out for 2 years in six sites along a south‐north productivity gradient in a semi‐arid region of the Eastern‐Mediterranean. 3. Size matching increased with increased precipitation as well as with an increase in worker‐size variability, but slightly decreased with increasing temperatures, as predicted by foraging‐decision models. In contrast, foraging distance had no effect on size matching. Interestingly, size matching showed a unimodal relationship with forager number. 4. These results indicate that interplay between climate and body size affects foraging performance either directly via physiological constraints, or indirectly through their effect on food availability. Moreover, this is one of the first evidences to support the assumption that ant colonies can differ in their ability to optimally allocate their workforce in natural environments. This emphasises the importance of studying the way foraging strategies vary across environmental gradients at macroecological scales.     

Analyzing trait-climate relationships within and among taxa using machine learning and herbarium specimens

Premise

Continental-scale leaf trait studies can help explain how plants survive in different environments, but large data sets are costly to assemble at this scale. Automating the measurement of digitized herbarium collections could rapidly expand the data available to such studies. We used machine learning to identify and measure leaves from existing, digitized herbarium specimens. The process was developed, validated, and applied to analyses of relationships between leaf size and climate within and among species for two genera: Syzygium (Myrtaceae) and Ficus (Moraceae).

Methods

Convolutional neural network (CNN) models were used to detect and measure complete leaves in images. Predictions of a model trained with a set of 35 randomly selected images and a second model trained with 35 user-selected images were compared using a set of 50 labeled validation images. The validated models were then applied to 1227 Syzygium and 2595 Ficus specimens digitized by the National Herbarium of New South Wales, Australia. Leaf area measurements were made for each genus and used to examine links between leaf size and climate.

Results

The user-selected training method for Syzygium found more leaves (9347 vs. 8423) using fewer training masks (218 vs. 225), and found leaves with a greater range of sizes than the random image training method. Within each genus, leaf size was positively associated with temperature and rainfall, consistent with previous observations. However, within species, the associations between leaf size and environmental variables were weaker.

Conclusions

CNNs detected and measured leaves with levels of accuracy useful for trait extraction and analysis and illustrate the potential for machine learning of herbarium specimens to massively increase global leaf trait data sets. Within-species relationships were weak, suggesting that population history and gene flow have a strong effect at this level. Herbarium specimens and machine learning could expand sampling of trait data within many species, offering new insights into trait evolution.     

The future of soil invertebrate communities in polar regions: different climate change responses in the Arctic and Antarctic?

The polar regions are experiencing rapid climate change with implications for terrestrial ecosystems. Here, despite limited knowledge, we make some early predictions on soil invertebrate community responses to predicted twenty‐first century climate change. Geographic and environmental differences suggest that climate change responses will differ between the Arctic and Antarctic. We predict significant, but different, belowground community changes in both regions. This change will be driven mainly by vegetation type changes in the Arctic, while communities in Antarctica will respond to climate amelioration directly and indirectly through changes in microbial community composition and activity, and the development of, and/or changes in, plant communities. Climate amelioration is likely to allow a greater influx of non‐native species into both the Arctic and Antarctic promoting landscape scale biodiversity change. Non‐native competitive species could, however, have negative effects on local biodiversity particularly in the Arctic where the communities are already species rich. Species ranges will shift in both areas as the climate changes potentially posing a problem for endemic species in the Arctic where options for northward migration are limited. Greater soil biotic activity may move the Arctic towards a trajectory of being a substantial carbon source, while Antarctica could become a carbon sink.