Receptor analysis: An arithmetic correction improves precision and accuracy

Data of receptor analysis by ligand binding experiments should be processed using the formula DCORR = (B1 - B2.F1/F2)/VS.DCORR is an estimate of the concentration of receptor-bound radioligand; B1 and F1 are estimates of bound and free radioligand in assay 1; B2 and F2 are the corresponding values obtained from the parallel assay 2, which contains an additional excess of nonlabeled ligand; VS is the volume of assays 1 and 2 that was submitted to separation. DCORR will be superior to the conventional formula, D = (B1 - B2)/VS, if the radiolabeled receptor-ligand complexes are incompletely separated from nonspecifically bound and free radioligands. DCORR corrects for the systematic underestimation of the specifically bound radioligand implicated in D as well as for random errors due to imprecise pipetting during preparation of the parallel assays. The superiority of DCORR over D is verified by processing the data of androgen receptor analyses using agar gel electrophoresis for separation of bound and free radioligand.     

Abundance and degree of dispersion of genomic d(GA) n ·d(TC) n sequences

Summary The abundance of d(GA) _n ·d(TC) _n tracts was determined in genomes of rodents and primates. Dot blot hybridization assays revealed that such tracts constitute 0.40%, 0.30%, and 0.40%, respectively, of the rat, hamster, and mouse genomes, but only 0.07% and 0.05% of the human and monkey genomes. A plaque hybridization assay of rat and human genomic libraries showed that 37% and 16%, respectively, of the recombinant phages in these libraries contain d(GA) _n ·d(TC) _n tracts. A survey of sequences stored in the GenBank data bank showed that a significant fraction of the stored rodent genes (about 2.0%) contain long d(GA) _n ·d(TC) _n tracts (n> 30) with <10% mismatching. The primate genes contain only shorter tracts (n<15) with <10% mismatching. In addition, the rodent and the primate genes contain tracts with larger degrees of mismatching. The chicken, which represents an entirely different branch of the evolutionary tree, was found to be as low in d(GA) _n ·d(TC) _n tracts as the primates. It is suggested that a common ancestor of the rodents has acquired the ability to amplify d(GA) _n ·d(TC) _n tracts.     

Feeding habits of larval Mirogrex terraesanctae (Steinitz, 1952) in Lake Kinneret (Israel) I. Field study

Analysis of the food composition, distribution, lengths and dry weights of larval bleak, Mirogrex terraesanctae (Steinitz, 1952) in Lake Kinneret, Israel was conducted. Indices of electivity of ingested prey organisms were also determined. Larvae were surveyed throughout the 1989–90 reproductive seasons (Dec–Mar). Small larvae (<10.28 mm SL) preferentially select prey items smaller than 180 µ. Dominant zooplankters in the larval guts included: Bosmina longirostris, Ceriodaphnia reticulata and C. rigaudi, Asplanchna priodonita, Synchaeta oblonga, S. pectinata and juvenile cyclopoid copepods. Diaphanosoma brachiurum was rarely found (instars only) and no adult copepods were observed in larval guts. Some larvae specimens were found with up to 500 undigested (intact) accidentally ingested cells of Peridinium spp. per gut.     

Feeding habits of larval Mirogrex terraesanctae (Steinitz, 1952) in Lake Kinneret (Israel) II. Experimental study

Interactions between the larvae of Mirogrex terraesanctae (Steinitz, 1952) in Lake Kinneret, Israel, and their zooplankton prey were studied experimentally. Prey species preference and size selectivities were measured. Larvae were hatched in the lab from eggs collected in the field, and fed different food items in various concentrations. The food items included lake zooplankton, algae, and commercial pellets. It was shown that small, first feeding larvae (7–8.5 mm SL) prefer small bodied zooplankters (< 180 µ). The effect of these food sources on larval growth was measured. It was found that larval Mirogrex grew at a higher rate when fed zooplankton prey sized from 63 µ–250 µ. Food items smaller than 63 µ, larger than 250 µ and Scenedesmus sp., produced less than optimal growth rates. The importance of Mirogrex feeding habits and their potential influence on the Kinneret ecosystem is considered.     

Nullius in Verba1: Advancing Data Transparency in Industrial Ecology

With the growth of the field of industrial ecology (IE), research and results have increased significantly leading to a desire for better utilization of the accumulated data in more sophisticated analyses. This implies the need for greater transparency, accessibility, and reusability of IE data, paralleling the considerable momentum throughout the sciences. The Data Transparency Task Force (DTTF) was convened by the governing council of the International Society for Industrial Ecology in late 2016 to propose best‐practice guidelines and incentives for sharing data. In this article, the members of the DTTF present an overview of developments toward transparent and accessible data within the IE community and more broadly. We argue that increased transparency, accessibility, and reusability of IE data will enhance IE research by enabling more detailed and reproducible research, and also facilitate meta‐analyses. These benefits will make the results of IE work more timely. They will enable independent verification of results, thus increasing their credibility and quality. They will also make the uptake of IE research results easier within IE and in other fields as well as by decision makers and sustainability practitioners, thus increasing the overall relevance and impact of the field. Here, we present two initial actions intended to advance these goals: (1) a minimum publication requirement for IE research to be adopted by the Journal of Industrial Ecology; and (2) a system of optional data openness badges rewarding journal articles that contain transparent and accessible data. These actions will help the IE community to move toward data transparency and accessibility. We close with a discussion of potential future initiatives that could build on the minimum requirements and the data openness badge system.     

Nongrowing season methane emissions–a significant component of annual emissions across northern ecosystems

Wetlands are the single largest natural source of atmospheric methane (CH₄), a greenhouse gas, and occur extensively in the northern hemisphere. Large discrepancies remain between “bottom‐up” and “top‐down” estimates of northern CH₄ emissions. To explore whether these discrepancies are due to poor representation of nongrowing season CH₄ emissions, we synthesized nongrowing season and annual CH₄ flux measurements from temperate, boreal, and tundra wetlands and uplands. Median nongrowing season wetland emissions ranged from 0.9 g/m² in bogs to 5.2 g/m² in marshes and were dependent on moisture, vegetation, and permafrost. Annual wetland emissions ranged from 0.9 g m^?2 year^?1 in tundra bogs to 78 g m^?2 year^?1 in temperate marshes. Uplands varied from CH₄ sinks to CH₄ sources with a median annual flux of 0.0 ± 0.2 g m^?2 year^?1. The measured fraction of annual CH₄ emissions during the nongrowing season (observed: 13% to 47%) was significantly larger than that was predicted by two process‐based model ensembles, especially between 40° and 60°N (modeled: 4% to 17%). Constraining the model ensembles with the measured nongrowing fraction increased total nongrowing season and annual CH₄ emissions. Using this constraint, the modeled nongrowing season wetland CH₄ flux from >40° north was 6.1 ± 1.5 Tg/year, three times greater than the nongrowing season emissions of the unconstrained model ensemble. The annual wetland CH₄ flux was 37 ± 7 Tg/year from the data‐constrained model ensemble, 25% larger than the unconstrained ensemble. Considering nongrowing season processes is critical for accurately estimating CH₄ emissions from high‐latitude ecosystems, and necessary for constraining the role of wetland emissions in a warming climate.     

Land use changes could modify future negative effects of climate change on old‐growth forest indicator species

Aim

Climate change is expected to have major impacts on terrestrial biodiversity at all ecosystem levels, including reductions in species‐level distribution and abundance. We aim to test the extent to which land use management, such as setting‐aside forest from production, could reduce climate‐induced biodiversity impacts for specialist species over large geographical gradients.

Location

Sweden.

Methods

We applied ensembles of species distribution models based on citizen science data for six species of red‐listed old‐forest indicator fungi confined to spruce dead wood. We tested the effect on species habitat suitabilities of alternative climate change scenarios and varying amounts of forest set‐aside from production over the coming century.

Results

With 3.6% of forest area set‐aside from production and assuming no climate change, overall habitat suitabilities for all six species were projected to increase in response to maturing spruce in set‐aside forest. However, overall habitat suitabilities for all six species were projected to decline under climate change scenario RCP4.5 (intermediate–low emissions), with even greater declines projected under RCP 8.5 (high emissions). Increasing the amount of forest set‐aside to 16% resulted in significant increases in overall habitat suitability, with one species showing an increase. A further increase to 32% forest set‐aside resulted in considerably more positive trends, with three of six species increasing.

Main conclusions

There is interspecific variation in the importance of future macroclimate and resource availability on species occurrence. However, large‐scale conservation measures, such as increasing resource availability through setting aside forest from production, could reduce future negative effects from climate change, and early investment in conservation is likely to reduce the future negative impacts of climate change on specialist species.     

Species‐poor and low‐lying sites are more ecologically unique in a hyperdiverse Amazon region: Evidence from multiple taxonomic groups

Aim

We analysed beta‐diversity patterns of various biological groups simultaneously, from the perspective of site ecological uniqueness. We also investigated whether ecological uniqueness variation could be explained by variations in environmental conditions and spatial variables.

Data

Central Amazonia.

Methods

We estimated the total beta diversity and ecological uniqueness for 14 biological groups, including plants and animals, sampled at the same sites on a mesoscale in central Amazonia, Brazil. The uniqueness values for all biological groups were combined in a single matrix (multi‐taxa matrix of site uniqueness), which was then used as a response variable matrix in a partial redundancy analysis. We also investigated differences in the uniqueness patterns between plant and animal groups.

Results

In general, plants showed higher total beta diversity than animals. For plants, uniqueness was explained mainly by environmental conditions, while for animals, uniqueness was also related to spatial variables. Although variation in uniqueness was mainly related to soil clay content, it is difficult to determine a single major environmental variable underlying the variation in uniqueness because the topographical gradient influences many of them, including soil clay content.

Main Conclusion

The uniqueness values were higher in low‐lying areas, indicating that near‐stream sites were more ecologically unique. Despite the lower number of species in the lowlands, their unique biota contributed strongly to the maintenance of the total beta diversity of the area. This finding should be considered in conservation plans that aim to represent and preserve the regional biota. Our approach proved to be useful to analyse and compare the ecological uniqueness of multiple taxa.