Arbuscular mycorrhizal fungi as (agro)ecosystem engineers

Symbiotic interactions have been shown to facilitate shifts in the structure and function of host plant communities. For example, parasitic plants can induce changes in plant diversity through the suppression of competitive community dominants. Arbuscular mycorrhizal (AM) fungi have also be shown to induce shifts in host communities by increasing host plant nutrient uptake and growth while suppressing non-mycorrhizal species. AM fungi can therefore function as ecosystem engineers facilitating shifts in host plant communities though the presumed physiological suppression of non-contributing or non-mycorrhizal plant species. This dichotomy in plant response to AM fungi has been suggested as a tool to suppress weed species (many of which are non-mycorrhizal) in agro-ecosystems where mycorrhizal crop species are cultivated. Rinaudo et al. (2010), this issue, have demonstrated that AM fungi can suppress pernicious non-mycorrhizal weed species including Chenopodium album (fat hen) while benefiting the crop plant Helianthus annuus (sunflower). These findings now suggest a future for harnessing AM fungi as agro-ecosystem engineers representing potential alternatives to costly and environmentally damaging herbicides.     

Incorporating movement into models of grey seal population dynamics

1. One of the most difficult problems in developing spatially explicit models of population dynamics is the validation and parameterization of the movement process. We show how movement models derived from capture-recapture analysis can be improved by incorporating them into a spatially explicit metapopulation model that is fitted to a time series of abundance data. 2. We applied multisite capture-recapture analysis techniques to photo-identification data collected from female grey seals at the four main breeding colonies in the North Sea between 1999 and 2001. The best-fitting movement models were then incorporated into state-space metapopulation models that explicitly accounted for demographic and observational stochasticity. 3. These metapopulation models were fitted to a 20-year time series of pup production data for each colony using a Bayesian approach. The best-fitting model, based on the Akaike Information Criterion (AIC), had only a single movement parameter, whose confidence interval was 82% less than that obtained from the capture-recapture study, but there was some support for a model that included an effect of distance between colonies. 4. The state-space modelling provided improved estimates of other demographic parameters. 5. The incorporation of movement, and the way in which it was modelled, affected both local and regional dynamics. These differences were most evident as colonies approached their carrying capacities, suggesting that our ability to discriminate between models should improve as the length of the grey seal time series increases.     

Evaluation of enteric methane prediction equations for dairy cows used in whole farm models

The importance of evaluating greenhouse gas (GHG) emissions from dairy cows within the whole farm setting is being realized as more important than evaluating these emissions in isolation. Current whole farm models aimed at evaluating GHG emissions make use of simple regression equations to predict enteric methane (CH₄) production. The objective of the current paper is to evaluate the performance of nine CH₄ prediction equations that are currently being used in whole farm GHG models. Data used to evaluate the prediction equations came from a collection of individual (IND) and treatment averaged (TRT) data. Equations were compared based on mean square prediction error (MSPE) and concordance correlation coefficient (CCC) analysis. In general, predictions were poor, with root MSPE (as a percentage of observed mean) values ranging from 20.2 to 52.5 for the IND database and from 24.0 to 38.2 for the TRT database and CCC values ranging from 0.009 to 0.493 for the IND database and from 0.000 to 0.271 for the TRT database. Overall, the equations of Moe & Tyrrell and IPCC Tier II performed best on the IND dataset, and the equations of Moe & Tyrrell and Kirchgeßner et al., performed best on the TRT dataset. Results show that the simple more generalized equations performed worse than those that attempted to represent important aspects of diet composition, but in general significant amounts of bias and deviation of the regression slope from unity existed for all equations. The low prediction accuracy of CH₄ equations in whole farm models may introduce substantial error into inventories of GHG emissions and lead to incorrect mitigation recommendations.     

稻飞虱预报模型及防治技术

应用回归分析法,对江苏省高邮市１９８３～１９９７年共１５年稻飞虱发生程度的历史观测资料和气象资料进行了分析,建立了中、短期预测模型,经历史资料回验,符合率８５％以上。并提出规范化药剂防治策略及技术。     

ECOBAS — A tool to develop ecosystem models exemplified by the shallow lake model EMMO

The modelling and simulation tool ECOBAS was extended in order to include special features supporting the development of ecological models. The «Graphical Model Editor» allows the connection of at least 2 modules in order to build a whole model to run simulations. With the ECOBAS simulation system the model can be tested extensively in order to find appropriate parameter sets («Parameter analysis» and «Parameter estimation») and to identify critical parameters («Sensitivity analysis»). The «Interaction Analysis» shows the internal dependencies of a model. ECOBAS integrates the steps of ecological modelling and creates well readable and complete documentations within one working step, supports modularization of models and the user is rid of the technical and numerical aspects of modelling. Hence ECOBAS is setting up complete, consistent and syntactical correct models.All new features of the ECOBAS-system will be introduced by applying it on the existing ecosystem model EMMO.     

Where will species go? Incorporating new advances in climate modelling into projections of species distributions

Bioclimatic models are the primary tools for simulating the impact of climate change on species distributions. Part of the uncertainty in the output of these models results from uncertainty in projections of future climates. To account for this, studies often simulate species responses to climates predicted by more than one climate model and/or emission scenario. One area of uncertainty, however, has remained unexplored: internal climate model variability. By running a single climate model multiple times, but each time perturbing the initial state of the model slightly, different but equally valid realizations of climate will be produced. In this paper, we identify how ongoing improvements in climate models can be used to provide guidance for impacts studies. In doing so we provide the first assessment of the extent to which this internal climate model variability generates uncertainty in projections of future species distributions, compared with variability between climate models. We obtained data on 13 realizations from three climate models (three from CSIRO Mark2 v3.0, four from GISS AOM, and six from MIROC v3.2) for two time periods: current (1985–1995) and future (2025–2035). Initially, we compared the simulated values for each climate variable (P, T_max, T_min, and T_mean) for the current period to observed climate data. This showed that climates simulated by realizations from the same climate model were more similar to each other than to realizations from other models. However, when projected into the future, these realizations followed different trajectories and the values of climate variables differed considerably within and among climate models. These had pronounced effects on the projected distributions of nine Australian butterfly species when modelled using the BIOCLIM component of DIVA-GIS. Our results show that internal climate model variability can lead to substantial differences in the extent to which the future distributions of species are projected to change. These can be greater than differences resulting from between-climate model variability. Further, different conclusions regarding the vulnerability of species to climate change can be reached due to internal model variability. Clearly, several climate models, each represented by multiple realizations, are required if we are to adequately capture the range of uncertainty associated with projecting species distributions in the future.     

Incorporating invasive weeds into a plant indicator method (LakeSPI) to assess lake ecological condition

The use of lake macrophytes for ecological quality assessments usually seeks to indicate the degree of anthropogenic impact, but few of these schemes implicitly consider impacts of alien weeds. LakeSPI (submerged plant indicators) uses indicators of habitat degradation for macrophytes but also incorporates the degree of impact from alien weeds. Application of LakeSPI to 195 New Zealand lakes provided a dataset to examine how component metrics responded over gradients of anthropogenic pressures, and consider whether weed invasion was merely a ‘passenger’ of habitat degradation, or represented an additional pressure. As expected, metrics measuring depth, and diversity of native vegetation negatively correlated with independent measures of lake eutrophy and were also relatively well explained (69–78% variation) by multiple regression with lake and catchment attributes that included proxies for anthropogenic pressure. In contrast, metrics for invasive impact were largely de-coupled from eutrophication, and poorly explained (31%) by the multiple regression. The response of native vegetation metrics to invasive impact measures varied, with the strongest detected interaction relating to native displacement by increased weed occupation of the vegetated zone. Interactions between invasion and lake trophic status were also discerned, with the extent of weed occupation having a more substantial outcome for the presence of charophyte meadows in low productivity lakes than in more productive lakes. These results suggest weed invasion should be considered as an additional source of anthropogenic pressure, and incorporated in macrophyte bioassessment schemes for a more complete differentiation of lake ecological condition.     

Suppression of methanogenesis by dissimilatory Fe(III)-reducing bacteria in tropical rain forest soils: implications for ecosystem methane flux

Tropical forests are an important source of atmospheric methane (CH₄), and recent work suggests that CH₄ fluxes from humid tropical environments are driven by variations in CH₄ production, rather than by bacterial CH₄ oxidation. Competition for acetate between methanogenic archaea and Fe(III)‐reducing bacteria is one of the principal controls on CH₄ flux in many Fe‐rich anoxic environments. Upland humid tropical forests are also abundant in Fe and are characterized by high organic matter inputs, steep soil oxygen (O₂) gradients, and fluctuating redox conditions, yielding concomitant methanogenesis and bacterial Fe(III) reduction. However, whether Fe(III)‐reducing bacteria coexist with methanogens or competitively suppress methanogenic acetate use in wet tropical soils is uncertain. To address this question, we conducted a process‐based laboratory experiment to determine if competition for acetate between methanogens and Fe(III)‐reducing bacteria influenced CH₄ production and C isotope composition in humid tropical forest soils. We collected soils from a poor to moderately drained upland rain forest and incubated them with combinations of ¹³C‐bicarbonate, ¹³C‐methyl labeled acetate (¹³CH₃COO^?), poorly crystalline Fe(III), or fluoroacetate. CH₄ production showed a greater proportional increase than Fe²⁺ production after competition for acetate was alleviated, suggesting that Fe(III)‐reducing bacteria were suppressing methanogenesis. Methanogenesis increased by approximately 67 times while Fe²⁺ production only doubled after the addition of ¹³CH₃COO^?. Large increases in both CH₄ and Fe²⁺ production also indicate that the two process were acetate limited, suggesting that acetate may be a key substrate for anoxic carbon (C) metabolism in humid tropical forest soils. C isotope analysis suggests that competition for acetate was not the only factor driving CH₄ production, as ¹³C partitioning did not vary significantly between ¹³CH₃COO^? and ¹³CH₃COO^?+Fe(III) treatments. This suggests that dissimilatory Fe(III)‐reduction suppressed both hydrogenotrophic and aceticlastic methanogenesis. These findings have implications for understanding the CH₄ biogeochemistry of highly weathered wet tropical soils, where CH₄ efflux is driven largely by CH₄ production.     

Effects of free-air CO2 enrichment (FACE) on CH4 emission from a rice paddy field

Methane (CH₄) is a particularly potent greenhouse gas with a radiative forcing 23 times that of CO₂ on a per mass basis. Flooded rice paddies are a major source of CH₄ emissions to the Earth's atmosphere. A free‐air CO₂ enrichment (FACE) experiment was conducted to evaluate changes in crop productivity and the crop ecosystem under enriched CO₂ conditions during three rice growth seasons from 1998 to 2000 in a rice paddy at Shizukuishi, Iwate, Japan. To understand the influence of elevated atmospheric CO₂ concentrations on CH₄ emission, we measured methane flux from FACE rice fields and rice fields with ambient levels of CO₂ during the 1999 and 2000 growing seasons. Methane production and oxidation potentials of soil samples collected when the rice was at the tillering and flowering stages in 2000 were measured in the laboratory by the anaerobic incubation and alternative propylene substrates methods, respectively. The average tiller number and root dry biomass were clearly larger in the plots with elevated CO₂ during all rice growth stages. No difference in methane oxidation potential between FACE and ambient treatments was found, but the methane production potential of soils during the flowering stage was significantly greater under FACE than under ambient conditions. When free‐air CO₂ was enriched to 550 ppmv, the CH₄ emissions from the rice paddy field increased significantly, by 38% in 1999 and 51% in 2000. The increased CH₄ emissions were attributed to accelerated CH₄ production potential as a result of more root exudates and root autolysis products and to increased plant‐mediated CH₄ emissions because of the larger rice tiller numbers under FACE conditions.     

Changing temperatures and prediction models for the liver fluke (Fasciola hepatica)

The principle of using mathematical modesl, based on temperature data, to predict the development times of the extra-mammalian stages of the liver fluke is described. The effect of temperature on survival of those stages are also modelled. The effect of temperature is also examined in relation to its effect on predation efficiency.     

Incorporating patterns of disperser behaviour into models of seed dispersal and its effects on estimated dispersal curves

The processes determining where seeds fall relative to their parent plant influence the spatial structure and dynamics of plant populations and communities. For animal dispersed species the factors influencing seed shadows are poorly understood. In this paper we test the hypothesis that the daily temporal distribution of disperser behaviours, for example, foraging and movement, influences dispersal outcomes, in particular the shape and scale of dispersal curves. To do this, we describe frugivory and the dispersal curves produced by the southern cassowary, Casuarius casuarius, the only large-bodied disperser in Australia’s rainforests. We found C. casuarius consumed fruits of 238 species and of all fleshy-fruit types. In feeding trials, seeds of 11 species were retained on average for 309 min (±256 SD). Sampling radio-telemetry data randomly, that is, assuming foraging occurs at random times during the day, gives an estimated average dispersal distance of 239 m (±207 SD) for seeds consumed by C. casuarius. Approximately 4% of seeds were dispersed further than 1,000 m. However, observation of wild birds indicated that foraging and movement occur more frequently early and late in the day. Seeds consumed early in the day were estimated to receive dispersal distances 1.4 times the ‘random’ average estimate, while afternoon consumed seeds received estimated mean dispersal distances of 0.46 times the ‘random’ estimate. Sampling movement data according to the daily distribution of C. casuarius foraging gives an estimated mean dispersal distance of 337 m (±194 SD). Most animals’ behaviour has a non-random temporal distribution. Consequently such effects should be common and need to be incorporated into seed shadow estimation. Our results point to dispersal curves being an emergent property of the plant–disperser interaction rather than being a property of a plant or species.     

Incorporating Uncertainty into a Life Cycle Assessment (LCA) Model of Short-Rotation Willow Biomass (Salix spp.) Crops

To estimate fossil fuel demand and greenhouse gas emissions associated with short-rotation willow (Salix spp.) crops in New York State, we constructed a life cycle assessment model capable of estimating point values and measures of variability for a number of key processes across eight management scenarios. The system used 445.0 to 1,052.4 MJ of fossil energy per oven-dry tonne (odt) of delivered willow biomass, resulting in a net energy balance of 18.3:1 to 43.4:1. The largest fraction of the energy demand across all scenarios was driven by the use of diesel fuels. The largest proportion of diesel fuel was associated with harvesting and delivery of willow chips seven times on 3-year rotations over the life of the crop. Similar patterns were found for greenhouse gas emissions across all scenarios, as fossil fuel use served as the biggest source of emissions in the system. Carbon sequestration in the belowground portion of the willow system provided a large carbon sink that more than compensated for carbon emissions across all scenarios, resulting in final greenhouse gas balances of ?138.4 to ?52.9 kg CO₂ eq. per odt biomass. The subsequent uncertainty analyses revealed that variability associated with data on willow yield, litterfall, and belowground biomass eliminated some of the differences between the tested scenarios. Even with the inclusion of uncertainty analysis, the willow system was still a carbon sequestration system after a single crop cycle (seven 3-year rotations) in all eight scenarios. A better understanding and quantification of factors that drive the variability in the biological portions of the system is necessary to produce more precise estimates of the emissions and energy performance of short-rotation woody crops.     

Insight into citric acid-induced chromium detoxification in rice (Oryza sativa. L)

Abstract

High content of chromium in plants hampers plants’ metabolism, disrupts plant growth and development. Therefore, improving plants’ tolerance to Cr toxicity is very essential. In our present study, we investigated the role of citric acid (CA) on chromium detoxification in terms of stress tolerance in rice. Application of CA under Cr stress restore the growth parameters, total protein content and membrane stability confirming that CA plays important role in Cr detoxification in rice. However, supplementation of CA under Cr stress caused no significant change in root Cr content but increased shoot Cr concentration (97?µg/g) compare with Cr stressed plant (24?µg/gm), suggesting that CA alleviates Cr toxicity by its chelating properties. Moreover, Fe content showed no significant changes due to CA supplementation under Cr stress, implying that Fe regulation is not involved with CA-mediated mitigation of Cr toxicity in rice. Furthermore, increased CAT, POD, and GR activity along with raised metabolites (glutathione and proline) indicates active participation in ROS scavenging and palliate the Cr toxicity in rice.     

New records of mango shield scale Milviscutulus mangiferae (Green) (Hemiptera: Coccidae) and Brevennia rehi (Lindinger) (Hemiptera: Pseudococcidae) in north Queensland

Abstract  The first Australian records of mango shield scale ( Milviscutulus mangiferae ) from north Queensland and additional records from parts of Papua New Guinea are presented. The majority of specimens were collected from mango leaves ( Mangifera indica ). A summary of its known distribution, other hosts, identification and damage levels is also presented. Also, the detection of rice mealybug ( Brevennia rehi ) in far north Queensland is reported for the first time. This pest is known to occur in the Northern Territory. The north Queensland detections are from native grasses. The records presented here, for both species, are regarded as new detections, rather than new incursions.     

Metagenomic analysis of microbial consortium from natural crude oil that seeps into the marine ecosystem offshore Southern California

Crude oils can be major contaminants of the marine ecosystem and microorganisms play a significant role in the degradation of its main constituents. To increase our understanding of the microbial hydrocarbon degradation process in the marine ecosystem, we collected crude oil from an active seep area located in the Santa Barbara Channel (SBC) and generated a total of about 52 Gb of raw metagenomic sequence data. The assembled data comprised ~500 Mb, representing ~1.1 million genes derived primarily from chemolithoautotrophic bacteria. Members of Oceanospirillales, a bacterial order belonging to the Deltaproteobacteria, recruited less than 2% of the assembled genes within the SBC metagenome. In contrast, the microbial community associated with the oil plume that developed in the aftermath of the Deepwater Horizon (DWH) blowout in 2010, was dominated by Oceanospirillales, which comprised more than 60% of the metagenomic data generated from the DWH oil plume. This suggests that Oceanospirillales might play a less significant role in the microbially mediated hydrocarbon conversion within the SBC seep oil compared to the DWH plume oil. We hypothesize that this difference results from the SBC oil seep being mostly anaerobic, while the DWH oil plume is aerobic. Within the Archaea, the phylum Euryarchaeota, recruited more than 95% of the assembled archaeal sequences from the SBC oil seep metagenome, with more than 50% of the sequences assigned to members of the orders Methanomicrobiales and Methanosarcinales. These orders contain organisms capable of anaerobic methanogenesis and methane oxidation (AOM) and we hypothesize that these orders – and their metabolic capabilities – may be fundamental to the ecology of the SBC oil seep.