Profiling ellagic acid content: The importance of form and ascorbic acid levels

As the importance of plant-based antioxidants to human health becomes clearer there is a rapidly expanding search for rich sources of these compounds. Much attention is currently focussed on the antioxidant potential of ellagic acid (EA). Making assessment difficult is that EA occurs in different forms: free EA, EA glycosides and polymeric ellagitannins. The overall structure of these forms has a pronounced effect on their antioxidant efficiency and is responsible for widely differing reactivity, solubility and hence bioavailability properties. Often associated with EA is vitamin C which also contributes to the plant foods total antioxidant activity. Previous studies have suggested that ascorbic acid may have protective effects on the polyphenol content of plants. With a view to gaining evidence that the bioactive forms of vitamin C influence EA content, several fruits with a range of EA and vitamin C contents were examined. To facilitate a more detailed assessment of the selected fruits antioxidant potential the relative proportions of EA forms were also determined. In strawberries and boysenberries EA content was predominantly in the polymeric form (21% and 12% free EA plus EA glycoside vs total EA levels for strawberry and boysenberry respectively), while in Kakadu plum it was mainly in the free form (70% of total EA). An increasing percentage of dehydroascorbic acid (9 to 14% of total vitamin C) indicating enhanced transformation of ascorbic acid to its oxidative degradation product together with stable free EA levels (≈ 950 mg/100 g DW) over the 4 month frozen storage period for the Kakadu plum samples are consistent with a possible protective effect of EA by ascorbic acid.

Immediate and residual effects of heat stress and restricted intake on milk protein and casein composition and energy metabolism

The effects of heat stress on dairy production can be separated into 2 distinct causes: those effects that are mediated by the reduced voluntary feed intake associated with heat stress, and the direct physiological and metabolic effects of heat stress. To distinguish between these, and identify their effect on milk protein and casein concentration, mid-lactation Holstein-Friesian cows (n = 24) were housed in temperature-controlled chambers and either subjected to heat stress HS; temperature-humidity index (THI) ~78 or kept in a THI < 70 environment and pair-fed with heat-stressed cows (TN-R) for 7 d. A control group of cows was kept in a THI < 70 environment with ad libitum feeding (TN-AL). A subsequent recovery period (7 d), with THI < 70 and ad libitum feeding followed. Intake accounted for only part of the effects of heat stress. Heat stress reduced the milk protein concentration, casein number, and casein concentration and increased the urea concentration in milk beyond the effects of restriction of intake. Under HS, the proportion in total casein of αS1-casein increased and the proportion of αS2-casein decreased. Because no effect of HS on milk fat or lactose concentration was found, these effects appeared to be the result of specific downregulation of mammary protein synthesis, and not a general reduction in mammary activity. No residual effects were found of HS or TN-R on milk production or composition after THI < 70 and ad libitum intake were restored. Heat-stressed cows had elevated blood concentrations of urea and Ca, compared with TN-R and TN-AL. Cows in TN-R had higher serum nonesterified fatty acid concentrations than cows in HS. It was proposed that HS and TN-R cows may mobilize different tissues as endogenous sources of energy.

Mechanisms of the impact of a weed (grader grass, Themeda quadrivalvis) on reptile assemblage structure in a tropical savannah

Invasive grasses are among the worst threats to native biodiversity, but the mechanisms causing negative effects are poorly understood. To investigate the impact of an invasive grass on reptiles, we compared the reptile assemblages that used native kangaroo grass (Themeda triandra), and black spear grass (Heteropogon contortus), to those using habitats invaded by grader grass (Themeda quadrivalvis). There were significantly more reptile species, in greater abundances, in native kangaroo and black spear grass than in invasive grader grass. To understand the sources of negative responses of reptile assemblages to the weed, we compared habitat characteristics, temperatures within grass clumps, food availability and predator abundance among these three grass habitats. Environmental temperatures in grass, invertebrate food availability, and avian predator abundances did not differ among the habitats, and there were fewer reptiles that fed on other reptiles in the invaded than in the native grass sites. Thus, native grass sites did not provide better available thermal environments within the grass, food, or opportunities for predator avoidance. We suggest that habitat structure was the critical factor driving weed avoidance by reptiles in this system, and recommend that the maintenance of heterogeneous habitat structure, including clumping native grasses, with interspersed bare ground, and leaf litter are critical to reptile biodiversity.

Projecting future expansion of invasive species: Comparing and improving methodologies for species distribution modeling

Modeling the distributions of species, especially of invasive species in non-native ranges, involves multiple challenges. Here, we developed some novel approaches to species distribution modeling aimed at reducing the influences of such challenges and improving the realism of projections. We estimated species-environment relationships with four modeling methods run with multiple scenarios of (1) sources of occurrences and geographically isolated background ranges for absences, (2) approaches to drawing background (absence) points, and (3) alternate sets of predictor variables. We further tested various quantitative metrics of model evaluation against biological insight. Model projections were very sensitive to the choice of training dataset. Model accuracy was much improved by using a global dataset for model training, rather than restricting data input to the species’ native range. AUC score was a poor metric for model evaluation and, if used alone, was not a useful criterion for assessing model performance. Projections away from the sampled space (i.e. into areas of potential future invasion) were very different depending on the modeling methods used, raising questions about the reliability of ensemble projections. Generalized linear models gave very unrealistic projections far away from the training region. Models that efficiently fit the dominant pattern, but exclude highly local patterns in the dataset and capture interactions as they appear in data (e.g. boosted regression trees), improved generalization of the models. Biological knowledge of the species and its distribution was important in refining choices about the best set of projections. A post-hoc test conducted on a new Partenium dataset from Nepal validated excellent predictive performance of our “best” model. We showed that vast stretches of currently uninvaded geographic areas on multiple continents harbor highly suitable habitats for Parthenium hysterophorus L. (Asteraceae; parthenium). However, discrepancies between model predictions and parthenium invasion in Australia indicate successful management for this globally significant weed. This article is protected by copyright. All rights reserved.

Water addition, evaporation and water holding capacity of poultry litter

Litter moisture content has been related to ammonia, dust and odour emissions as well as bird health and welfare. Improved understanding of the water holding properties of poultry litter as well as water additions to litter and evaporation from litter will contribute to improved litter moisture management during the meat chicken grow-out. The purpose of this paper is to demonstrate how management and environmental conditions over the course of a grow-out affect the volume of water A) applied to litter, B) able to be stored in litter, and C) evaporated from litter on a daily basis. The same unit of measurement has been used to enable direct comparison—litres of water per square metre of poultry shed floor area, L/m2, assuming a litter depth of 5 cm. An equation was developed to estimate the amount of water added to litter from bird excretion and drinking spillage, which are sources of regular water application to the litter. Using this equation showed that water applied to litter from these sources changes over the course of a grow-out, and can be as much as 3.2 L/m2/day. Over a 56 day grow-out, the total quantity of water added to the litter was estimated to be 104 L/m2. Litter porosity, water holding capacity and water evaporation rates from litter were measured experimentally. Litter porosity decreased and water holding capacity increased over the course of a grow-out due to manure addition. Water evaporation rates at 25 °C and 50% relative humidity ranged from 0.5 to 10 L/m2/day. Evaporation rates increased with litter moisture content and air speed. Maintaining dry litter at the peak of a grow-out is likely to be challenging because evaporation rates from dry litter may be insufficient to remove the quantity of water added to the litter on a daily basis.

Projecting future expansion of invasive species: Comparing and improving methodologies for species distribution modeling

Modeling the distributions of species, especially of invasive species in non-native ranges, involves multiple challenges. Here, we developed some novel approaches to species distribution modeling aimed at reducing the influences of such challenges and improving the realism of projections. We estimated species-environment relationships with four modeling methods run with multiple scenarios of (1) sources of occurrences and geographically isolated background ranges for absences, (2) approaches to drawing background (absence) points, and (3) alternate sets of predictor variables. We further tested various quantitative metrics of model evaluation against biological insight. Model projections were very sensitive to the choice of training dataset. Model accuracy was much improved by using a global dataset for model training, rather than restricting data input to the species’ native range. AUC score was a poor metric for model evaluation and, if used alone, was not a useful criterion for assessing model performance. Projections away from the sampled space (i.e. into areas of potential future invasion) were very different depending on the modeling methods used, raising questions about the reliability of ensemble projections. Generalized linear models gave very unrealistic projections far away from the training region. Models that efficiently fit the dominant pattern, but exclude highly local patterns in the dataset and capture interactions as they appear in data (e.g. boosted regression trees), improved generalization of the models. Biological knowledge of the species and its distribution was important in refining choices about the best set of projections. A post-hoc test conducted on a new Partenium dataset from Nepal validated excellent predictive performance of our “best” model. We showed that vast stretches of currently uninvaded geographic areas on multiple continents harbor highly suitable habitats for Parthenium hysterophorus L. (Asteraceae; parthenium). However, discrepancies between model predictions and parthenium invasion in Australia indicate successful management for this globally significant weed. This article is protected by copyright. All rights reserved.

Mechanisms of the impact of a weed (grader grass, Themeda quadrivalvis) on reptile assemblage structure in a tropical savannah

Invasive grasses are among the worst threats to native biodiversity, but the mechanisms causing negative effects are poorly understood. To investigate the impact of an invasive grass on reptiles, we compared the reptile assemblages that used native kangaroo grass (Themeda triandra), and black spear grass (Heteropogon contortus), to those using habitats invaded by grader grass (Themeda quadrivalvis). There were significantly more reptile species, in greater abundances, in native kangaroo and black spear grass than in invasive grader grass. To understand the sources of negative responses of reptile assemblages to the weed, we compared habitat characteristics, temperatures within grass clumps, food availability and predator abundance among these three grass habitats. Environmental temperatures in grass, invertebrate food availability, and avian predator abundances did not differ among the habitats, and there were fewer reptiles that fed on other reptiles in the invaded than in the native grass sites. Thus, native grass sites did not provide better available thermal environments within the grass, food, or opportunities for predator avoidance. We suggest that habitat structure was the critical factor driving weed avoidance by reptiles in this system, and recommend that the maintenance of heterogeneous habitat structure, including clumping native grasses, with interspersed bare ground, and leaf litter are critical to reptile biodiversity.

Statistical methods for analysis of multi-harvest data from perennial pasture variety selection trials

Variety selection in perennial pasture crops involves identifying best varieties from data collected from multiple harvest times in field trials. For accurate selection, the statistical methods for analysing such data need to account for the spatial and temporal correlation typically present. This paper provides an approach for analysing multi-harvest data from variety selection trials in which there may be a large number of harvest times. Methods are presented for modelling the variety by harvest effects while accounting for the spatial and temporal correlation between observations. These methods provide an improvement in model fit compared to separate analyses for each harvest, and provide insight into variety by harvest interactions. The approach is illustrated using two traits from a lucerne variety selection trial. The proposed method provides variety predictions allowing for the natural sources of variation and correlation in multi-harvest data.