Trichoderma harzianum produces nonanoic acid, an inhibitor of spore germination and mycelial growth of two cacao pathogens

An isolate of Trichoderma harzianum Rifai from an infected cacao pod produces and secretes nonanoic (pelargonic) acid into a liquid culture medium. Nonanoic acid (NA) was very inhibitory to spore germination and mycelial growth of two cacao pathogens, Crinipellis perniciosa Stahel and Moniliophthora roreri Cif. H.C. Evans. It was highly active causing 75% inhibition of spore germination in an in vitro assay at a rate as low as 0.09 μM for M. roreri and 0.92 μM for C. perniciosa. Mycelial growth was comparatively less sensitive to inhibition, but still there was a 75% reduction in growth with 0.62 μM in M. roreri and 151 μM NA in C. perniciosa. In contrast, NA did not affect Trichoderma mycelial growth or spore germination at concentrations that were inhibitory to the pathogens. 6-pentyl-α-pyrone was also produced and secreted into the medium by T. harzianum, however; it was not antagonistic to the cacao pathogens. Although a number of metabolites produced by Trichoderma spp. have been identified in the past, this is the first report of NA production and secretion by any Trichoderma. The results suggest that NA may play a role in the successful use of some Trichoderma spp. isolates in the biocontrol of fungal diseases of plants.     

Effects of sub-minimum inhibitory concentration antibiotic levels and temperature on growth kinetics and outer membrane protein expression in Mannheimia haemolytica and Haemophilus somnus

The objective of this study was to determine the effects of sub-minimum inhibitory concentrations (sub-MICs) of 2 veterinary antibiotic preparations, chlortetracycline (CTC) and chlortetracycline-sulfamethazine (CTC + SMZ), on growth kinetics and outer membrane protein expression in Mannheimia haemolytica and Haemophilus somnus at normal and febrile body temperatures. Sub-minimum inhibitory concentrations of both antibiotics reduced the growth rates of M. haemolytica and H. somnus. Growth of both species was not inhibited when grown at 41 degrees C compared to 37 degrees C. There was no detectable consistent effect of antibiotic or temperature on outer membrane protein expression for either species. Our study indicates that sub-MIC levels of CTC and CTC + SMZ markedly impair growth of clinical M. haemolytica and H. somnus isolates, potentially allowing more effective host clearance during infection.     

Variation in virulence of Greek isolates ofPhytophthora citrophthora as measured by their ability to cause crown rot on three peach rootstocks

The virulence ofPhytophthora citrophthora isolated from various host-plants on three peach rootstocks (GF677, PR204, KID I) was examined. There was no significant difference among the rootstocks with respect to their susceptibility to testedP. citrophthora isolates. The most virulent isolate originated from sycamore (Acer pseudoplatanus); isolates from pistachio trees (Pistacia vera) also showed high virulence but were significantly less virulent than the sycamore isolate. Isolates originating from plum (Prunus domestica), almond (Prunus amygdalus) and lemon (Citrus limon) trees were moderately virulent on peach rootstocks; those from cyclamen (Cyclamen persicum) showed the lowest virulence of those tested. There was thus great variation in virulence among the testedP. citrophthora isolates. It is possible that the isolates ofP. citrophthora from sycamore, pistachio, plum, almond and lemon trees are a threat to peach trees, whereas the low virulence of the isolates from cyclamen hosts suggests that these pathogens are not a serious threat to peach trees. http://www.phytoparasitica.org posting Jan. 3, 2002.     

Landscape patterns as habitat predictors: building and testing models for cavity-nesting birds in the Uinta Mountains of Utah,USA

The ability to predict species occurrences quickly is often crucial for managers and conservation biologists with limited time and funds. We used measured associations with landscape patterns to build accurate predictive habitat models that were quickly and easily applied (i.e., required no additional data collection in the field to make predictions). We used classification trees (a nonparametric alternative to discriminant function analysis, logistic regression, and other generalized linear models) to model nesting habitat of red-naped sapsuckers (Sphyrapicus nuchalis), northern flickers (Colaptes auratus),tree swallows (Tachycineta bicolor), and mountain chickadees (Parus gambeli) in the Uinta Mountains of northeastern Utah, USA. We then tested the predictive capability of the models with independent data collected in the field the following year. The models built for the northern flicker, red-naped sapsucker, and tree swallow were relatively accurate (84%, 80%, and 75% nests correctly classified,respectively)compared to the models for the mountain chickadee (50% nests correctly classified). All four models were more selective than a null model that predicted habitat based solely on a gross association with aspen forests. We conclude that associations with landscape patterns can be used to build relatively accurate, easy to use, predictive models for some species. Our results stress, however, that both selecting the proper scale at which to assess landscape associations and empirically testing the models derived from those associations are crucial for building useful predictive models. This revised version was published online in July 2006 with corrections to the Cover Date.     

Predicting effective doses for the joint action of two fungicide applications

A function was derived to predict fungicide efficacy when more than one application of a single active ingredient is made to a crop, given parameters describing the dose–response curves of the component single-spray applications. In the function, a second application is considered to act on that proportion of the total pathogen population which was uncontrollable at the time of the first application (represented by the lower asymptote of the dose–response curve for the first treatment), plus any additional part of the population which survived the first application as a result of a finite dose being applied. Data to estimate the single-spray dose–response curve parameters and validate predictions of two-spray programme efficacy were obtained from separate subsets of treatments in four field experiments. A systemic fungicide spray was applied to wheat at a range of doses, at one or both of two times (t₁ and t₂), in all dose combinations. Observed values of the area under the disease progress curve (AUDPC) for septoria leaf blotch (Mycosphaerella graminicola) were used to construct response surfaces of dose at t₁ by dose at t₂ for each culm leaf layer. Parameters were estimated from single-spray and zero-dose treatment data only. The model predicted a high proportion (R² = 71–95%) of the variation in efficacy of the two-spray programmes. AUDPC isobols showed that the dose required at t₂ was inversely related to the dose at t₁, but the slope of the relationship varied with the relative timings of t₁ and t₂ in relation to culm leaf emergence. Isobols were curved, so the effective dose – the total dose required to achieve a given level of disease suppression – was lower when administered as two applications.     

Quantifying patch distribution at multiple spatial scales: Applications to wildlife-habitat models

Multiscale analyses are widely employed for wildlife-habitat studies. In most cases, however, each scale is considered discrete and little emphasis is placed on incorporating or measuring the responses of wildlife to resources across multiple scales. We modeled the responses of three Arctic wildlife species to vegetative resources distributed at two spatial scales: patches and collections of patches aggregated across a regional area. We defined a patch as a single or homogeneous collection of pixels representing 1 of 10 unique vegetation types. We employed a spatial pattern technique, three-term local quadrat variance, to quantify the distribution of patches at a larger regional scale. We used the distance at which the variance for each of 10 vegetation types peaked to define a moving window for calculating the density of patches. When measures of vegetation patch and density were applied to resource selection functions, the most parsimonious models for wolves and grizzly bears included covariates recorded at both scales. Seasonal resource selection by caribou was best described using a model consisting of only regional scale covariates. Our results suggest that for some species and environments simple patch-scale models may not capture the full range of spatial variation in resources to which wildlife may respond. For mobile animals that range across heterogeneous areas we recommend selection models that integrate resources occurring at a number of spatial scales. Patch density is a simple technique for representing such higher-order spatial patterns.