Models of natural pest control : Towards predictions across agricultural landscapes

Natural control of invertebrate crop pests has the potential to complement or replace conventional insecticide based practices, but its mainstream application is hampered by predictive unreliability across agroecosystems. Inconsistent responses of natural pest control to changes in landscape characteristics have been attributed to ecological complexity and system-specific conditions. Here, we review agroecological models and their potential to provide predictions of natural pest control across agricultural landscapes. Existing models have used a multitude of techniques to represent specific crop-pest-enemy systems at various spatiotemporal scales, but less wealthy regions of the world are underrepresented. A realistic representation of natural pest control across systems appears to be hindered by a practical trade-off between generality and realism. Nonetheless, observations of context-sensitive, trait-mediated responses of natural pest control to land-use gradients indicate the potential of ecological models that explicitly represent the underlying mechanisms. We conclude that modelling natural pest control across agroecosystems should exploit existing mechanistic techniques towards a framework of contextually bound generalizations. Observed similarities in causal relationships can inform the functional grouping of diverse agroecosystems worldwide and the development of the respective models based on general, but context-sensitive, ecological mechanisms. The combined use of qualitative and quantitative techniques should allow the flexible integration of empirical evidence and ecological theory for robust predictions of natural pest control across a wide range of agroecological contexts and levels of knowledge availability. We highlight challenges and promising directions towards developing such a general modelling framework.Peer reviewe

Multiple novel prostate cancer susceptibility signals identified by fine-mapping of known risk loci among Europeans

Genome-wide association studies (GWAS) have identified numerous common prostate cancer (PrCa) susceptibility loci. We have fine-mapped 64 GWAS regions known at the conclusion of the iCOGS study using large-scale genotyping and imputation in 25 723 PrCa cases and 26 274 controls of European ancestry. We detected evidence for multiple independent signals at 16 regions, 12 of which contained additional newly identified significant associations. A single signal comprising a spectrum of correlated variation was observed at 39 regions; 35 of which are now described by a novel more significantly associated lead SNP, while the originally reported variant remained as the lead SNP only in 4 regions. We also confirmed two association signals in Europeans that had been previously reported only in East-Asian GWAS. Based on statistical evidence and linkage disequilibrium (LD) structure, we have curated and narrowed down the list of the most likely candidate causal variants for each region. Functional annotation using data from ENCODE filtered for PrCa cell lines and eQTL analysis demonstrated significant enrichment for overlap with bio-features within this set. By incorporating the novel risk variants identified here alongside the refined data for existing association signals, we estimate that these loci now explain ∼38.9% of the familial relative risk of PrCa, an 8.9% improvement over the previously reported GWAS tag SNPs. This suggests that a significant fraction of the heritability of PrCa may have been hidden during the discovery phase of GWAS, in particular due to the presence of multiple independent signals within the same regio

Safety and efficacy of fluoxetine on functional outcome after acute stroke (AFFINITY): a randomised, double-blind, placebo-controlled trial

Background Trials of fluoxetine for recovery after stroke report conflicting results. The Assessment oF FluoxetINe In sTroke recoverY (AFFINITY) trial aimed to show if daily oral fluoxetine for 6 months after stroke improves functional outcome in an ethnically diverse population. Methods AFFINITY was a randomised, parallel-group, double-blind, placebo-controlled trial done in 43 hospital stroke units in Australia (n=29), New Zealand (four), and Vietnam (ten). Eligible patients were adults (aged ≥18 years) with a clinical diagnosis of acute stroke in the previous 2–15 days, brain imaging consistent with ischaemic or haemorrhagic stroke, and a persisting neurological deficit that produced a modified Rankin Scale (mRS) score of 1 or more. Patients were randomly assigned 1:1 via a web-based system using a minimisation algorithm to once daily, oral fluoxetine 20 mg capsules or matching placebo for 6 months. Patients, carers, investigators, and outcome assessors were masked to the treatment allocation. The primary outcome was functional status, measured by the mRS, at 6 months. The primary analysis was an ordinal logistic regression of the mRS at 6 months, adjusted for minimisation variables. Primary and safety analyses were done according to the patient's treatment allocation. The trial is registered with the Australian New Zealand Clinical Trials Registry, ACTRN12611000774921. Findings Between Jan 11, 2013, and June 30, 2019, 1280 patients were recruited in Australia (n=532), New Zealand (n=42), and Vietnam (n=706), of whom 642 were randomly assigned to fluoxetine and 638 were randomly assigned to placebo. Mean duration of trial treatment was 167 days (SD 48·1). At 6 months, mRS data were available in 624 (97%) patients in the fluoxetine group and 632 (99%) in the placebo group. The distribution of mRS categories was similar in the fluoxetine and placebo groups (adjusted common odds ratio 0·94, 95% CI 0·76–1·15; p=0·53). Compared with patients in the placebo group, patients in the fluoxetine group had more falls (20 [3%] vs seven [1%]; p=0·018), bone fractures (19 [3%] vs six [1%]; p=0·014), and epileptic seizures (ten [2%] vs two [<1%]; p=0·038) at 6 months. Interpretation Oral fluoxetine 20 mg daily for 6 months after acute stroke did not improve functional outcome and increased the risk of falls, bone fractures, and epileptic seizures. These results do not support the use of fluoxetine to improve functional outcome after stroke

High Tunnels for Local Food Systems: Subsidies, Equity, and Profitability

High tunnels are expanding opportunities to increase local food production in the midst of a globalized food system. They can overcome biophysical growing constraints by buffering temperatures to extend the growing season and shelter crops from extreme weather events. In 2010, the U.S. Department of Agriculture (USDA) Natural Resources Conservation Service (NRCS) began subsidizing the purchase of high tunnels. However, many questions remain about the factors influencing participation in the program and its impacts. Using mixed-methods research, this paper assesses the biophysical, market, and socio-demographic factors influencing NRCS high tunnel adoption in the U.S. and examines how food production in high tunnels affects farmers, consumers, and the local food movement. Results show that the number of NRCS high tunnels per county increased in relation to a mixture of biophysical (high latitude, proximity to the coast, small average farm size, and high percent of farmland in vegetable production), market (high direct-to-consumer sales, good access to grocery stores, and high median household income), and socio-demographic (high percentage of nonwhite population, metropolitan counties with more than 250,000 people, and adjacent urban counties with fewer than 20,000 people) factors. According to our survey of Virginia high tunnel growers, high tunnel produce is largely sold locally (within 50 miles or 80 km of production) and marketed direct-to-consumers in Virginia. Many growers in Virginia who would not have purchased a high tunnel without NRCS support plan to purchase additional high tunnels in the future even without a subsidy. High tunnels are an emerging part of the U.S. local food movement, but work remains to ensure that their benefits reach all sectors of U.S. society

Supplement 1. R source code for the spatial modeling package described in this paper, including main and subroutine files, with descriptions of code and instructions for use.

<h2>File List</h2><blockquote> <a href="Kernels.R">Kernels.R</a><br> <a href="SpatialParams.R">SpatialParams.R</a><br> <a href="SpatialSubs.R">SpatialSubs.R</a><br> <a href="Example.R">Example.R</a><br> </blockquote><h2>Description</h2><blockquote> <p>This supplement includes the subroutines and an example main file to be used for performing spatial simulations as described in O’Rourke and Jones (2011). It was written on a Macintosh computer running Mac OS X 10.6.7 (10J869), originally coded in R 1.8, and updated for publication to R version 2.13.0.</p> <blockquote> <p>i. Kernels.R: This is an R script containing descriptions of dispersal kernels used in our simulations. Currently included are a uniform dispersal kernel and a quereshi kernel (reference).</p> <p>ii. SpatialParams.R: This file contains basic parameters for the landscape including dimension, percentages of agricultural land, agricultural land devoted to corn production, and non-agricultural land; parameters for crop rotation and finally, the number of seasons (years) a given landscape will be simulated.</p> <p>iii. SpatialSubs.R: This file contains subroutines for creating the landscape, for insect dispersal and population growth.</p> <p>iv. Example.R: An example simulation. This file calls the appropriate subroutines and runs an example simulation for nyears seasons. Plots the results as a time series.</p> </blockquote> </blockquote

Appendix C. Histogram of δ13C values of all ECB analyzed.

Histogram of δ13C values of all ECB analyzed

Appendix A. Proportions of E- and Z-race ECB sampled from upstate New York that developed on C3 hosts according to δ13C analyses.

Proportions of E- and Z-race ECB sampled from upstate New York that developed on C3 hosts according to δ13C analyses

Appendix B. Total numbers of E- and Z-race moths trapped, the number of trap locations monitored, and the duration of trapping for each county mapped in Fig. 4.

Total numbers of E- and Z-race moths trapped, the number of trap locations monitored, and the duration of trapping for each county mapped in Fig. 4

Species traits elucidate crop pest response to landscape composition: a global analysis

Recent synthesis studies have shown inconsistent responses of crop pests to landscape composition, imposing a fundamental limit to our capacity to design sustainable crop protection strategies to reduce yield losses caused by insect pests. Using a global dataset composed of 5242 observations encompassing 48 agricultural pest species and 26 crop species, we tested the role of pest traits (exotic status, host breadth and habitat breadth) and environmental context (crop type, range in landscape gradient and climate) in modifying the pest response to increasing semi-natural habitats in the surrounding landscape. For natives, increasing semi-natural habitats decreased the abundance of pests that exploit only crop habitats or that are highly polyphagous. On the contrary, populations of exotic pests increased with an increasing cover of semi-natural habitats. These effects might be related to changes in host plants and other resources across the landscapes and/or to modified top-down control by natural enemies. The range of the landscape gradient explored and climate did not affect pests, while crop type modified the response of pests to landscape composition. Although species traits and environmental context helped in explaining some of the variability in pest response to landscape composition, the observed large interspecific differences suggest that a portfolio of strategies must be considered and implemented for the effective control of rapidly changing communities of crop pests in agroecosystems