Trade-offs constrain the success of glyphosate-free farming.

Glyphosate, the most widely used herbicide, is linked with environmental harm and there is a drive to replace it in agricultural systems. We model the impacts of discontinuing glyphosate use and replacing it with cultural control methods. We simulate winter wheat arable systems reliant on glyphosate and typical in northwest Europe.

The utility of the 'Arable Weeds and Management in Europe' database: Challenges and opportunities of combining weed survey data at a European scale.

Over the last 30 years, many studies have surveyed weed vegetation on arable land. The 'Arable Weeds and Management in Europe' (AWME) database is a collection of 36 of these surveys and the associated management data. Here, we review the challenges associated with combining disparate datasets and explore some of the opportunities for future research that present themselves thanks to the AWME database.

Modelling the factors affecting the spatiotemporal distribution of cabbage stem flea beetle (Psylliodes chrysocephala) larvae in winter oilseed rape (Brassica napus) in the UK.

Background: Cabbage stem flea beetle (CSFB; Psylliodes chrysocephala L.) management in oilseed rape (Brassica napus L.) has become an urgent issue in the absence of permitted and effective insecticides.

Estimation of bed net coverage indicators in Tanzania using mobile phone surveys: a comparison of sampling approaches.

Background: Threats to maintaining high population access with effective bed nets persist due to errors in quantification, bed net wear and tear, and inefficiencies in distribution activities. Monitoring bed net coverage is therefore critical, but usually occurs every 2-3 years through expensive, large-scale household surveys. Mobile phone-based survey methodologies are emerging as an alternative to household surveys and can provide rapid estimates of coverage, however, little research on varied sampling approaches has been conducted in sub-Saharan Africa.

Using functional traits to model annual plant community dynamics.

Predicting the response of biological communities to changes in the environment or management is a fundamental pursuit of community ecology. Meeting this challenge requires the integration of multiple processes: habitat filtering, niche differentiation, biotic interactions, competitive exclusion, and stochastic demographic events. Most approaches to this long-standing problem focus either on the role of the environment, using trait-based filtering approaches, or on quantifying biotic interactions with process-based community dynamics models.