Spatial weed distribution models under climate change: a short review

Climate change is a concern worldwide that could trigger many changes with severe consequences. Since human demography is steadily increasing, agriculture has to be constantly investigated to aim at improving its efficiency. Weeds play a key role in this task, especially in the recent past and at present, when new introductions have been favoured by a rise in tourism and international trade. To obtain knowledge relating weeds and their behaviour to climate change, species distribution models (SDMs) have also increased recently. In this work, we have reviewed some articles published since 2017 on modelled weeds, aiming to give a response to, among other things, the species most studied, the scale and location of the studies, the algorithms used and validation parameters, global change scenarios, types of variables, and the sources from which the data were collected. Fifty-nine articles were selected to be reviewed, with maximum entropy (MaxEnt) and area under the curve (AUC) being the most popular software and validation processes. Environmental and topographic variables were considered above pedological and anthropogenic ones. Europe was the continent and China, the USA, and India the countries most studied. In this review, it was found that the number of published articles between developed and developing countries is unbalanced and comes out in favour of the former. The current knowledge on this topic can be considered to be good not enough, especially in developing countries with high population densities. The more knowledge we can obtain, the better our understanding is of how to deal with this issue, which is a worldwide preoccupation.

Automated summary

Climate change is a global concern with severe consequences, prompting the need for continuous investigation of agriculture to improve its efficiency. Weeds have played a crucial role in this regard, especially with the increase in tourism and international trade. Species distribution models (SDMs) have been used to study the relationship between weeds and climate change. A review of articles published since 2017 found that the most studied species, scale and location of studies, algorithms used, validation parameters, global change scenarios, variables, and data sources varied. The imbalance between developed and developing countries in terms of published articles highlights the need for more research, particularly in densely populated developing countries.