The environmental consequences of climate-driven agricultural frontiers

opportunities for economic development that, if done properly, may reduce poverty and food insecurity in some economically marginal parts of the world, such as northern Canada, where a lack of economic opportunities has created epidemic levels of food insecurity. With that said, it is important to recognize that food insecurity in remote communities is rarely a function of food production alone and is more often associated with a complex legacy of colonialism, edu- cation, and socio-cultural disconnects. There are serious negative environmental impacts associated with the unfettered develop- ment of climate-driven agricultural frontiers. Recognizing that climate-driven agricultural frontiers are a potential source of new greenhouse gas emissions and other environmental impacts including a loss of biodiversity and a loss of water quality for hundreds of millions of people highlights the need for national and international policy to guide sustainable develop- ment in the frontiers. The development of such policies should engage with Indigenous Com- munities and other local stakeholders to establish participatory processes that would ensure that economic development plans are led locally and that local communities are the primary beneficiaries of any land use change. Together, therefore, using participatory methodologies, local governance and frameworks such as the Sustainable Development Goals, it should be possible to help countries realize the potential benefits associated with a changing environment without causing major further environmental problems.

Supporting information S1 Table. List of GCMs used to drive future climate projections. (DOCX) S2 Table. Definition of bioclimatic variables used in maxent models. (DOCX) S3 Table. List of crops modeled and ecocrop parameters used. KTmp = Killing Temperature (˚C); Tn = Absolute Minimum Temp (˚C); TnOp = Minimum Optimal Temp (˚C); Tx = Absolute Maximum Temp (˚C); TxOp = Maximum Optimal Temp (˚C); Pn = Absolute Minimum Precip (mm); PnOp = Minimum Optimal Precip (mm); Px = Absolute Maximum Precip (mm); PxOp = Maximum Optimal Precip (mm); Gseas = Growing Season Duration (days). (DOCX) S4 Table. Gridded datasets used to derive occurrence points for each crop. (DOCX) S5 Table. Bioclimatic variables used to create the maxent model for each crop. (DOCX) S6 Table. Summary of model performance (AUC), logistic threshold used to create binary distributions (Threshold) and the four most important variables for each crop (Var 1–4). (DOCX) S7 Table. Critical maximum and minimum temperatures for each crop. Critical tempera- ture thresholds used are in bold. Critical temperature values were obtained from references [76–90]. (DOCX) S8 Table. Dice-Sorenson spatial congruence for ecocrop, maxent, and combined model with extreme temperature masks. Dice-Sorenson measures the spatial overlap with the The environmental consequences of climate-driven agricultural frontiers PLOS ONE | https://doi.org/10.1371/journal.pone.0228305 February 12, 2020 13 / 19