Diversity and conservation priorities of crop wild relatives in Mexico

Abstract

Crop wild relatives (CWR) are valuable resources for crop breeding due to their close genetic relationship to the cultivated plants and their wide genetic variation, allowing the introgression of desirable traits into the crops, such as resistance to plant pests and diseases or adaptability to climate change. Mexico is a centre of agrobiodiversity, including CWR, but climate change, and other factors, are contributing to the loss of important Mexican CWR genetic diversity. The in situ and ex situ conservation status of Mexican priority CWR were assessed through a gap analysis as part of a national CWR conservation strategy for Mexico, to ensure the long-term preservation and improve the availability of these genetic resources. A set of 310 priority CWR taxa, previously identified as part of the national CWR inventory for Mexico, were analysed. Species distribution modelling and ecogeographic diversity analyses were used to detect gaps in in situ and ex situ conservation at taxon and ecogeographic levels. Priority target sites were identified throughout the country for complementary in situ and ex situ conservation of these taxa. The results obtained allow us to make recommendations for immediate conservation actions, thus helping to mitigate the threats to Mexican agrobiodiversity and enhance both national and global food security.

In situ and ex situ conservation gap analyses of crop wild relatives from Malawi

“…To achieve the above aims, methods adapted from Magos Brehm et al (2017a) and widely used at national and global level CWR conservation were applied (e.g. Hunter and Heywood 2011;Fielder 2015;Castañeda-Á lvarez et al 2016;Phillips et al 2016;Taylor et al 2017;Contreras-Toledo 2018).…”

“…Observed taxa distribution and sampling bias were mapped in DIVA-GIS 7.5.0 (Hijmans et al 2012) for 1621 records with TOTALQUAL [ 50% for a grid cell size of approximately 10 9 10 km. The potential taxa distribution and richness were obtained using the Maximum Entropy (MaxEnt) algorithm (Phillips et al 2006) and circular buffer (CA 50 ) in ArcMap 10.4.1 (ESRI 2015; Hijmans and Spooner 2001;Contreras Toledo et al 2019).…”

“…Taxa with C 50 occurrence records used 10 replications and 5 replications for taxa with C 10 records. Models that had; (1) average area under the Test ROC Curve [(ATAUC) [ 0.7]; (2) standard deviation of ATAUC (STAUC) below 0.15; (3) proportion of potential distribution area with standard deviation above 0.15 (ASD15) is below 10% were considered stable and used for estimating potential taxa distribution (Ramírez-Villegas et al 2010;Liu and Matt 2016;Contreras Toledo et al 2019). For the taxa that did not pass the MaxEnt models validation criteria above and for taxa with \ 10 occurrence records, a circular buffer method was applied adapting a 19 km buffer diameter for Malawi based on country size.…”

“…For studies targeting larger areas, a 50 km circular buffer (CA 50 ) was considered (e.g. Hijmans and Spooner 2001;Contreras Toledo et al 2019).…”

“…Many crops cultivated in the Southern African Development Community (SADC) region and of global importance such as cotton, wheat, maize, coffee and rice have benefited from adaptive traits originating from CWR (Brar 2005;Edmé et al 2005;Hajjar and Hodgkin 2007;Vincent et al2013;Allen et al 2017;Allen et al 2019). However, their conservation has been grossly passive with very low representation in many gene banks (Castañeda-Á lvarez et al 2016;Phillips et al 2016;Contreras-Toledo et al 2019).…”