One hundred years of climate change in Mexico

natural spatial areas that integrate physiographic, evolutionary and ecological features of biodi- versity [37]. However, the impacts of climate change at this level have yet to be performed [32]. To fill this gap, we developed average historical climate surfaces for Mexico, for three peri- ods covering most of the 20th and early 21th centuries: t1-1940 (1910–1949), t2-1970 (1950– 1979) and t3-2000 (1980–2009). We used these surfaces to describe historical climate change countrywide and in the 19 biogeographic provinces of Mexico. Materials and methods Climate data We analyzed monthly minimum and maximum temperature and accumulated rainfall data gathered from weather stations from the National Meteorological Office that were previously organized by Cuervo-Robayo [17], to derive monthly mean climate surfaces for three periods: t1-1940 (1910–1949), t2-1970 (1950–1979) and t3-2000 (1980–2009). We selected these periods based on previous global [38,39] and regional [19] climate change analysis and we also consid- ered the number of stations available for each period [40]. For t1-1940, we used a 40-year period, instead of 30 years as in the other time slices, due to the limited number of stations available. Because interpolation estimations are normally poor toward the edges of a region, the analysis should expand beyond the limits to the target region. Consequently, we included weather stations from southern portions of the United States, northern Belize and Guatemala. Data from the U.S. were gathered from the United States Historical Climatology Network

(USHC: http://cdiac.ornl.gov/epubs/ndp/ushcn/access.html), and data from Belize and Guate- mala were gathered through the FAOCLIM 2.0 software (http://www.fao.org/nr/climpag/pub/ en1102_en.asp) and the National Climatic Data Center (http://www.ncdc.noaa.gov data were organized and averaged into their corresponding periods using the “Structuration” extension from the Integrated Water Resources Management tool implemented in Idrisi Selva software, which is freely available at http://idrisi.uaemex.mx [41]. For the period t1-1940, weather sta- tions were located mainly in central Mexico, in the states of Guanajuato, Jalisco, Michoaca´n, and Me´xico. For the other two time periods, weather stations distributed throughout the coun- try, mainly at or near densely populated areas (Fig 1). We used ANUSPLIN software version 4.37 [42] to generate countrywide continuous cli- mate surfaces for the continental area (i.e., excluding oceans). This program uses the thin- plate smoothing splines interpolation technique, which integrates climatic and topographic data for making spatial climatic estimations, thus performing better than other interpolation methods [43,44]. Nonetheless, methods that incorporate expert knowledge, e.g. PRISM [45], sometimes perform better to capture features, such as rain shadow, which can be advantageous in complex geographical regions. Finally, we only used climate data from stations that operated for more than 10 years (S1) in at least one variable (temperature or precipitation). We used a

second-order spline with three independent variables (latitude, longitude and elevation) [17]. The value of the smoothing parameter was determined by minimizing a measure of the predic- tive error of the fitted surface given by the generalized cross-validation (GCV). For precipita- tion, we used a square-root transformation that reduces positively skewed values and ignores all negative values in precipitation data [42,46]. It also applies more smoothing to large precipi- tation values and less smoothing to small precipitation data values [47]. Given that we had more than 2000 stations for t2-1970 and t3-2000, we used SPLINB, as recommended by Hutch- inson [46], and used SELNOT to select a set of knots to reduce the complexity of the fitted spline. For t1-1940 we used SPLINA, which uses all available stations [46,47]. PLOS ONE Historical climate change in Mexico PLOS ONE | https://doi.org/10.1371/journal.pone.0209808 July 16, 2020 3 / 19