Wheat, rice, maize, and soybean provide two-thirds of human caloric intake. Assessing the impact of global temperature increase on production of these crops is therefore critical to maintaining global food supply, but different studies have yielded different results. Here, we investigated the impacts of temperature on yields of the four crops by compiling extensive published results from four analytical methods: global grid-based and local point-based models, statistical regressions, and field-warming experiments. Results from the different methods consistently showed negative temperature impacts on crop yield at the global scale, generally underpinned by similar impacts at country and site scales. Without CO₂ fertilization, effective adaptation, and genetic improvement, each degree-Celsius increase in global mean temperature would, on average, reduce global yields of wheat by 6.0%, rice by 3.2%, maize by 7.4%, and soybean by 3.1%. Results are highly heterogeneous across crops and geographical areas, with some positive impact estimates. Multimethod analyses improved the confidence in assessments of future climate impacts on global major crops and suggest crop- and region-specific adaptation strategies to ensure food security for an increasing world population.

Fractional vegetation cover (FVC) is an important biophysical parameter of terrestrial ecosystems. Variation of FVC is a major problem in research fields related to remote sensing applications. In this study, the global FVC from 1982 to 2011 was estimated by GIMMS NDVI data, USGS global land cover characteristics data and HWSD soil type data with a modified dimidiate pixel model, which considered vegetation and soil types and mixed pixels decomposition. The evaluation of the robustness and accuracy of the GIMMS FVC with MODIS FVC and Validation of Land European Remote sensing Instruments (VALERI) FVC show high reliability. Trends of the annual FVC_max and FVC_mean datasets in the last 30 years were reported by the Mann–Kendall method and Sen’s slope estimator. The results indicated that global FVC change was 0.20 and 0.60 in a year with obvious seasonal variability. All of the continents in the world experience a change in the annual FVC_max and FVC_mean, which represents biomass production, except for Oceania, which exhibited a significant increase based on a significance level of p = 0.001 with the Student’s t-test. Global annual maximum and mean FVC growth rates are 0.14%/y and 0.12%/y, respectively. The trends of the annual FVC_max and FVC_mean based on pixels also illustrated that the global vegetation had turned green in the last 30 years. A significant trend on the p = 0.05 level was found for 15.36% of the GIMMS FVC_max pixels on a global scale (excluding permanent snow and ice), in which 1.8% exhibited negative trends and 13.56% exhibited positive trends. The GIMMS FVC_mean similarly produced a total of 16.64% significant pixels with 2.28% with a negative trend and 14.36% with a positive trend. The North Frigid Zone represented the highest annual FVC_max significant increase (p = 0.05) of 25.17%, which may be caused mainly by global warming, Arctic sea-ice loss and an advance in growing seasons. Better FVC predictions at large regional scales, with high temporal resolution (month) and long time series, would advance our ability to understand the characteristics of the global FVC changes in the last 30 years and predict the response of vegetation to global climate change.

Warming is projected to increase the productivity of northern ecosystems. However, knowledge on whether the northward displacement of vegetation productivity isolines matches that of temperature isolines is still limited. Here we compared changes in the spatial patterns of vegetation productivity and temperature using the velocity of change concept, which expresses these two variables in the same unit of displacement per time. We show that across northern regions (>50° N), the average velocity of change in growing-season normalized difference vegetation index (NDVI_GS, an indicator of vegetation productivity; 2.8 ± 1.1 km yr⁻¹) is lower than that of growing-season mean temperature (T_GS; 5.4 ± 1.0 km yr⁻¹). In fact, the NDVI_GS velocity was less than half of the T_GS velocity in more than half of the study area, indicating that the northward movement of productivity isolines is much slower than that of temperature isolines across the majority of northern regions (about 80% of the area showed faster changes in temperature than productivity isolines). We tentatively attribute this mismatch between the velocities of productivity and temperature to the effects of limited resource availability and vegetation acclimation mechanisms. Analyses of ecosystem model simulations further suggested that limited nitrogen availability is a crucial obstacle for vegetation to track the warming trend.