Widening global variability in grassland biomass since the 1980s

Frequent failure of nutrients to increase plant biomass supports the need for precision fertilization in agriculture

Implementing precision fertilization to maximize crop yield while minimizing economic and environmental impacts has become critical for agriculture. Variability in biomass response to fertilization within fields, among regions, and over time creates simultaneous risks of under-yielding and overfertilization. We quantify factors determining fertilization responsiveness (i.e., biomass increases with fertilization) up to 15 years in 61 unfertilized rangelands on six continents. We demonstrate widespread multi-year variability in responsiveness, with fertilization increasing average yield by 43% but failing to improve biomass 26% of the time. All sites were responsive at least once, but only four of 61 responded in all plots and years. Modelled management scenarios highlighted that fertilizer cessation is likely to generate sizable economic savings but always reduces yield because of the difficulty in predicting when and where biomass will be unresponsive. This work reveals substantial scale-dependent variability in fertilization responsiveness globally, while clarifying the prospects and pitfalls of managing more spatially and temporally precise nutrient application.

Interactions among nutrients govern the global grassland biomass-precipitation relationship

Ecosystems are experiencing changing global patterns of mean annual precipitation (MAP) and enrichment with multiple nutrients that potentially colimit plant biomass production. In grasslands, mean aboveground plant biomass is closely related to MAP, but how this relationship changes after enrichment with multiple nutrients remains unclear. We hypothesized the global biomass-MAP relationship becomes steeper with an increasing number of added nutrients, with increases in steepness corresponding to the form of interaction among added nutrients and with increased mediation by changes in plant community diversity. We measured aboveground plant biomass production and species diversity in 71 grasslands on six continents representing the global span of grassland MAP, diversity, management, and soils. We fertilized all sites with nitrogen, phosphorus, and potassium with micronutrients in all combinations to identify which nutrients limited biomass at each site. As hypothesized, fertilizing with one, two, or three nutrients progressively steepened the global biomass-MAP relationship. The magnitude of the increase in steepness corresponded to whether sites were not limited by nitrogen or phosphorus, were limited by either one, or were colimited by both in additive, or synergistic forms. Unexpectedly, we found only weak evidence for mediation of biomass-MAP relationships by plant community diversity because relationships of species richness, evenness, and beta diversity to MAP and to biomass were weak or opposing. Site-level properties including baseline biomass production, soils, and management explained little variation in biomass-MAP relationships. These findings reveal multiple nutrient colimitation as a defining feature of the global grassland biomass-MAP relationship.

The dataset of main grain land changes in China over 1985-2020

Continuous, Accurate, and detailed information on main grain land (MGL) areas is crucial for provisioning food security and making policies affecting sustainable agricultural production. It still lacks a long-term MGL distribution dataset with fine spatial resolution. This study aimed to produce a long-term, high-resolution MGL distribution map for China. Here, we developed the change map of MGL with resolution 30 m in China for the period 1985-2020 using the Landsat image-based random forest algorithm on the GEE platform. Finally, the planting intensity, gain time and loss time of MGL was calculated. Results indicate that our mapping results are highly consistent with the annual planting area of various grain crops according to national statistics. A validation based on 3113 field survey samples with a 30-m resolution showed that the overall accuracy of MGL were 93.57%. The full MGL dataset is freely available at https://doi.org/10.6084/m9.figshare.26212643.v2 .