The decoupling of cropland and livestock due to the industrialization of livestock production is a difficult problem for sustainable agricultural development in many global locations, including China. As population and urbanization increase, this decoupling is likely to become more serious. To date, the relationship between cropland and livestock has been mainly studied from a single perspective, and mostly at the regional and the local scales. Thus, the objective of our study is to systematically assess the coupling relationship between cropland and livestock from multiple aspects on a large scale. Here, we used a complex system covering cropland, livestock and environment subsystems to comprehensively analyze the spatio-temporal variation of the coupling coordination between cropland and livestock and its influencing factors in China over the past two decades. Elaborating on the data, we constructed a comprehensive system of evaluation indexes for cropland–livestock systems. We used a coupling coordination degree model to evaluate the coupling coordination relationship between cropland and livestock in 31 provinces of China during 2000–2020. The results show that the range of cropland–livestock and cropland–livestock–environment coupling coordination degree was 0.4–0.9. In most of the provinces, there was no risk of cropland and livestock decoupling; however, the coupling coordination degree needed to be increased. More attention should be paid to the coordinated development of cropland and livestock coupling in urbanized areas such as Beijing and Tianjin, where cropland and livestock decoupling was more likely to occur. Among the assessed 29 factors, 15 and 16 had an impact on the cropland–livestock and the cropland–livestock–environment coupling coordination degrees, respectively. Our study provides science-based evidence to support estimating the coupling relationship between cropland and livestock in the future.

Given that nitrogen (N) is a major limiting factor for global crop production, improving low-nitrogen (LN) tolerance in barley is essential for sustaining yields worldwide. Building on our laboratory’s previous quantitative trait locus (QTL) mapping, which identified three LN-specific QTL clusters on chromosomes 2H and 5H, this study investigated the potential of gene pyramiding to improve LN tolerance. We generated two recombinant inbred line populations (C79 and F79) containing these QTLs and evaluated them for thirty-six traits related to yield, agronomy, and N, phosphorus (P), and potassium (K) uptake and utilization. The results confirmed that LN stress significantly reduced most yield, agronomic, and NPK-related traits. Under LN conditions, grain yield and accumulations of N, P, and K in the C79 population increased with the number of QTL clusters harbored by the lines. More compellingly, in the F79 population under LN stress, lines containing all three QTL clusters exhibited superior performance for critical yield components such as grain yield, spike number, grain number, and nutrient efficiency indices. Furthermore, in both populations, lines with the full QTL complement demonstrated higher values for harvest index, grain number, and K harvest index under LN stress than under normal-N conditions. In conclusion, this study is the first to link LN-QTL pyramiding with P and K use efficiency and demonstrates that pyramiding breeding can produce high-yielding barley varieties with enhanced LN tolerance and nutrient absorption capacity.

Biochar-based organic fertilizer is increasingly used to improve soil quality, yet its effects on soil aggregation and organic carbon (SOC) fractions remain poorly understood. This study aimed to elucidate the effects of biochar-based organic fertilizer on SOC accumulation and soil aggregation and their underlying mechanisms. A microcosm experiment was conducted using a Cambisol under four treatments: no addition, organic fertilizer alone, biochar alone, and biochar-based organic fertilizer. We determined aggregate size distribution and stability, SOC and its fractions, as well as microbial community composition. Biochar-based organic fertilizer increased the proportion of macroaggregates, geometric mean diameter, and SOC content (from 0.9% to 1.9%, p < 0.05), along with increases in mineral-associated organic carbon (MAOC) and particulate organic carbon (POC, an increase of 8.1 g kg⁻¹, p < 0.05). The biochar component played a dominant role in promoting MAOC accumulation and aggregate stability, both of which were closely linked to shifts in bacterial community composition. In contrast, organic fertilizer primarily contributed to POC content associated with fungal communities. Overall, biochar-based organic fertilizer is effective for improving soil physical structure and SOC accumulation via biochar–organic fertilizer synergy. These findings have important implications for its use as a sustainable soil amendment for degraded arable soils.

Peri-urban transition zones experience intense conflicts among production, living, and ecological functions, yet the ecological effects of specific land-use transition pathways remain insufficiently quantified. Most studies of production–living–ecological space (PLES) use land-use transition matrices to quantify aggregate transitions among land-use classes, which limits the identification of coupling relationships and differences among specific pathways across ecological cost (EC), ecological value (EV), and network ecological efficiency (NEE). Using Wenjiang District, Chengdu, as a case study, this study integrates complex network analysis, a coupling coordination model, and CA–Markov scenario simulation to develop a pathway coupling framework. The framework quantifies the coupling of EC, EV, and NEE among eight PLES functional land-use classes from 2000 to 2025, and compares their potential ecological effects under three scenarios from 2030 to 2050. The conversion of agricultural production land to urban living land (APL→ULL) was the dominant pathway, with a net transition area of 28.26 km². The eco-environmental quality index declined from 0.228 to 0.200, a cumulative decrease of 12.3%, and the ecological contribution rate remained negative in every period. Coupling coordination varied markedly among pathways. APL→ULL showed severe imbalance ($D$ = 0.191), APL→CPL showed moderate relative coordination ($D$ = 0.741), and APL→FEL and related restoration pathways showed good relative coordination ($D$ = 0.870 to 0.968). Here, $D$ represents the relative coordination of direction-aligned and normalized indicators within the pathway sample rather than absolute ecological performance. Backcasting yielded a Kappa coefficient of 0.82. The future scenarios indicated that ecological protection could slow but not fully reverse the projected degradation trend. Based on ecological effects, relative coordination, and scenario responses, the major pathways were classified as priority-control, priority-incentive, or conditional-management pathways. By using individual land-use transition pathways as a common unit of analysis, the framework links network structure identification, joint assessment of EC, EV, and NEE, comparison of scenario responses, and management classification. It thereby extends PLES eco-environmental assessment from aggregate area change or single indicators to pathway-level diagnosis and decision support.