气候变化和人类活动对孟印缅地区农田净初级生产力的影响

Under global change and climate variations, determining the impacts of climate change and human ac tivities on cropland net primary productivity (NPP) in Bangladesh, India and Myanmar (BIM) is of great significance for identifying yield-limiting factors, making adaptive agricultural management plans, and improving yields. Based on the GLOPEM-CEVSA model, through an integration of remote sensing data and LAI simulation, we investigated the impacts and spatiotemporal changes of water and human activities on BIM from 1982 to 2015. Three types of cropland NPPs were considered: actual NPP ( NPP _A ), NPP affected by temperature and water ( NPP _WT ), and NPP only affected by temperature ( NPP _T ). Our analysis revealed that the water factor plays a predominant role in de termining the NPP level in the BIM. Temperature variability was found to be conducive to NPP _T , exhibiting an in creasing trend of 10.66 g C m ^–2 yr ^–1 . However, this trend was partially offset by precipitation variability, resulting in a net increase of 0.96 g C m ^–2 yr ^–1 . In comparing temperature-driven NPP to temperature and water-driven NPP, water stress caused NPP _T to decrease by 65.46% compared to NPP _WT for the entire region. Cropland NPP in northwestern India and the central Deccan Plateau were significantly affected by water stress. Moreover, the in fluence of water on NPP in the BIM exhibited a substantial upward trend from 1982 to 2015, with Myanmar expe riencing the most significant increase. The gap between NPP _WT and NPP _A in BIM demonstrated a notable de creasing trend during the same period, underscoring the positive impact of human activities on NPP. Inferences drawn from our findings suggest that with the implementation of rational and efficient crop management practices, there is a 36.80% potential improvement in NPP _A compared to NPP _WT in the BIM region, with India and Myanmar showing potential increases of 39.20% and 38.29%, respectively. These insights provide guidance for practical measures aimed at water resource management to enhance cropland productivity in the BIM, and they present a methodology for quantifying the effects of climatic changes and human activities at a regional scale.

在全球变化和气候变化的背景下，量化气候变化和人类活动对孟加拉国、印度和缅甸（BIM）农田净初级生产力的 影响，对识别产量限制因素、制定合理的农业管理计划及提高农田产量具有重要意义。本研究基于 GLOPEM-CEVSA 模型，通过 整合遥感数据和 LAI 模拟及模拟三种情景下的农田 NPP：实际 NPP（ NPP _A ）、仅受温度和水分影响的 NPP（ NPP _WT ）和仅受温度 影响的 NPP（ NPP _T ），分析了 1982–2015 年水分和人类活动对 BIM 的影响及时空变化。研究发现，水分胁迫对孟印缅地区的农田 NPP 起主导作用。近 30 多年 BIM 地区的温度变化可使 NPP _T 以 10.66 g C m ^–2 yr ^–1 的速率增加，但结合实际的水分条件， NPP _WT 的增长趋势仅为 0.96 g C m ^–2 yr ^–1 。与仅受温度影响的 NPPT 相比，水分胁迫可使整个研究区的 NPP _WT 降低 65.46%，而且印度西 北部和德干高原中部的农田 NPP 受到水分胁迫的影响强烈。此外，1982–2015 年，BIM 中水分胁迫对 NPP 的影响呈现出显著的 增长趋势，其中缅甸的增长率最高。BIM 地区的 NPP _WT 和 NPP _A 之间的差距呈显著下降趋势，表明近 30 多年来人类活动对 NPP 有积极影响。因此，如果采取合理有效的作物管理，相较于 NPP _WT ，BIM 地区的 NPP _A 仍有 36.80%的提升潜力，其中印度和缅 甸分别有 39.20%和 38.29%的潜力。本研究结果可为 BIM 地区农业生产及农业水资源管理利用提高农田生产力提供参考，并为量 化气候变化和人类活动在区域范围内的影响提供方法参考。