Data from: Distribution, drivers, and restoration priorities of plant invasions in India

Biological invasions threaten biodiversity and human wellbeing, with developing tropical countries being more vulnerable. Despite the urgency to reduce impacts of invasions, management interventions are constrained by unavailability of timely information on invasive species occurrence, potential drivers, and restoration priorities. Generating this information at biogeographic scales can be costly, unless integrated with multi-objective biodiversity monitoring. Invasive plant monitoring is integrated with India’s national-scale tiger population assessment, wherein natural areas are sampled at 25 km2 scale to inventory plants. In 2018, a total of 158,979 plots were sampled covering ~358,550 km2. We used 206,393 locations of high concern invasive plants to model their distribution using socio-ecological covariates and identify potential drivers of invasions. Considering the invasion magnitude and financial constraints in management, we further identified priority restorations sites at national-scale to maximize biodiversity outcomes. High-concern invasive plants were recorded from ~254,880 km2 (72% sampled area) and modelled to invade in total ~750,905 km2 (66%) Indian natural systems. While open and deciduous ecosystems were the highest invaded by woody plants, areas with extreme climate and less anthropic pressure were least invaded. Since managing invasions across their range seemed futile due to costly (~13.5 billion USD for one-time management) and ineffective strategies, restoration priority was assigned to least invaded areas (11% protected areas, 23% multi-use) to maximize biodiversity returns. Synthesis and applications: India implemented national-scale invasive plant monitoring by integrating it with the umbrella project on tiger assessment. Embarking on this big data, we show that two-thirds of India’s natural areas are under multiple plant invasions, owing to the legacy of anthropogenic modifications. Our study offers a restoration priority model, empowering policymakers to devise adaptive strategies for restoring invaded biomes and maximizing biodiversity returns.生物入侵对生物多样性与人类福祉构成严重威胁，其中发展中热带国家受其影响更为脆弱。尽管降低入侵影响的紧迫性日益凸显，但入侵管理干预措施常因缺乏入侵物种分布、潜在驱动因子及修复优先级的及时信息而受限。若不结合多目标生物多样性监测体系，在生物地理尺度上生成此类信息往往成本高昂。入侵植物监测与印度全国性老虎种群评估项目进行了整合，该项目以25 km²为采样单元对自然区域开展植物清查。2018年，项目共完成158,979个样地的采样，覆盖面积约358,550 km²。本研究选取206,393个重点关注入侵植物的分布点位，结合社会生态协变量构建其适生分布模型，并识别入侵事件的潜在驱动因子。考虑到入侵态势的严峻性以及入侵管理的资金限制，本研究进一步在全国尺度上划定了修复优先级区域，以实现生物多样性效益的最大化。研究共在约254,880 km²（占采样区域的72%）的范围内记录到重点关注入侵植物，模型预测其潜在入侵总面积可达750,905 km²，占印度自然生态系统的66%。其中，开阔落叶生态系统受木本植物入侵的程度最高，而气候极端且人类活动压力较低的区域受入侵程度最低。鉴于对全入侵范围开展治理的策略不仅成本高昂（一次性治理投入约135亿美元）且效果不佳，本研究将修复优先级划定为受入侵程度最低的区域（其中11%为保护地，23%为多功能用地），以最大化生物多样性收益。综合与应用：印度通过将入侵植物监测与老虎种群评估这一伞护项目相结合，建立了全国尺度的入侵植物监测体系。基于本研究的海量监测数据，我们发现印度三分之二的自然生态系统正遭受多种入侵植物的侵扰，这一现状源于人类活动改造的历史遗留问题。本研究提出的修复优先级模型，可为政策制定者制定受入侵生物群落的适应性修复策略、最大化生物多样性收益提供有力支撑。