鸟类栖息地研究进展
Scientia Silvae Sinicae（2011）
Key Laboratory for Silviculture and Conservation of Ministry of Education | College of Biological Sciences and Technology
Abstract
从研究方法、栖息地选择、栖息地评价、栖息地破碎化等方面对鸟类栖息地的研究进行总结。鸟类栖息地研究常用的方法有条带取样法和0.04hm2圆形地块法等,近年来3S等技术的应用,提高了研究效率,拓展了鸟类栖息地的研究领域;鸟类对栖息地的选择大多以植被等环境因子为基础,在不同空间尺度及不同季节和生活史阶段,鸟类栖息地选择的影响因素各不相同;在鸟类栖息地选择研究基础上,对鸟类栖息地进行适宜性评价及等级划分,可以为鸟类栖息地保护和恢复提供理论依据;栖息地破碎化会对鸟类生存和鸟类行为产生影响,从而影响鸟类种群的营巢成功率、繁殖成功率及鸟类群落分布。从研究对象、方法、内容等方面对国内鸟类栖息地研究进行展望。
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Key words
aves,fragmentation,habitat selection,suitability assessment
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Pretraining has recently greatly promoted the development of natural language processing (NLP)We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performanceWe propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generationThe model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in ChineseExperimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performanceUpload PDF to Generate Summary
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