...
首页> 外文期刊>Journal of Ornithology >Predicting the occurrence of rare Brazilian birds with species distribution models
【24h】

Predicting the occurrence of rare Brazilian birds with species distribution models

机译:使用物种分布模型预测巴西珍禽的发生

获取原文
获取原文并翻译 | 示例

摘要

Species distribution models (SDMs) yield reliable and needed predictions to identify regions that have similar environmental conditions and were used here to predict potential ranges of rare species to identify new localities were they might occur based on their occurrence probability (i.e. niche suitability). We modeled the potential distribution ranges of ten endangered or rare birds from the South American Cerrado biome, using four temperature- and four precipitation-related bioclimatic variables, three topographical variables, and nine different niche modeling methods for each species. We used an ensemble-forecasting approach to reach a consensus scenario to obtain the average distribution for each species based on the five best models generating a distribution map of each species. Model efficiency was related to sample size and not appropriate below ten independent spatial occurrences. The potential distributions of seven species revealed that their occurrence ranges might go beyond their known ranges, but that most of them seem to occur near the regions where they have already been reported. The models of only three species were considered unsatisfactory in helping identify their potential distribution. Models created maps with higher occurrence probability regions where rare Cerrado birds might occur. These range projections can potentially decrease the costs and improve the efficiency of future field searches. On methodological terms, the application of SDMs to predict species ranges should compare different modeling methods and evaluate the effect of sample size on their performance.
机译:物种分布模型(SDM)产生可靠且需要的预测,以识别具有相似环境条件的区域,并在此处用于预测稀有物种的潜在范围,以根据新物种的发生概率(即利基适应性)确定它们可能发生的新地点。我们使用四个温度和四个与降水有关的生物气候变量,三个地形变量和每种物种的九种不同的生态位建模方法,对南美Cerrado生物群落中十只濒危或稀有鸟类的潜在分布范围进行了建模。我们使用整体预测方法达成共识,以基于生成每种物种分布图的五个最佳模型获得每种物种的平均分布。模型效率与样本量有关,不适用于十个独立的空间事件。七个物种的潜在分布表明,它们的发生范围可能超出其已知范围,但大多数似乎出现在已报告它们的区域附近。仅三个物种的模型被认为不能帮助他们确定其潜在分布。模型创建的地图具有较高的发生概率区域,在该区域中可能会出现罕见的Cerrado鸟类。这些范围预测可以潜在地降低成本并提高未来野外搜索的效率。从方法上讲,应用SDM预测物种范围应比较不同的建模方法并评估样本量对其性能的影响。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号