临灭绝的和同源竞争者的最新范围地图揭示了不同的利基偏好
Jo A Werba1,2, David A W Miller2, Adrianne B Brand1
1U.S. Geological Survey, Eastern Ecological Science Center (Patuxent Wildlife Research Center) SO Conte Anadromous Fish Research Laboratory Turners Falls Massachusetts USA.
Ecology and evolution
|May 22, 2024
概括
这项研究开发了一种灵活的模型,以准确估计罕见的物种分布,即使在小规模. 该模型考虑了各种数据挑战,改善了保护工作的分布和不确定性估计.
科学领域:
- 生态与保护生物学 生态与保护生物学
- 量化生态学 量化生态学
- 种类分布建模 种类分布建模
背景情况:
- 估计范围受限物种的分布具有挑战性,因为微小尺度上的生物气候变化有限.
- 传统的物种分布模型在小规模数据和各种调查方法方面扎.
- 准确的分布和不确定性估计对于有效保护稀有物种至关重要.
研究的目的:
- 开发和应用一种灵活的分析方法,以高分辨率 (100x100米) 建模物种分布.
- 为了改善分布和不确定性的估计,神秘的,范围有限的物种,如Shenandoah (Plethodon shenandoah).
- 为了确定影响沙龙分布在微细空间尺度上的关键非生物因素.
主要方法:
- 来自多种调查类型的综合数据,考虑到季节性可用性和重复调查.
- 利用了具有空间共变量,随机效应和对调查协议的偏移的通用增值模型.
- 与温度和降水相关的检测和可用性的内置时间变化.
主要成果:
- 空间随机效应对于识别小规模发生差异和估计不确定性至关重要.
- 沙兰的数量在降雨后增加,Plethodon cinereus比Plethodon shenandoah更能容忍潮湿的条件.
- 鉴定了关键的非生物关系,并改善了分布估计,尽管数据尺度不匹配.
结论:
- 灵活的分析方法提高了分布和不确定性估计,特别是在范围较小的物种.
- 控制空间自相关性,估计空间不确定性,并纳入调查特定数据,提高模型可靠性.
- 该研究强调了微观无生物因素对于理解物种分布和为保护提供信息的重要性.
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