亲爱的研友该休息了!由于当前在线用户较少,发布求助请尽量完整地填写文献信息,科研通机器人24小时在线,伴您度过漫漫科研夜!身体可是革命的本钱,早点休息,好梦!

Stacked species distribution and macroecological models provide incongruent predictions of species richness for Drosophilidae in the Brazilian savanna

作者
Renata Alves da Mata,Rosana Tidon,Guilherme de Oliveira,Bruno Vilela,José Alexandre Felizola Diniz‐Filho,Thiago F. Rangel,Levi Carina Terribile
出处
期刊:Insect Conservation and Diversity [Wiley]
卷期号:10 (5): 415-424 被引量:19
标识
DOI:10.1111/icad.12240
摘要

Abstract We tested the adequacy of two richness‐modelling approaches within the ‘spatially explicit species assemblage modelling’ ( SESAM ) framework for drosophilid flies in a tropical biome. The pattern of drosophilid species richness throughout the Brazilian savanna was investigated by comparing richness estimates from macroecological models ( MEM ) and stacked species distribution models (S‐ SDM ). We used occurrence records for macroecological modelling and to generate geographic ranges by modelling species’ niches, which were stacked to generate SDM richness. Richness predictions were compared between models and with empirical data from well‐sampled areas. The spatial variation in drosophilid richness for both estimates revealed more species in the central and south‐eastern regions of the biome. Nonetheless, MEM generated a more fragmented pattern than S‐ SDM , with scattered patches of high richness. S‐ SDM produced richness estimates nearer to the empirical values than MEM , which in turn strongly underestimated richness. The correlation between S‐ SDM and observed richness suggests that climate is the major (indirect) driver of drosophilid richness in the Brazilian savanna. Richness estimates based on macroecological modelling are, however, almost certainly affected by inventory incompleteness and sampling bias. We emphasise that S‐ SDM can be a valuable approach to explore species richness patterns in poorly sampled regions.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
7秒前
7秒前
璐璐在这完成签到 ,获得积分10
10秒前
xiaoxinbaba完成签到,获得积分10
12秒前
14秒前
15秒前
xiaoxinbaba发布了新的文献求助10
19秒前
ZZZzzz完成签到,获得积分10
20秒前
xiaoming完成签到,获得积分10
21秒前
MQQ发布了新的文献求助10
21秒前
25秒前
俭朴映寒完成签到,获得积分10
27秒前
Lynne发布了新的文献求助10
30秒前
wangli完成签到,获得积分10
31秒前
35秒前
41秒前
jcksonzhj完成签到,获得积分10
42秒前
能干锦程完成签到,获得积分10
43秒前
CipherSage应助科研通管家采纳,获得10
43秒前
深情安青应助科研通管家采纳,获得10
43秒前
45秒前
安静怜雪完成签到,获得积分10
59秒前
文静的摩托完成签到,获得积分10
1分钟前
高温炉完成签到 ,获得积分10
1分钟前
终止密码子完成签到 ,获得积分10
1分钟前
小歘歘完成签到 ,获得积分10
1分钟前
1分钟前
学不完了发布了新的文献求助10
1分钟前
昏睡的碧菡完成签到,获得积分10
1分钟前
传奇3应助mm采纳,获得10
1分钟前
Luke完成签到,获得积分10
1分钟前
能干锦程发布了新的文献求助10
1分钟前
2分钟前
lili应助杏杏采纳,获得20
2分钟前
2分钟前
害怕的焱发布了新的文献求助10
2分钟前
小狐狸发布了新的文献求助10
2分钟前
害怕的焱完成签到,获得积分10
2分钟前
香蕉觅云应助小狐狸采纳,获得10
2分钟前
不留应助嘻嘻哈哈采纳,获得144
2分钟前
高分求助中
Markov Chain Monte Carlo 10000
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Common Foundations of American and East Asian Modernisation: From Alexander Hamilton to Junichero Koizumi 5000
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
Discerning Saints: Moralization of Intrinsic Motivation and Selective Prosociality at Work 500
Handbuch Trainingswissenschaft – Trainingslehre 500
Additive Manufacturing Design and Applications (ASM Handbook, Volume 24A) 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7585506
求助须知:如何正确求助?哪些是违规求助? 9163824
关于积分的说明 19611671
捐赠科研通 7166722
什么是DOI,文献DOI怎么找? 3266600
关于科研通互助平台的介绍 2431588
邀请新用户注册赠送积分活动 2258310