Identifying drivers of tropical riverine larval fish abundance and diversity

Author:

Tyler Kyle J.1ORCID,Wedd Dion1,Crook David A.12ORCID,Kennard Mark J.3ORCID,King Alison J.12ORCID

Affiliation:

1. Research Institute for the Environment and Livelihoods, Charles Darwin University, Casuarina, Northern Territory, Australia

2. Centre for Freshwater Ecosystems, La Trobe University, Wodonga, Victoria, Australia

3. Australian Rivers Institute, Griffith University, Nathan, Queensland, Australia

Abstract

Several hypotheses and conceptual models propose to explain mechanisms mediating riverine fish abundance, but few empirical studies to date have explored their utility in tropical systems. This study assesses key components of previous fish recruitment models by exploring spatiotemporal variation in larval fish assemblages in response to predicted key drivers in a tropical Australian river catchment. Data on larval fish composition and abundance, alongside hydrological, hydraulic, habitat and food variables, were collected monthly to bimonthly over one year at eight sites. Variables which best predicted larval fish abundance and diversity were determined with Boosted Regression Trees. The most commonly important predictors were microfauna abundance, structural habitat complexity and temperature, with high values of each predicting high larval fish abundance and diversity. Maximum larval diversity occurred when discharge was highest because several wet-season spawning taxa occurred alongside aseasonally spawning taxa. These findings support previous generic fish recruitment models, demonstrating the utility of their inclusion in the recent Riverine Recruitment Synthesis Model and the applicability of this model for describing processes important for tropical riverine fish recruitment.

Publisher

Canadian Science Publishing

Subject

Aquatic Science,Ecology, Evolution, Behavior and Systematics

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3