Dana Infante

Dr. Dana Infante

Department of Fisheries and Wildlife, College of Agriculture & Natural Resources, Michigan State University, East Lansing, MI 48824, USA
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Research Focus & Metrics

Academic Career Length

19Years (2008-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 September 2020 in Ecological Modelling
Verified
Journal Article
Closed access
HYHao Yu
Hao Yu
ACArthur R. Cooper
Arthur R. Cooper
Dana InfanteDana Infante
Dana Infante

1 August 2022 in Water Biology and Security
Verified
Journal Article
Open access
RVRobert L. Vadas
Robert L. Vadas
RHRobert M. Hughes
Robert M. Hughes
YBYeon Jae Bae
Yeon Jae Bae
MBMin Jeong Baek
Min Jeong Baek
OGOrestes Carlos Bello Gonzáles
Orestes Carlos Bello Gonzáles
CYChris O. Yoder
Chris O. Yoder

2 December 2008 in Hydrobiologia
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Journal Article
Closed access
PDF file
Dana InfanteDana Infante
Dana Infante
JAJ. David Allan
J. David Allan
SLSimon Linke
Simon Linke
RNRichard H. Norris
Richard H. Norris

15 May 2017 in Reviews in Fish Biology and Fisheries
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Journal Article
Closed access
PDF file
CPCraig Paukert
Craig Paukert
ALAbigail J. Lynch
Abigail J. Lynch
TBT. Douglas Beard
T. Douglas Beard
YCYushun Chen
Yushun Chen
SCSteven J. Cooke
Steven J. Cooke
IWIan J. Winfield
Ian J. Winfield

1 February 2021 in Science of The Total Environment
Verified
Journal Article
Closed access
Yin-Phan TsangYin-Phan Tsang
Yin-Phan Tsang
Dana InfanteDana Infante
Dana Infante
LWLizhu Wang
Lizhu Wang
DKDamon Krueger
Damon Krueger
DWDaniel Wieferich
Daniel Wieferich

9 October 2014 in SpringerPlus
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Journal Article
Open access
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Yin-Phan TsangYin-Phan Tsang
Yin-Phan Tsang
DWDaniel Wieferich
Daniel Wieferich
KFKuolin Fung
Kuolin Fung
Dana InfanteDana Infante
Dana Infante
ACArthur R. Cooper
Arthur R. Cooper
The growing quality and availability of spatial map layers (e.g., climate, geology, and land use) allow stream studies, which historically have occurred over small areas like a single watershed or stream reach, to increasingly explore questions from a landscape perspective. This large-scale perspective for fluvial studies depends on the ability to characterize influences on streams resulting from throughout entire upstream networks or catchments. While acquiring upstream information for a single reach is relatively straight-forward, this process becomes demanding when attempting to obtain summaries for all streams throughout a stream network and across large basins. Additionally, the complex nature of stream networks, including braided streams, adds to the challenge of accurately generating upstream summaries. This paper outlines an approach to solve these challenges by building a database and applying an algorithm to gather upstream landscape information for digitized stream networks. This approach avoids the need to directly use spatial data files in computation, and efficiently and accurately acquires various types of upstream summaries of landscape information across large regions using tabular processing. In particular, this approach is not limited to the use of any specific database software or programming language, and its flexibility allows it to be adapted to any digitized stream network as long as it meets a few minimum requirements. This efficient approach facilitates the growing demand of acquiring upstream summaries at large geographic scales and helps to support the use of landscape information in assisting management and decision-making across large regions.