Maximilian Pichler

Maximilian Pichler

Universität Regensburg

H-index: 5

Europe-Germany

About Maximilian Pichler

Maximilian Pichler, With an exceptional h-index of 5 and a recent h-index of 5 (since 2020), a distinguished researcher at Universität Regensburg, specializes in the field of Ecology, Machine Learning, Data Science.

His recent articles reflect a diverse array of research interests and contributions to the field:

Novel community data in ecology-properties and prospects

Environmental DNA captures the internal structure of a pond metacommunity

Combining environmental DNA and remote sensing for efficient, fine-scale mapping of arthropod biodiversity

Can predictive models be used for causal inference?

Machine learning and deep learning—A review for ecologists

Fixed or random? On the reliability of mixed‐effects models for a small number of levels in grouping variables

Machine‐learning algorithms predict soil seed bank persistence from easily available traits

Linking functional traits and demography to model species-rich communities

Maximilian Pichler Information

University

Position

___

Citations(all)

261

Citations(since 2020)

260

Cited By

33

hIndex(all)

5

hIndex(since 2020)

5

i10Index(all)

5

i10Index(since 2020)

5

Email

University Profile Page

Universität Regensburg

Google Scholar

View Google Scholar Profile

Maximilian Pichler Skills & Research Interests

Ecology

Machine Learning

Data Science

Top articles of Maximilian Pichler

Title

Journal

Author(s)

Publication Date

Novel community data in ecology-properties and prospects

Florian Hartig

Nerea Abrego

Alex Bush

Jonathan M Chase

Gurutzeta Guillera-Arroita

...

2024

Environmental DNA captures the internal structure of a pond metacommunity

bioRxiv

Wang Cai

Maximilian Pichler

Jeremy Biggs

Pascale Nicolet

Naomi Ewald

...

2023

Combining environmental DNA and remote sensing for efficient, fine-scale mapping of arthropod biodiversity

bioRxiv

Yuanheng Li

Christian Devenish

Marie I Tosa

Mingjie Luo

David M Bell

...

2023/9/12

Can predictive models be used for causal inference?

arXiv preprint arXiv:2306.10551

Maximilian Pichler

Florian Hartig

2023/6/18

Machine learning and deep learning—A review for ecologists

Maximilian Pichler

Florian Hartig

2023/4

Fixed or random? On the reliability of mixed‐effects models for a small number of levels in grouping variables

Ecology and Evolution

Johannes Oberpriller

Melina de Souza Leite

Maximilian Pichler

2022/7

Machine‐learning algorithms predict soil seed bank persistence from easily available traits

Applied Vegetation Science

Sergey Rosbakh

Maximilian Pichler

Peter Poschlod

2022/4

Linking functional traits and demography to model species-rich communities

Nature Communications

Loïc Chalmandrier

Florian Hartig

Daniel C Laughlin

Heike Lischke

Maximilian Pichler

...

2021/5/11

A new joint species distribution model for faster and more accurate inference of species associations from big community data

Methods in Ecology and Evolution

Maximilian Pichler

Florian Hartig

2021/11

See List of Professors in Maximilian Pichler University(Universität Regensburg)