Home ranges have occupied the Wildlife Management research and literature for decades; they are the bread-and-butter of most species accounts and textbooks. Various software exists computing Minimum Convex Polygons (MCPs), Kernel estimators etc. However, the validity, repeatability and transparency of these methods have been questioned by Signer et al. (2015) and others for years, while the U.S. Endangered Species ACT (ESA) or virtually any other legislation hardly use them anyways.
Here I elaborate on sense and mostly non-sense of 'modern' home range work and why it fails in the wider ecology of the species during the Anthropocene when space is finite and widely used up by human industrial-related development.
Citations (in reverse alphabetical order to match podcast content)
Signer, J., Balkenhol, N., Ditmer, M. et al. (2015) Does estimator choice influence our ability to detect changes in home-range size?. Anim
Biotelemetry 3. https://doi.org/10.1186/s40317-015-0051-x
Signer, J. and Balkenhol, N. (2015), Reproducible home ranges (rhr): A new, user‐friendly R package for analyses of wildlife telemetry data. Wildl.
Soc. Bull., 39: 358-363. https://doi.org/10.1002/wsb.539
Huettmann F. (2015) On the Relevance and Moral Impediment of Digital Data Management, Data Sharing, and Public Open Access and Open
Source Code in (Tropical) Research: The Rio Convention Revisited Towards Mega Science and Best Professional Research Practices. In: F.
Huettmann F. (ed.) Central American Biodiversity: Conservation, Ecology, and a Sustainable Future. Springer New York, pages 391-418.
Huettmann, F. (2009) The Global Need for, and Appreciation of, High-Quality Metadata in Biodiversity work. pp 25-28. In: E. Spehn and C. Koerner
(ed). Data Mining for Global Trends in Mountain Biodiversity. CRC Press, Taylor & Francis.
Huettmann, F. (2006) Software certification in the profession of wildlife biology and conservation management: A crucial and required task for
safeguarding species and habitats worldwide. OFWIM (Organisation of Fish and Wildlife Information Managers) Newsletter 5-6.
Huettmann, F. (2005) Databases and science-based management in the context of wildlife and habitat: towards a certified ISO standard for
objective decision-making for the global community by using the internet. Journal of Wildlife Management 69: 466-472.
Humphries G.W. and F. Huettmann (2018) Machine Learning in Wildlife Biology: Algorithms, Data Issues and Availability, Workflows, Citizen Science,
Code Sharing, Metadata and a Brief Historical Perspective. In: G. Humphries, D.R. Magness and F. Huettmann. Machine Learning for
Ecology and Sustainable Natural Resource Management. pp 3-26.
Bluhm, B, D. Watts, and F. Huettmann (2010) Free Database Availability, Metadata and the Internet: An Example of Two High Latitude Components
of the Census of Marine Life. Chapter 13, pp. 233 – 244. In: S. Cushman and F. Huettmann. Spatial Complexity, Informatics and Wildlife
Conservation. Springer Tokyo, Japan. pp. 233-244.
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