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Official codebase for NS-Map, as defined in the paper Identifying Nonstationarity in Ecological Time Series.

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Nonstationary S-Map (NS-Map)

This repository contains the data and code associated with the paper "Quantifying nonstationarity in ecological time series" by Kenneth Gee, Tanya Rogers, and Stephan Munch. This method extends S-map empirical dynamic modeling to nonstationary systems through the introduction of a modified weighting kernel.

This package includes the source code for the original implementation of NSMap, as well as various Jupyter Notebooks which execute the simulation experiments and ecological data analysis specified in the paper.

You may get started by looking through the Jupyter notebooks to see how predictions are made and nonstationarity is assessed. If you want to do you own analysis with NSMap, you may install the package using pip install NSMap (https://pypi.org/project/NSMap/).

For help using the project, email the author kenflat2@gmail.com.

Data Sources

Veilleux, B.G. (1979). An Analysis of the Predatory Interaction Between Paramecium and Didinium. Journal of Animal Ecology, 48, 787–803.

Benincà, E., Jöhnk, K.D., Heerkloss, R. & Huisman, J. (2009). Coupled predator–prey oscillations in a chaotic food web. Ecology Letters, 12, 1367–1378.

Peterson, W. (2009). Copepod Species Richness as an Indicator of Long-Term Changes in the Coastal Ecosystem of the Northern California Current. California Cooperative Oceanic Fisheries Investigations Reports, 50.

Ernest, S.K.M., Yenni, G.M., Allington, G., Bledsoe, E.K., Christensen, E.M., Diaz, R.M., et al. (2020). The Portal Project: a long-term study of a Chihuahuan desert ecosystem. bioRxiv, 332783.

Warzybok, P., Santora, J.A., Ainley, D.G., Bradley, R.W., Field, J.C., Capitolo, P.J., et al. (2018). Prey switching and consumption by seabirds in the central California Current upwelling ecosystem: Implications for forage fish management. Journal of Marine Systems, 185, 25–39.

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Official codebase for NS-Map, as defined in the paper Identifying Nonstationarity in Ecological Time Series.

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