Biodiversity forecasting in natural plankton communities reveals temperature and biotic interactions as key predictors

As natural ecosystems face unprecedented human-made degradation, it is urgent to provide quantitative forecasts of changes in biodiversity and identify relevant biotic and abiotic predictors. Forecasting natural ecosystems has proven challenging due to their complexity, chaotic nonlinear nature, and lack of adequate data. In this study, we investigate the predictability of lake plankton biodiversity using four years of daily data of environmental predictors and community metrics derived from state-dependent models. Our findings show that presence-absence-based biodiversity metrics are more predictable than abundance-based metrics. For short-term forecasts, the most significant predictor of species richness is prior richness, while the key predictors for Jaccard dissimilarity are prior richness and prior Jaccard dissimilarity. In long-term forecasts of both metrics, water temperature emerges as the primary predictor, with community connectance (number of interactions) also contributing t..., , , # Biodiversity forecasting in natural plankton communities reveals temperature and biotic interactions as key predictors

[https://doi.org/10.5061/dryad.0zpc86775](https://doi.org/10.5061/dryad.0zpc86775)

## Description of the data and file structure

We obtained high-frequency data on physical and chemical water parameters, plankton abundance, nutrients, and weather from an autonomous lake monitoring platform in the middle of Lake Greifen, a small peri-alpine eutrophic lake in central Switzerland. All missing data represented as NA.

### Files and variables

#### File: code\_data.zip

**Description:** 

### **data**

This folder contains the raw and formatted data to reproduce the analyses.

**analysis_variables.csv**: Contains the variables used for the analysis (i.e., biodiversity change variables, biotic and abiotic predictors. NA values in the data indicate that no values are available for that given time point.

* **date**: The date when the measurement was taken in the format ye...,