free bootstrap themes

About PhytoLoss

General objectives

PhytoLoss is a database modul for the assessment of ecological quality in fresh waters using zooplankton data. PhytoLoss estimates the influence of food web interactions on phytoplankton biomass and trophic state. Funding is provided by LAWA (L√§nderArbeits-gemeinschaft WAsser). 

Why PhytoLoss?

Platform for zooplankton analyses

PhytoLoss aims at the compensation of negative effects on zooplankton analysis from of the exclusion of the EU Water Framework Directive. It provides tools for data import, linking with phytoplankton data and calculation of index values.

OTL-MZ

Operational Taxa List Metazooplankton

The OTL-MZ is necessary for consistent coding of zooplankton taxa according to international taxonomic standards prior to the data import procedure. Thus, provided data remain valid for future analyses.

alt

Data quality matters

Standardized import forms

Zooplankton analyses are essential for long-term monitoring of fish as well as the impact of climate change. Therefore, data quality management has to ensure future usability by implementing standard procedures and forms. 

Grazing indices

Guilds and Grazing Effect Strength

The grazing potential can be estimated by linking zooplankton to phytoplankton guild biomass and the calculation of Food Quality Indices (FQI) and Metazooplankton Grazing Indices (MGI). Here, the edible fraction (!) of phytoplankton is of special interest.

Top-down control?

Zooplankton size indices

Zooplankton size is closely related to predation pressure by planktivorous fish and invertebrates. PhytoLoss calculates several size indices and provides a new Index of Predatory Cladocera (Raubcladocerenindex).

Visualisation

Radardiagrams and Profiles

Radardiagrams of selected indices show patterns characteristic of specific ecological states. Results from PhytoLoss are summarized as Zooplankton Lake Profiles.

PhytoLoss - The future

What to expect next...

At the moment PhytoLoss indices are being evaluated in a comprehensive test with real data. Next updates will provide addititional options for data analysis (internal biomass calculation, indices of biodiversity, etc.).