Abstract

Submerged macrophytes are important structural components of freshwater ecosystems that are widely used as long-term bioindicators for the trophic state of freshwater lakes. Climate change and related rising water temperatures are suspected to affect macrophyte growth and species composition as well as the length of the growing season. Alternative to the traditional ground-based monitoring methods, remote sensing is expected to provide fast and effective tools to map submerged macrophytes at short intervals and over large areas. This study analyses interrelations between spectral signature, plant phenology and the length of growing season as influenced by the variable water temperature. During the growing seasons of 2011 and 2015, remote sensing reflectance spectra of macrophytes and sediment were collected systematically in-situ with hyperspectral underwater spectroradiometer at Lake Starnberg, Germany. The established spectral libraries were used to develop reflectance models. The combination of spectral information and phenologic characteristics allows the development of a phenologic fingerprint for each macrophyte species. By inversion, the reflectance models deliver day and daytime specific spectral signatures of the macrophyte populations. The subsequent classification processing chain allowed distinguishing species-specific macrophyte growth at different phenologic stages. The analysis of spectral signatures within the phenologic development indicates that the invasive species Elodea nuttallii is less affected by water temperature oscillations than the native species Chara spp. and Potamogeton perfoliatus.

Highlights

  • Macrophytes are important structural components and sensitive bioindicators of the long-term trophic state of freshwater lakes [1]

  • The analysis of spectral signatures within the phenologic development indicates that the invasive species Elodea nuttallii is less affected by water temperature oscillations than the native species Chara spp. and Potamogeton perfoliatus

  • The highest accuracy was obtained for the test sites Chara and P. perfoliatus

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Summary

Introduction

Macrophytes are important structural components and sensitive bioindicators of the long-term trophic state of freshwater lakes [1]. Occurrence and species composition depend on the nutrient conditions, water level, water temperature and transparency [1,2,3,4,5]. Changing environmental conditions affect variations in macrophyte species composition, distribution, vegetation begin and senescence [6,7,8]. A regular update of the macrophyte index [1] in freshwater lake ecosystems is recommended by the European Water Framework Directive (WFD). Palmer et al [10] recommend more frequent observations of freshwater lakes to detect changes in water quality at an early stage. Remote sensing offers a timeand cost-effective method to support monitoring approaches including those recommended by the WFD. Due to its capability to deliver information at high spatiotemporal resolution, remote sensing methods offer the potential to observe detailed seasonal changes in macrophyte distribution and water

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