Herbaceous perennial plants with short generation time have stronger responses to climate anomalies than those with longer generation time.

There is an urgent need to synthesize the state of our knowledge on plant responses to climate. The availability of open-access data provide opportunities to examine quantitative generalizations regarding which biomes and species are most responsive to climate drivers. Here, we synthesize time series of structured population models from 162 populations of 62 plants, mostly herbaceous species from temperate biomes, to link plant population growth rates (λ) to precipitation and temperature drivers. We expect: (1) more pronounced demographic responses to precipitation than temperature, especially in arid biomes; and (2) a higher climate sensitivity in short-lived rather than long-lived species. We find that precipitation anomalies have a nearly three-fold larger effect on λ than temperature. Species with shorter generation time have much stronger absolute responses to climate anomalies. We conclude that key species-level traits can predict plant population responses to climate, and discuss the relevance of this generalization for conservation planning.

Assessing in situ dominance pattern of phytoplankton classes by dominance analysis as a proxy for realized niches.

This study looks at two facets of dominant phytoplankton classes during phytoplankton succession. A detailed assessment of this issue is of special interest with regard to realized niches from a theoretical point of view but also for lake management as practical application. A realized niche mirrors the functional adaptability of an organism in a lake-specific constellation of environmental parameters. Therefore, the characterization of realized niches could be a key factor for management of problematic waters. Different strategies exist to control eutrophication and the risk of blooms by harmful algae. During the last decades, many restoration measures were initiated to manage eutrophicated inland lakes. In the past, it has become evident several times that restoration strategies do not necessarily lead to a reduction of biomass of undesirable cyanobacteria but can even promote their development. Due to this uncertainty of success and the high costs for remediation strategies, new prediction tools are required - ideally, based on routine monitoring data. Therefore, we developed a new method to extract potential optimal growth conditions (POGC) as indicators of realized niches for different phytoplankton taxa from existing data to improve existing strategies used in lake remediation and restoration. The analysis presented in this work is based on dominance pattern of different phytoplankton groups relative to environmental variables. Interpretation of these dominance patterns as indicators of POGC showed distinct pattern for several phytoplankton classes for all investigated objects. We identified low nitrogen and phosphate concentrations as favorable condition for cyanobacteria in Lake Auensee and Lake Feldberger Haussee. The reservoir Bleilochtalsperre showed a high N/P-concentration and cyanobacteria dominance was generally very low.