Using Data From Seed-Dispersal Modelling to Manage Invasive Tree Species: The Example of Fraxinus pennsylvanica Marshall in Europe

Management strategies to control invasive species need information about dispersal distances to predict establishment potential. Fraxinus pennsylvanica is a North American anemochorous tree species that is invasive in many Central European floodplain forests. To predict seed-dispersal potential, the stochastic model WaldStat was used, which enables different options for directionality (isotropic and anisotropic) to be simulated. In this article, we (1) show empirical results of fructification and seed dispersal for this tree species. The model predicts approximately 250,000 seeds for one F. pennsylvanica tree. These results were used to (2) calculate species-specific dispersal distances and effects of wind direction. To consider the influence of wind on dispersal potential of the tree species, long-distance dispersal (LDD [95th percentile dispersal distance]) was calculated. Mean dispersal distances varied between 47 and 66 m. LDD values modelled along the main wind direction ranged from 60 to 150 m. Seed production, dispersal distance, and direction data were (3) incorporated into theoretical management scenarios for forest ecosystems. Finally (4), we discuss management options and the practical relevance of model scenarios in relation to the accuracy of spatial dispersal predictions. Further analyses should be focused on possible, well-adapted management concepts at stand level that could restrict the potential spread of invasive species.     

Improvements in anisotropic models of single tree effects in Cartesian coordinates

For anisotropic density functions of e.g. fruit or leaf dispersal, most mathematical research is only done in polar coordinates. However, in software solutions aiming to derive inverse models for real world dispersal data, Cartesian coordinates may be preferred for several reasons. Thus, we introduce an anisotropic model in Cartesian coordinates following the approach in Wälder et al. (2009) with the von Mises approach. By introducing a correction factor, we thereby consider the fundamental attribute, that the integral over a density function with respect to the Cartesian coordinates has to be equal 1. It may have been overlooked so far that guaranteeing for this attribute needs different approaches whether working in polar or Cartesian coordinates. One result is that our approach can be used also for other anisotropic models rather than models from the von Mises approach.     

Evaluation of Catalyzed and Electrically Heated Filters for Removal of Particulate Emissions from Diesel-A- and JP-8-Fueled Engines

Abstract

In-service diesel engines are a significant source of particulate matter (PM) emissions, and they have been subjected to increasingly strict emissions standards. Consequently, the wide-scale use of some type of particulate filter is expected. This study evaluated the effect of an Engelhard catalyzed soot filter (CSF) and a Rypos electrically heated soot filter on the emissions from in-service diesel engines in terms of PM mass, black carbon concentration, particle-bound polycyclic aromatic hydrocarbon concentration, and size distribution. Both filters capture PM. The CSF relies on the engine's exhaust to reach the catalyst regeneration temperature and oxidize soot, whereas the electrically heated filter contains a heating element to oxidize soot. The filters were installed on several military diesel engines. Particle concentrations and compositions were measured before and after installation of the filter and again after several months of operation. Generally, the CSF removed at least 90% of total PM, and the removal efficiency improved or remained constant after several months of operation. In contrast, the electrical filters removed 44-69% of PM mass. In addition to evaluating the soot filters, the sampling team also compared the results of several real-time particle measurement instruments to traditional filter measurements of total mass.     

Windows of change: temporal scale of analysis is decisive to detect ecosystem responses to climate change

Long-term ecological research has become a cornerstone of the scientific endeavour to better understand ecosystem responses to environmental change. This paper provides a perspective on how such research could be advanced. It emphasizes that a profound understanding of the mechanisms underlying these responses requires that records of ecologic processes be not only sufficiently long, but also collected at an appropriate temporal resolution. We base our argument on an overview of studies of climate impacts in limnic and marine ecosystems, suggesting that lakes and oceans respond to (short-term) weather conditions during critical time windows in the year. The observed response patterns are often time-lagged or driven by the crossing of thresholds in weather-related variables (such as water temperature and thermal stratification intensity). It becomes clear from the previous studies that average annual, seasonal or monthly climate data often fall short of characterizing the thermal dynamics that most organisms respond to. To illustrate such literature-based evidence using a concrete example, we compare 2?years of water temperature data from Müggelsee (Berlin, Germany) at multiple temporal scales (from hours to years). This comparison underlines the pitfalls of analysing data at resolutions not high enough to detect critical differences in environmental forcing. Current science initiatives that aim at improving the temporal resolution of long-term observatory data in aquatic systems will help to identify adequate timescales of analysis necessary for the understanding of ecosystem responses to climate change.