A novel method to estimate the response of habitat types to nitrogen deposition.

Increasing nitrogen depositions adversely affect European landscapes, including habitats within the Natura2000 network. Critical loads for nitrogen deposition have been established to quantify the loss of habitat quality. When the nitrogen deposition rises above a habitat-specific critical load, the quality of the focal habitat is expected to be negatively influenced. Here, we investigate how the quality of habitat types is affected beyond the critical load. We calculated response curves for 60 terrestrial habitat types in the Netherlands to the estimated nitrogen deposition (EMEP-data). The curves for habitat types are based on the occurrence of their characteristic plant species in North-Western Europe (plot data from the European Vegetation Archive). The estimated response curves were corrected for soil type, mean annual temperature and annual precipitation. Evaluation was carried out by expert judgement, and by comparison with gradient deposition field studies. For 39 habitats the response to nitrogen deposition was judged to be reliable by five experts, while out of the 41 habitat types for which field studies were available, 25 showed a good agreement. Some of the curves showed a steep decline in quality and some a more gradual decline with increasing nitrogen deposition. We compared the response curves with both the empirical and modelled critical loads. For 41 curves, we found a decline already starting below the critical load.

Prediction of plant species occurrence as affected by nitrogen deposition and climate change on a European scale.

Plant species occurrence in Europe is affected by changes in nitrogen deposition and climate. Insight into potential future effects of those changes can be derived by a model approach based on field-based empirical evidence on a continental scale. In this paper, we present a newly developed empirical model PROPS, predicting the occurrence probabilities of plant species in response to a combination of climatic factors, nitrogen deposition and soil properties. Parameters included were temperature, precipitation, nitrogen deposition, soil pH and soil C/N ratio. The PROPS model was fitted to plant species occurrence data of about 800,000 European relevés with estimated values for pH and soil C/N ratio and interpolated climate and modelled N deposition data obtained from the Ensemble meteo data set and EMEP model results, respectively. The model was validated on an independent data set. The test of ten species against field data gave an average Pearson's r-value of 0.79. PROPS was applied to a grassland and a heathland site to evaluate the effect of scenarios for nitrogen deposition and climate change on the Habitat Suitability Index (HSI), being the average of the relative probabilities, compared to the maximum probability, of all target species in a habitat. Results for the period 1930-2050 showed that an initial increase and later decrease in nitrogen deposition led to a pronounced decrease in HSI, and with dropping nitrogen deposition to an increase of the HSI. The effect of climate change appeared to be limited, resulting in a slight increase in HSI.

Threshold effects of air pollution and climate change on understory plant communities at forested sites in the eastern United States.

Forest understory plant communities in the eastern United States are often diverse and are potentially sensitive to changes in climate and atmospheric inputs of nitrogen caused by air pollution. In recent years, empirical and processed-based mathematical models have been developed to investigate such changes in plant communities. In the study reported here, a robust set of understory vegetation response functions (expressed as version 2 of the Probability of Occurrence of Plant Species model for the United States [US-PROPS v2]) was developed based on observations of forest understory and grassland plant species presence/absence and associated abiotic characteristics derived from spatial datasets. Improvements to the US-PROPS model, relative to version 1, were mostly focused on inclusion of additional input data, development of custom species-level input datasets, and implementation of methods to address uncertainty. We investigated the application of US-PROPS v2 to evaluate the potential impacts of atmospheric nitrogen (N) and sulfur (S) deposition, and climate change on forest ecosystems at three forested sites located in New Hampshire, Virginia, and Tennessee in the eastern United States. Species-level N and S critical loads (CLs) were determined under ambient deposition at all three modeled sites. The lowest species-level CLs of N deposition at each site were between 2 and 11 kg N/ha/yr. Similarly, the lowest CLs of S deposition, based on the predicted soil pH response, were less than 2 kg S/ha/yr among the three sites. Critical load exceedance was found at all three model sites. The New Hampshire site included the largest percentage of species in exceedance. Simulated warming air temperature typically resulted in lower maximum occurrence probability, which contributed to lower CLs of N and S deposition. The US-PROPS v2 model, together with the PROPS-CLF model to derive CL functions, can be used to develop site-specific CLs for understory plants within broad regions of the United States. This study demonstrates that species-level CLs of N and S deposition are spatially variable according to the climate, light availability, and soil characteristics at a given location. Although the species niche models generally performed well in predicting occurrence probability, there remains uncertainty with respect to the accuracy of reported CLs. As such, the specific CLs reported here should be considered as preliminary estimates.

Feasibility of coupled empirical and dynamic modeling to assess climate change and air pollution impacts on temperate forest vegetation of the eastern United States.

Changes in climate and atmospheric nitrogen (N) deposition caused pronounced changes in soil conditions and habitat suitability for many plant species over the latter half of the previous century. Such changes are expected to continue in the future with anticipated further changing air temperature and precipitation that will likely influence the effects of N deposition. To investigate the potential long-term impacts of atmospheric N deposition on hardwood forest ecosystems in the eastern United States in the context of climate change, application of the coupled biogeochemical and vegetation community model VSD+PROPS was explored at three sites in New Hampshire, Virginia, and Tennessee. This represents the first application of VSD+PROPS to forest ecosystems in the United States. Climate change and elevated (above mid-19th century) N deposition were simulated to be important factors for determining habitat suitability. Although simulation results suggested that the suitability of these forests to support the continued presence of their characteristic understory plant species might decline by the year 2100, low data availability for building vegetation response models with PROPS resulted in uncertain results at the extremes of simulated N deposition. Future PROPS model development in the United States should focus on inclusion of additional foundational data or alternate candidate predictor variables to reduce these uncertainties.

Year-round grazing to counteract effects of atmospheric nitrogen deposition may aggravate these effects.

Excessive nitrogen input in natural ecosystems is a major threat to biodiversity. A coastal dune area near Amsterdam in the Netherlands suffers from high atmospheric nitrogen deposition affecting sensitive habitats such as fixed coastal dunes with herbaceous vegetation ('grey dunes'). To mitigate its effect year round grazing was applied from 2007 until 2012. In winter, when natural food supply is low, the cattle received supplementary hay that caused additional inputs of nitrogen. Estimates based on nitrogen contents of hay, as well as of manure, showed the input through winter feeding (c. 3-14 kg N ha(-1).y(-1)) is in the same order of magnitude as both the actual deposition (c. 17 kg N ha(-1).y(-1)) and the critical load for a number of herbaceous habitat types (10-15 kg N ha(-1).y(-1)). Locally, the effect of winter feeding adds to the effect of nitrogen redistribution within the area caused by the cattle's terrain usage. We conclude that winter feeding may aggravate effects of atmospheric nitrogen deposition.

Use of dynamic soil-vegetation models to assess impacts of nitrogen deposition on plant species composition: an overview.

Field observations and experimental data of effects of nitrogen (N) deposition on plant species diversity have been used to derive empirical critical N loads for various ecosystems. The great advantage of such an approach is the inclusion of field evidence, but there are also restrictions, such as the absence of explicit criteria regarding significant effects on the vegetation, and the impossibility to predict future impacts when N deposition changes. Model approaches can account for this. In this paper, we review the possibilities of static and dynamic multispecies models in combination with dynamic soil-vegetation models to (1) predict plant species composition as a function of atmospheric N deposition and (2) calculate critical N loads in relation to a prescribed protection level of the species composition. The similarities between the models are presented, but also several important differences, including the use of different indicators for N and acidity and the prediction of individual plant species vs. plant communities. A summary of the strengths and weaknesses of the various models, including their validation status, is given. Furthermore, examples are given of critical load calculations with the model chains and their comparison with empirical critical N loads. We show that linked biogeochemistry-biodiversity models for N have potential for applications to support European policy to reduce N input, but the definition of damage thresholds for terrestrial biodiversity represents a major challenge. There is also a clear need for further testing and validation of the models against long-term monitoring or long-term experimental data sets and against large-scale survey data. This requires a focused data collection in Europe, combing vegetation descriptions with variables affecting the species diversity, such as soil acidity, nutrient status and water availability. Finally, there is a need for adaptation and upscaling of the models beyond the regions for which dose-response relationships have been parameterized, to make them generally applicable.