
Rainer Ferdinand WunderlichFrench National Institute for Agriculture, Food, and Environment (INRAE) | INRAE
Rainer Ferdinand Wunderlich
Ph.D. (Bioenvironmental Systems Engineering)
About
17
Publications
11,829
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197
Citations
Introduction
Background:
Geology, Natural Resource Management.
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Current interest:
Spatial Ecology, Distribution Models, Re-sampling, Model Evaluation, Uncertainty, Virtual Species.
Skills and Expertise
Additional affiliations
January 2018 - July 2018
Education
August 2018 - January 2023
February 2012 - April 2014
October 2007 - March 2011
Ludwig-Maximilian-University of Munich & Technische Universität München
Field of study
- Geosciences
Publications
Publications (17)
Model evaluation metrics play a critical role in the selection of adequate species distribution models for conservation and for any application of species distribution modelling (SDM) in general. The responses of these metrics to modelling conditions, however, are rarely taken into account. This leads to inadequate model selection, downstream analy...
Accurate information provided by reliable models is essential for identifying hotspots and mitigating roadkill. However, existing methods, such as kernel density estimation (KDE) and maximum entropy modeling (ME) may individually identify only a subset of the suitable locations for mitigation, because KDE cannot detect hotspots once local abundance...
Context
Species distribution modeling (SDM) is an integral tool for conservation, biogeography, and climate change biology. However, practioners have to choose from increasingly numerous SDM algorithms performing well under different conditions, including clade and resolution.
Objectives
To identify the most suitable SDM algorithms for trees, bird...
Rising energy needs and pressure to reduce greenhouse gas emissions have led to a significant increase in solar power projects worldwide. Recently, the development of floating photovoltaic (FPV) systems offers promising opportunities for land scarce areas. We present a dynamic model that simulates the main biochemical processes in a milkfish (Chano...
In terrestrial ecosystems, the nitrogen dynamics, including N2O production, are majorly regulated by a complex consortium of microbes favored by different substrates and environmental conditions. To better predict the daily, seasonal and annual variation in N2O fluxes, it is critical to estimate the temperature sensitivity of different ammonia-oxid...
Microbes are a critical component of soil ecosystems, performing crucial functions in biogeochemical cycling, carbon sequestration, and plant health. However, it remains uncertain how their community structure, functioning, and resultant nutrient cycling, including net GHG fluxes, would respond to climate change at different scales. Here, we review...
The grapevine (Vitis vinifera) is widely cultivated for the production of wine and other commodities. Wine is globally traded, with an annual market value of approximately USD 4 billion in Portugal alone. However, climate change is expected to profoundly alter regional temperature and precipitation regimes across the Iberian Peninsula and, thus, in...
Nitrogen (N) amendment of soil ecosystems alters GHG fluxes to the atmosphere by increasing nitrous oxide (N2O) emission and affecting methane (CH4) uptakes in well-aerated soils. Although nitrification inhibitors (NIs) can decrease N2O emission, this may alter the rate of ammonia (NH3) volatilization, crop yield, and soil CH4 fluxes by directly or...
Recent advances in computation power have enabled the creation of digital twins of the microbiome (DTM) to substantially curb soil greenhouse gases (GHG) emissions under global change conditions [...]
Understanding the environmental niche segregation of ammonia-oxidizing archaea (AOA) and bacteria (AOB) and its impact on their relative contributions to nitrification and nitrous oxide (N2O) production is essential for predicting N2O dynamics within an ecosystem. Here, we used ammonia oxidizer-specific inhibitors to measure the differential contri...
Nitrification inhibitors (NIs) such as dicyandiamide (DCD), 3,4-dimethylpyrazole phosphate (DMPP), and allylthiourea (AT) are commonly used to suppress ammonia oxidization at different time scales varying from a few hours to several months. Although the responses of NIs to edaphic and temperature conditions have been studied, the influence of the a...
Soil encompasses diverse microbial communities that are essential for fundamental ecosystem functions such as biogeochemical cycling. To better understand underlying biogeochemical processes, it is necessary to know the structure of soil archaeal and bacterial communities and their responses to edaphic and climate variables within and across variou...
Globally, soils are subject to radical changes in their biogeochemistry as rampant deforestation and other forms of land use and climate change continue to transform planet Earth. To better understand soil ecosystem functioning, it is necessary to understand the responses of soil microbial diversity and community structure to changing climate, land...
Though agricultural landscape biodiversity and ecosystem service (ES) conservation is crucial to sustainability, agricultural land is often underrepresented in ES studies, while cultural ES associated with agricultural land is often limited to aesthetic and tourism recreation value only. This study mapped 7 nonmaterial-intangible cultural ES (NICE)...
The human population is exponentially increasing and is projected to reach or exceed 9 billion by 2050. Accordingly, demand for agricultural goods such as cereals and oil crops is expected to grow by more than 200%. To meet crop production targets under a variety of dynamic environmental conditions, new solutions, including further advances in crop...
Local farmer knowledge is key to sustainable agriculture when organic farming promotes biodiversity conservation. Yet, farmers may not recognize ecosystem service (ES) benefits within their agricultural landscape. Surveys were administered to 113 farmers, and the opinions of 58 respondents toward organic farming were analyzed to identify influentia...
Supplementary code.
Maintained at:
https://github.com/RWunderlich/SEDI
Questions
Questions (2)
Dear colleagues,
I would like to predict some species distribution models to the LGM. For (bio-)climatic variables alone this is straightforward and still reasonable for topographic variables based on a paleo-DEM. However, I could not find a global dataset (raster, *.tif, *.afd, etc.) of paleo forest cover in percentage.
Please, let me know if you are aware of such data. Alternatively, I'd like to hear your opinions on how to model proportional LGM forest cover. For the latter, I would like to know which variables and which algorithms (ANN?) you would suggest to model forest cover.
Thanks.