TY  - JOUR
A1  - Dormann, Carsten F.
A1  - Elith, Jane
A1  - Bacher, Sven
A1  - Buchmann, Carsten M.
A1  - Carl, Gudrun
A1  - Carre, Gabriel
A1  - Garcia Marquez, Jaime R.
A1  - Gruber, Bernd
A1  - Lafourcade, Bruno
A1  - Leitao, Pedro J.
A1  - Münkemüller, Tamara
A1  - McClean, Colin
A1  - Osborne, Patrick E.
A1  - Reineking, Bjoern
A1  - Schröder-Esselbach, Boris
A1  - Skidmore, Andrew K.
A1  - Zurell, Damaris
A1  - Lautenbach, Sven
T1  - Collinearity a review of methods to deal with it and a simulation study evaluating their performance
JF  - Ecography : pattern and diversity in ecology ; research papers forum
N2  - Collinearity refers to the non independence of predictor variables, usually in a regression-type analysis. It is a common feature of any descriptive ecological data set and can be a problem for parameter estimation because it inflates the variance of regression parameters and hence potentially leads to the wrong identification of relevant predictors in a statistical model. Collinearity is a severe problem when a model is trained on data from one region or time, and predicted to another with a different or unknown structure of collinearity. To demonstrate the reach of the problem of collinearity in ecology, we show how relationships among predictors differ between biomes, change over spatial scales and through time. Across disciplines, different approaches to addressing collinearity problems have been developed, ranging from clustering of predictors, threshold-based pre-selection, through latent variable methods, to shrinkage and regularisation. Using simulated data with five predictor-response relationships of increasing complexity and eight levels of collinearity we compared ways to address collinearity with standard multiple regression and machine-learning approaches. We assessed the performance of each approach by testing its impact on prediction to new data. In the extreme, we tested whether the methods were able to identify the true underlying relationship in a training dataset with strong collinearity by evaluating its performance on a test dataset without any collinearity. We found that methods specifically designed for collinearity, such as latent variable methods and tree based models, did not outperform the traditional GLM and threshold-based pre-selection. Our results highlight the value of GLM in combination with penalised methods (particularly ridge) and threshold-based pre-selection when omitted variables are considered in the final interpretation. However, all approaches tested yielded degraded predictions under change in collinearity structure and the folk lore'-thresholds of correlation coefficients between predictor variables of |r| >0.7 was an appropriate indicator for when collinearity begins to severely distort model estimation and subsequent prediction. The use of ecological understanding of the system in pre-analysis variable selection and the choice of the least sensitive statistical approaches reduce the problems of collinearity, but cannot ultimately solve them.
Y1  - 2013
U6  - https://doi.org/10.1111/j.1600-0587.2012.07348.x
SN  - 0906-7590
SN  - 1600-0587
VL  - 36
IS  - 1
SP  - 27
EP  - 46
PB  - Wiley-Blackwell
CY  - Hoboken
ER  - 
TY  - JOUR
A1  - Dormann, Carsten F.
A1  - Schymanski, Stanislaus J.
A1  - Cabral, Juliano Sarmento
A1  - Chuine, Isabelle
A1  - Graham, Catherine
A1  - Hartig, Florian
A1  - Kearney, Michael
A1  - Morin, Xavier
A1  - Römermann, Christine
A1  - Schröder-Esselbach, Boris
A1  - Singer, Alexander
T1  - Correlation and process in species distribution models: bridging a dichotomy
JF  - Journal of biogeography
N2  - Within the field of species distribution modelling an apparent dichotomy exists between process-based and correlative approaches, where the processes are explicit in the former and implicit in the latter. However, these intuitive distinctions can become blurred when comparing species distribution modelling approaches in more detail. In this review article, we contrast the extremes of the correlativeprocess spectrum of species distribution models with respect to core assumptions, model building and selection strategies, validation, uncertainties, common errors and the questions they are most suited to answer. The extremes of such approaches differ clearly in many aspects, such as model building approaches, parameter estimation strategies and transferability. However, they also share strengths and weaknesses. We show that claims of one approach being intrinsically superior to the other are misguided and that they ignore the processcorrelation continuum as well as the domains of questions that each approach is addressing. Nonetheless, the application of process-based approaches to species distribution modelling lags far behind more correlative (process-implicit) methods and more research is required to explore their potential benefits. Critical issues for the employment of species distribution modelling approaches are given, together with a guideline for appropriate usage. We close with challenges for future development of process-explicit species distribution models and how they may complement current approaches to study species distributions.
KW  - Hypothesis generation
KW  - mechanistic model
KW  - parameterization
KW  - process-based model
KW  - species distribution model
KW  - SDM
KW  - uncertainty
KW  - validation
Y1  - 2012
U6  - https://doi.org/10.1111/j.1365-2699.2011.02659.x
SN  - 0305-0270
VL  - 39
IS  - 12
SP  - 2119
EP  - 2131
PB  - Wiley-Blackwell
CY  - Hoboken
ER  - 
TY  - JOUR
A1  - Hunke, Philip
A1  - Müller, Eva Nora
A1  - Schröder-Esselbach, Boris
A1  - Zeilhofer, Peter
T1  - The Brazilian Cerrado: assessment of water and soil degradation in catchments under intensive agricultural use
JF  - Ecohydrology : ecosystems, land and water process interactions, ecohydrogeomorphology
N2  - The Brazilian Cerrado is recognized as one of the most threatened biomes in the world, as the region has experienced a striking change from natural Cerrado vegetation to intense cash crop production. This paper reviews the history of land conversion in the Cerrado and the development of soil properties and water resources under past and ongoing land use. We compared soil and water quality parameters from different land uses considering 80 soil and 18 water studies conducted in different regions across the Cerrado to provide quantitative evidence of soil and water alterations from land use change.
 Following the conversion of native Cerrado, significant effects on soil pH, bulk density and available P and K for croplands and less-pronounced effects on pastures were evident. Soil total N did not differ between land uses because most of the sites classified as croplands were nitrogen-fixing soybeans, which are not artificially fertilized with N. In contrast, water quality studies showed nitrogen enrichment in agricultural catchments, indicating fertilizer impacts and potential susceptibility to eutrophication. Regardless of the land use, P is widely absent because of the high-fixing capacities of deeply weathered soils and the filtering capacity of riparian vegetation. Pesticides, however, were consistently detected throughout the entire aquatic system. In several case studies, extremely high-peak concentrations exceeded Brazilian and European Union (EU) water quality limits, which were potentially accompanied by serious health implications. Land use intensification is likely to continue, particularly in regions where less annual rainfall and severe droughts are projected in the northeastern and western Cerrado. Thus, the leaching risk and displacement of agrochemicals are expected to increase, particularly because the current legislation has caused a reduction in riparian vegetation. We conclude that land use intensification is likely to seriously limit the Cerrado's future regarding both agricultural productivity and ecosystem stability. Because only limited data are available, we recommend further field studies to understand the interaction between terrestrial and aquatic systems. This study may serve as a valuable database for integrated modelling to investigate the impact of land use and climate change on soil and water resources and to test and develop mitigation measures for the Cerrado. Copyright (C) 2014 John Wiley & Sons, Ltd.
KW  - Cerrado
KW  - land degradation
KW  - ecosystem change
KW  - water quality
KW  - soil parameters
KW  - ecohydrology
KW  - land use change
KW  - Mato Grosso
KW  - pesticides
KW  - cash crops
Y1  - 2015
U6  - https://doi.org/10.1002/eco.1573
SN  - 1936-0584
SN  - 1936-0592
VL  - 8
IS  - 6
SP  - 1154
EP  - 1180
PB  - Wiley-Blackwell
CY  - Hoboken
ER  - 
TY  - JOUR
A1  - Häring, Tim
A1  - Dietz, Elke
A1  - Osenstetter, Sebastian
A1  - Koschitzki, Thomas
A1  - Schröder-Esselbach, Boris
T1  - Spatial disaggregation of complex soil map units: A decision-tree based approach in Bavarian forest soils
JF  - Geoderma : an international journal of soil science
N2  - Detailed knowledge on the spatial distribution of soils is crucial for environmental monitoring, management, and modeling. However soil maps with a finite number of discrete soil map units are often the only available information about soils. Depending on the map scale or the detailing of the map legend this information could be too imprecise. We present a method for the spatial disaggregation of map units, namely the refinement of complex soil map units in which two or more soil types are aggregated. Our aim is to draw new boundaries inside the map polygons to represent a single soil type and no longer a mixture of several soil types. The basic idea for our method is the functional relationship between soil types and topographic position as formulated in the concept of the catena. We use a comprehensive soil profile database and topographic attributes derived from a 10 m digital elevation model as input data for the classification of soil types with random forest models. We grouped all complex map units which have the same combination of soil types. Each group of map units is modeled separately. For prediction of the soil types we stratified the soil map into these groups and apply a specific random forest model only to the associated map units. In order to get reliable results we define a threshold for the predicted probabilities at 0.7 to assign a specific soil type. In areas where the probability is below 0.7 for every possible soil type we assign a new class "indifferent" because the model only makes unspecific classification there. Our results show a significant spatial refinement of the original soil polygons. Validation of our predictions was estimated on 1812 independent soil profiles which were collected subsequent to prediction in the field. Field validation gave an overall accuracy of 70%. Map units, in which shallow soils were grouped together with deep soils could be separated best. Also histosols could be predicted successful. Highest error rate were found in map units, in which Gleysoils were grouped together with deep soils or Anthrosols. To check for validity of our results we open the black box random forest model by calculating the variable importance for each predictor variable and plotting response surfaces. We found good confirmations of our hypotheses, that topography has a significant influence on the spatial arrangement of soil types and that these relationships can be used for disaggregation.
Y1  - 2012
U6  - https://doi.org/10.1016/j.geoderma.2012.04.001
SN  - 0016-7061
VL  - 185
IS  - 6
SP  - 37
EP  - 47
PB  - Elsevier
CY  - Amsterdam
ER  - 
TY  - JOUR
A1  - Häring, Tim
A1  - Reger, Birgit
A1  - Ewald, Jörg
A1  - Hothorn, Torsten
A1  - Schröder-Esselbach, Boris
T1  - Predicting Ellenberg's soil moisture indicator value in the Bavarian Alps using additive georegression
JF  - Applied vegetation science : official organ of the International Association for Vegetation Science
N2  - Questions Can forest site characteristics be used to predict Ellenberg indicator values for soil moisture? Which is the best averaged mean value for modelling? Does the distribution of soil moisture depend on spatial information? Location Bavarian Alps, Germany. Methods We used topographic, climatic and edaphic variables to model the mean soil moisture value as found on 1505 forest plots from the database WINALPecobase. All predictor variables were taken from area-wide geodata layers so that the model can be applied to some 250 000 ha of forest in the target region. We adopted methods developed in species distribution modelling to regionalize Ellenberg indicator values. Therefore, we use the additive georegression framework for spatial prediction of Ellenberg values with the R-library mboost, which is a feasible way to consider environmental effects, spatial autocorrelation, predictor interactions and non-stationarity simultaneously in our data. The framework is much more flexible than established statistical and machine-learning models in species distribution modelling. We estimated five different mboost models reflecting different model structures on 50 bootstrap samples in each case. Results Median R2 values calculated on independent test samples ranged from 0.28 to 0.45. Our results show a significant influence of interactions and non-stationarity in addition to environmental covariates. Unweighted mean indicator values can be modelled better than abundance-weighted values, and the consideration of bryophytes did not improve model performance. Partial response curves indicate meaningful dependencies between moisture indicator values and environmental covariates. However, mean indicator values <4.5 and >6.0 could not be modelled correctly, since they were poorly represented in our calibration sample. The final map represents high-resolution information of site hydrological conditions. Conclusions Indicator values offer an effect-oriented alternative to physically-based hydrological models to predict water-related site conditions, even at landscape scale. The presented approach is applicable to all kinds of Ellenberg indicator values. Therefore, it is a significant step towards a new generation of models of forest site types and potential natural vegetation.
KW  - Boosting
KW  - Mboost
KW  - Non-stationarity
KW  - Predictive vegetation mapping
KW  - Site ecology
KW  - Species distribution modelling
Y1  - 2013
U6  - https://doi.org/10.1111/j.1654-109X.2012.01210.x
SN  - 1402-2001
VL  - 16
IS  - 1
SP  - 110
EP  - 121
PB  - Wiley-Blackwell
CY  - Hoboken
ER  - 
TY  - GEN
A1  - Jeltsch, Florian
A1  - Bonte, Dries
A1  - Pe'er, Guy
A1  - Reineking, Björn
A1  - Leimgruber, Peter
A1  - Balkenhol, Niko
A1  - Schröder-Esselbach, Boris
A1  - Buchmann, Carsten M.
A1  - Müller, Thomas
A1  - Blaum, Niels
A1  - Zurell, Damaris
A1  - Böhning-Gaese, Katrin
A1  - Wiegand, Thorsten
A1  - Eccard, Jana
A1  - Hofer, Heribert
A1  - Reeg, Jette
A1  - Eggers, Ute
A1  - Bauer, Silke
T1  - Integrating movement ecology with biodiversity research
BT  - exploring new avenues to address spatiotemporal biodiversity dynamics
N2  - Movement of organisms is one of the key mechanisms shaping biodiversity, e.g. the distribution of genes, individuals and species in space and time. Recent technological and conceptual advances have improved our ability to assess the causes and consequences of individual movement, and led to the emergence of the new field of ‘movement ecology’. Here, we outline how movement ecology can contribute to the broad field of biodiversity research, i.e. the study of processes and patterns of life among and across different scales, from genes to ecosystems, and we propose a conceptual framework linking these hitherto largely separated fields of research. Our framework builds on the concept of movement ecology for individuals, and demonstrates its importance for linking individual organismal movement with biodiversity. First, organismal movements can provide ‘mobile links’ between habitats or ecosystems, thereby connecting resources, genes, and processes among otherwise separate locations. Understanding these mobile links and their impact on biodiversity will be facilitated by movement ecology, because mobile links can be created by different modes of movement (i.e., foraging, dispersal, migration) that relate to different spatiotemporal scales and have differential effects on biodiversity. Second, organismal movements can also mediate coexistence in communities, through ‘equalizing’ and ‘stabilizing’ mechanisms. This novel integrated framework provides a conceptual starting point for a better understanding of biodiversity dynamics in light of individual movement and space-use behavior across spatiotemporal scales. By illustrating this framework with examples, we argue that the integration of movement ecology and biodiversity research will also enhance our ability to conserve diversity at the genetic, species, and ecosystem levels.
T3  - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 401 
KW  - mobile links
KW  - species coexistence
KW  - community dynamics
KW  - biodiversity conservation
KW  - long distance movement
KW  - landscape genetics
KW  - individual based modeling
Y1  - 2017
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-401177
ER  - 
TY  - JOUR
A1  - Jeltsch, Florian
A1  - Bonte, Dries
A1  - Peer, Guy
A1  - Reineking, Björn
A1  - Leimgruber, Peter
A1  - Balkenhol, Niko
A1  - Schröder-Esselbach, Boris
A1  - Buchmann, Carsten M.
A1  - Müller, Thomas
A1  - Blaum, Niels
A1  - Zurell, Damaris
A1  - Böhning-Gaese, Katrin
A1  - Wiegand, Thorsten
A1  - Eccard, Jana
A1  - Hofer, Heribert
A1  - Reeg, Jette
A1  - Eggers, Ute
A1  - Bauer, Silke
T1  - Integrating movement ecology with biodiversity research - exploring new avenues to address spatiotemporal biodiversity dynamics
Y1  - 2013
UR  - http://download.springer.com/static/pdf/827/art%253A10.1186%252F2051-3933-1- 6.pdf?auth66=1394891271_f1a4cb74d6be42ee3f8872ef2ca22c24&ext=.pdf
U6  - https://doi.org/10.1186/2051-3933-1-6
ER  - 
TY  - CHAP
A1  - Jeltsch, Florian
A1  - Schröder-Esselbach, Boris
A1  - Blaum, Niels
A1  - Badeck, Franz-Werner
T1  - Einsatz der Fernerkundung in der Ökologie
BT  - Beispiele, Synergien und mögliche Verknüpfungen
N2  - Interdisziplinäres Zentrum für Musterdynamik und Angewandte Fernerkundung Workshop vom 9. - 10. Februar 2006
Y1  - 2006
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus-7075
ER  - 
TY  - JOUR
A1  - Kleyer, Michael
A1  - Schröder-Esselbach, Boris
A1  - Biedermann, Robert
A1  - Rudner, Michael
A1  - Fritzsch, K.
A1  - Kühner, A.
A1  - Poschlod, P.
A1  - Kahmen, S.
A1  - Tackenberg, O.
A1  - Talmon, E.
A1  - Poethke, H.-J.
A1  - Obermaier, E.
A1  - Hein, S.
A1  - Hinsch, M.
A1  - Henle, K.
A1  - Settele, Josef
A1  - Binzenhöfer, Birgit
A1  - Pfeifer, A.
A1  - Kögl, H.
T1  - Freie Beweidung mit geringer Besatzdichte und Fräsen als alternative Verfahren zur Pflege von Magerrasen
Y1  - 2004
SN  - 0341-7026
ER  - 
TY  - JOUR
A1  - Kramer-Schadt, Stephanie
A1  - Niedballa, Jürgen
A1  - Pilgrim, John D.
A1  - Schröder-Esselbach, Boris
A1  - Lindenborn, Jana
A1  - Reinfelder, Vanessa
A1  - Stillfried, Milena
A1  - Heckmann, Ilja
A1  - Scharf, Anne K.
A1  - Augeri, Dave M.
A1  - Cheyne, Susan M.
A1  - Hearn, Andrew J.
A1  - Ross, Joanna
A1  - Macdonald, David W.
A1  - Mathai, John
A1  - Eaton, James
A1  - Marshall, Andrew J.
A1  - Semiadi, Gono
A1  - Rustam, Rustam
A1  - Bernard, Henry
A1  - Alfred, Raymond
A1  - Samejima, Hiromitsu
A1  - Duckworth, J. W.
A1  - Breitenmoser-Wuersten, Christine
A1  - Belant, Jerrold L.
A1  - Hofer, Heribert
A1  - Wilting, Andreas
T1  - The importance of correcting for sampling bias in MaxEnt species distribution models
JF  - Diversity & distributions : a journal of biological invasions and biodiversity
N2  - AimAdvancement in ecological methods predicting species distributions is a crucial precondition for deriving sound management actions. Maximum entropy (MaxEnt) models are a popular tool to predict species distributions, as they are considered able to cope well with sparse, irregularly sampled data and minor location errors. Although a fundamental assumption of MaxEnt is that the entire area of interest has been systematically sampled, in practice, MaxEnt models are usually built from occurrence records that are spatially biased towards better-surveyed areas. Two common, yet not compared, strategies to cope with uneven sampling effort are spatial filtering of occurrence data and background manipulation using environmental data with the same spatial bias as occurrence data. We tested these strategies using simulated data and a recently collated dataset on Malay civet Viverra tangalunga in Borneo.
 LocationBorneo, Southeast Asia.
 MethodsWe collated 504 occurrence records of Malay civets from Borneo of which 291 records were from 2001 to 2011 and used them in the MaxEnt analysis (baseline scenario) together with 25 environmental input variables. We simulated datasets for two virtual species (similar to a range-restricted highland and a lowland species) using the same number of records for model building. As occurrence records were biased towards north-eastern Borneo, we investigated the efficacy of spatial filtering versus background manipulation to reduce overprediction or underprediction in specific areas.
 ResultsSpatial filtering minimized omission errors (false negatives) and commission errors (false positives). We recommend that when sample size is insufficient to allow spatial filtering, manipulation of the background dataset is preferable to not correcting for sampling bias, although predictions were comparatively weak and commission errors increased.
 Main ConclusionsWe conclude that a substantial improvement in the quality of model predictions can be achieved if uneven sampling effort is taken into account, thereby improving the efficacy of species conservation planning.
KW  - Borneo
KW  - carnivora
KW  - conservation planning
KW  - ecological niche modelling
KW  - maximum entropy (MaxEnt)
KW  - sampling bias
KW  - Southeast Asia
KW  - species distribution modelling
KW  - viverridae
Y1  - 2013
U6  - https://doi.org/10.1111/ddi.12096
SN  - 1366-9516
SN  - 1472-4642
VL  - 19
IS  - 11
SP  - 1366
EP  - 1379
PB  - Wiley-Blackwell
CY  - Hoboken
ER  -