TY  - JOUR
A1  - Rudner, Michael
A1  - Schröder-Esselbach, Boris
A1  - Biedermann, Robert
A1  - Müller, Mark
T1  - Habitat modelling in GIMOLUS - webGIS-based e-learning modules using logistic regression to assess species- habitat relationships
Y1  - 2003
UR  - http://brandenburg.geoecology.uni-potsdam.de/users/schroeder/download/publications/ rudner_schroeder_biedermann_mueller_agit2003.pdf
ER  - 
TY  - JOUR
A1  - Binzenhöfer, Birgit
A1  - Schroder, B.
A1  - Strauss, B.
A1  - Biedermann, Robert
A1  - Settele, Josef
T1  - Habitat models and habitat connectivity analysis for butterflies and burnet moths : the example of Zygaena carniolica and Coenonympha arcania
N2  - In this paper, habitat models were used to predict potential habitat for endangered species, which is an important question in landscape and conservation planning. Based on logistic regression, we developed habitat distribution models for the burnet moth Zygaena carniolica and the nymphalid butterfly Coenonympha arcania in Northern Bavaria, Germany. The relation between adult occurrence and habitat parameters, including the influence of landscape context, was analyzed on, 118 sites. Habitat connectivity analyses were carried out on the basis of (1) habitat suitability maps generated from these models and (2) dispersal data from mark recapture studies. Our results showed that (1) the presence of the burnet depended mainly on the presence of nectar plants and of nutrient-poor dry grasslands in direct vicinity, that of the nymphalid on larger areas of extensively used dry grasslands within 100 m vicinity in combination with small patches of higher shrubs and bushes. (2) Internal as well as external validation indicated the robustness and general applicability of the models. Transferability in time and space indicated their high potential relevance for applications in nature conservation, such as predicting possible effects of land use changes. (3) Habitat connectivity analyses revealed a high degree of habitat connectivity within the study area. Thus, we could show no effects of isolation or habitat size for both species. (c) 2005 Elsevier Ltd. All rights reserved
Y1  - 2005
ER  - 
TY  - JOUR
A1  - Pagel, Jörn
A1  - Fritzsch, Katrin
A1  - Biedermann, Robert
A1  - Schröder-Esselbach, Boris
T1  - Annual plants under cyclic disturbance regime : better understanding through model aggregation
N2  - In their application for conservation ecology, 'classical' analytical models and individual-based simulation models (IBMs) both entail their specific strengths and weaknesses, either in providing a detailed and realistic representation of processes or in regard to a comprehensive model analysis. This well-known dilemma may be resolved by the combination of both approaches when tackling certain problems of conservation ecology. Following this idea, we present the complementary use of both an IBM and a matrix population model in a case study on grassland conservation management. First, we develop a spatially explicit IBM to simulate the long-term response of the annual plant Thlaspi perfoliatum (Brassicaceae), claspleaf pennycress, to different management schemes (annual mowing vs. infrequent rototilling) based on field experiments. In order to complement the simulation results by further analyses, we aggregate the IBM to a spatially nonexplicit deterministic matrix population model. Within the periodic environment created by management regimes, population dynamics are described by periodic products of annual transition matrices. Such periodic matrix products provide a very conclusive framework to study the responses of species to different management return intervals. Thus, using tools of matrix model analysis (e.g., loop analysis), we can both identify dormancy within the age-structured seed bank as the pivotal strategy for persistence under cyclic disturbance regimes and reveal crucial thresholds in some less certain parameters. Results of matrix model analyses are therefore successfully tested by comparing their results to the respective IBM simulations. Their implications for an enhanced scientific basis for management decisions are discussed as well as some general benefits and limitations of the use of aggregating modeling approaches in conservation.
Y1  - 2008
UR  - 1960 = DOI: 10.1890/07-1305.1
SN  - 1051-0761
ER  -