TY  - JOUR
A1  - Palm, Juliane
A1  - van Schaik, N. Loes M. B.
A1  - Schröder-Esselbach, Boris
T1  - Modelling distribution patterns of anecic, epigeic and endogeic earthworms at catchment-scale in agro-ecosystems
JF  - Pedobiologia : international journal of soil biology
N2  - Species distribution models are useful for identifying driving environmental factors that determine earthworm distributions as well as for predicting earthworm distribution patterns and abundances at different scales. However, due to large efforts in data acquisition, studies on larger scales are rare and often focus on single species or earthworms in general. In this study, we use boosted regression tree models (BRTs) for predicting the distribution of the three functional earthworm types, i.e. anecics, endogeics and epigeics, in an agricultural area in Baden-Wurttemberg (Southwest Germany).
 First, we predicted presence and absence and later earthworm abundances, considering predictors depicting land management, topography, and soil conditions as well as biotic interaction by using the abundance of the other functional earthworm types. The final presence-absence models performed reasonably well, with explained deviances between 24 and 51% after crossvalidation. Models for abundances of anecics and endogeics were less successful, since the high small-scale variability and patchiness in earthworm abundance influenced the representativeness of the field measurements. This resulted in a significant model uncertainty, which is practically very difficult to overcome with earthworm sampling campaigns at the catchment scale.
 Results showed that management practices (i.e. disturbances), topography, soil conditions, and biotic interactions with other earthworm groups are the most relevant predictors for spatial distribution (incidence) patterns of all three functional groups. The response curves and contributions of predictors differ for the three functional earthworm types. Epigeics are also controlled by topographic features, endogeics by soil parameters.
KW  - Species distribution models
KW  - Earthworms
KW  - Soil hydrology
KW  - Boosted regression trees (BRT)
KW  - Distribution patterns
KW  - Biotic interactions
Y1  - 2013
U6  - https://doi.org/10.1016/j.pedobi.2012.08.007
SN  - 0031-4056
VL  - 56
IS  - 1
SP  - 23
EP  - 31
PB  - Elsevier
CY  - Jena
ER  - 
TY  - JOUR
A1  - Brandt, Karoline
A1  - Glemnitz, M.
A1  - Schroeder, Boris
T1  - The impact of crop parameters and surrounding habitats on different pollinator group abundance on agricultural fields
JF  - Agriculture, ecosystems & environment : an international journal for scientific research on the relationship of agriculture and food production to the biosphere
N2  - Pollination is a key ecosystem service. Pollinators, however, are in decline and their service is increasingly threatened. The decline is driven by several factors, most of which are related to agricultural management. However, the complexity of the landscape system, consisting of both cropped and non cropped areas, makes it difficult to address or even quantify the role of farming practices in pollinator abundance. Therefore, the aim of this paper is to improve our understanding of the relationships between pollinator abundance and their habitat use. We intend to identify and quantify the driving environmental factors that determine pollinator abundance in agricultural landscapes on the crop and landscape scale. These information helps us to design algorithms that can be used as a basis for predicting pollinator abundance on agricultural fields. To integrate varying environmental conditions data sampling was performed on farms in three different regions in Germany. Pollinators were classified into different groups with three aggregation levels. We observed crop parameters as well as landscape parameters in the areas surrounding fields in addition to temporal aspects. Generalized linear models (GLMs) were then calculated. Our results showed that both crop and landscape parameters affect pollinator abundance on agricultural fields. However, the explanatory power of the included parameters varied strongly among the particular pollinator groups and between aggregation levels. Furthermore, differentiation between species groups improves the explanatory power compared to models that are more aggregated. We also found that the temporal match between main activity periods of the particular pollinator groups and resource supply by the crop species is a key factor when analysing pollinator abundance. In conclusion, we demonstrated that the assessment and support of pollination services should be carried out with regard to individual pollinator groups. When studying pollinator abundance, the crop as well as the landscape scale should be addressed. A range of different habitat requirements and different activity periods of the pollinator groups must be covered to maintain pollination services, and therefore both diverse landscapes and diverse crop rotations are of crucial importance. (C) 2017 Elsevier B.V. All rights reserved.
KW  - Species distribution models
KW  - Generalized linear models (GLMs)
KW  - Environmental drivers
KW  - Habitat suitability
KW  - Pollinator conservation
KW  - Wild bees
Y1  - 2017
U6  - https://doi.org/10.1016/j.agee.2017.03.009
SN  - 0167-8809
SN  - 1873-2305
VL  - 243
SP  - 55
EP  - 66
PB  - Elsevier
CY  - Amsterdam
ER  -