Impact of rainforest conversion: How prokaryotic communities respond to anthropogenic land use changes

Berkelmann, Dirk

dc.contributor.advisor	Daniel, Rolf Prof. Dr.
dc.contributor.author	Berkelmann, Dirk
dc.date.accessioned	2020-12-03T12:58:40Z
dc.date.available	2020-12-03T12:58:40Z
dc.date.issued	2020-12-03
dc.identifier.uri	http://hdl.handle.net/21.11130/00-1735-0000-0005-1510-1
dc.identifier.uri	http://dx.doi.org/10.53846/goediss-8348
dc.language.iso	eng	de
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject.ddc	570	de
dc.title	Impact of rainforest conversion: How prokaryotic communities respond to anthropogenic land use changes	de
dc.type	doctoralThesis	de
dc.contributor.referee	Daniel, Rolf Prof. Dr.
dc.date.examination	2020-06-09
dc.description.abstracteng	In this thesis, the impact of rainforest conversion to the managed land use systems jungle rubber, rubber plantation and oil palm plantation on structure and function of soil microbial communities was investigated. The active bacterial community (RNA-based) was investigated by 16S rRNA marker gene analysis and the entire community (DNAbased) by direct metagenome sequencing. Additionally, different management practices were tested for their influence on soilborne bacterial communities in oil palm and endophytic microbial communities in cacao plantations. The main focus of this work was to determine the effects of rainforest conversion to agricultural land use systems on soilborne microbial communities by using metagenomic approaches. The active bacterial community was analysed by 16S rRNA gene amplicon analysis in combination with the SILVA database. The communities in all soils were dominated by Proteobacteria, Acidobacteria and Actinobacteria. Compared to rainforest reference soils, the relative abundance of Acidobacteria and Actinobacteria increased in managed land use systems, while Proteobacteria decreased. Ordination analysis showed correlations between the detected communities and measured pH and C:N ratios in soil. The functional community was predicted from the taxonomic composition and showed a relative abundance decrease of nitrogen metabolism and chemotaxis related marker genes from rainforest to the converted land use systems. In the same experimental setup, direct metagenome sequence analysis was performed in order to further investigate microbial community compositions and their functional potential. Bacterial diversity did significantly decrease from rainforest to rubber systems and functional diversity decreased in both plantation systems. Fungal diversity decreased from rainforest to converted land use systems significantly, while fungal functional diversity increased. In rainforest soils, Rhizobiales and Burkholderiales were the most dominant bacterial taxa. Towards higher land use intensity from rainforest to plantations, the communities shifted to Acidobacteria-dominated communities. With increasing land use intensity from rainforest to plantations accompanied by higher soil pH values, denitrification and nitrogen fixation potential increased and mostly originated from members of the bacterial orders Burkholderiales and Rhizobiales. The potential for motility and interaction, in form of flagellar assembly, chemotaxis and secretion systems, decreased towards converted land use systems. Genes involved in flagellar assembly were mostly connected to Burkholderiales and chemotaxis related genes to Acidobacteria. This study showed that community composition and functional potential is significantly affected by rainforest conversion. These changes are strongly tied to effects of land use management practices such as fertilizer input and alteration of plant diversity on soil properties and influence taxa involved in nitrogen metabolism. In addition to rainforest conversion, effects of different management practices on bacterial communities in oil palm and cacao plantations were analysed. The reduced fertilizer and herbicide use in oil palm plantations was investigated based on RNA and DNA-driven 16S rRNA gene amplicon analysis. Although differences in bacterial diversity or community composition between treatments were not recorded, notable differences in abundance were detected between the entire and active community, emphasizing rather short-term effects. Effects of different management intensities on endophytic bacterial and fungal communities in cacao leaves were tested by employing marker gene amplicon analysis. No differences in bacterial community composition or diversity were detected between the treatments, whereas fungal diversity was positively affected by increased management intensity. The communities were more effected by the different sampling site locations than by the treatment This study provides new insights into the effects of rainforest conversion to managed land use systems on microbial community composition and functional potential in tropical soils. It furthermore connected taxonomic profiles with functional potential in this scenario for the first time. The results presented here contributed to close the knowledge gap between soil microbial community structure and functions that are affected by land use change-induced altered soil properties. However, DNA-based functional profiles might differ from gene activity in situ. Community activity could be further investigated by combining the results presented here with RNA-based metatranscriptomic analyses.	de
dc.contributor.coReferee	Hoppert, Michael PD Dr.
dc.contributor.thirdReferee	Stülke, Jörg Prof. Dr.
dc.contributor.thirdReferee	Polle, Andrea Prof. Dr.
dc.contributor.thirdReferee	Scheu, Stefan Prof. Dr.
dc.contributor.thirdReferee	Heimel, Kai Prof. Dr.
dc.subject.eng	Soil Microbiology	de
dc.subject.eng	Metagenomics	de
dc.subject.eng	Marker gene analysis	de
dc.subject.eng	Environmental Microbiology	de
dc.subject.eng	Oil palm soil	de
dc.subject.eng	Rainforest conversion	de
dc.identifier.urn	urn:nbn:de:gbv:7-21.11130/00-1735-0000-0005-1510-1-8
dc.affiliation.institute	Biologische Fakultät für Biologie und Psychologie	de
dc.subject.gokfull	Biologie (PPN619462639)	de
dc.identifier.ppn	1742023150