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A general ecophysiological framework for modelling the impact of pests and pathogens on forest ecosystems.

ABSTRACT: Forest insects and pathogens (FIPs) have enormous impacts on community dynamics, carbon storage and ecosystem services, however, ecosystem modelling of FIPs is limited due to their variability in severity and extent. We present a general framework for modelling FIP disturbances through their impacts on tree ecophysiology. Five pathways are identified as the basis for functional groupings: increases in leaf, stem and root turnover, and reductions in phloem and xylem transport. A simple ecophysiological model was used to explore the sensitivity of forest growth, mortality and ecosystem fluxes to varying outbreak severity. Across all pathways, low infection was associated with growth reduction but limited mortality. Moderate infection led to individual tree mortality, whereas high levels led to stand-level die-offs delayed over multiple years. Delayed mortality is consistent with observations and critical for capturing biophysical, biogeochemical and successional responses. This framework enables novel predictions under present and future global change scenarios.

SUBMITTER: Dietze MC

PROVIDER: S-EPMC4257091 | biostudies-literature | 2014 Nov

REPOSITORIES: biostudies-literature

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A general ecophysiological framework for modelling the impact of pests and pathogens on forest ecosystems.

Dietze Michael C MC Matthes Jaclyn Hatala JH

Ecology letters 20140828 11

Forest insects and pathogens (FIPs) have enormous impacts on community dynamics, carbon storage and ecosystem services, however, ecosystem modelling of FIPs is limited due to their variability in severity and extent. We present a general framework for modelling FIP disturbances through their impacts on tree ecophysiology. Five pathways are identified as the basis for functional groupings: increases in leaf, stem and root turnover, and reductions in phloem and xylem transport. A simple ecophysiol ...[more]

PMID: 25168168

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Project description:Actinomycetia are known for their ability to produce a wide range of bioactive secondary metabolites having significant therapeutic importance. This study aimed to explore the potential of actinomycetia as a source of bioactive compounds with antimicrobial properties against multi-drug-resistant (MDR) clinical pathogens. A total of 65 actinomycetia were isolated from two unexplored forest ecosystems, namely the Pobitora Wildlife Sanctuary (PWS) and the Deepor Beel Wildlife Sanctuary (DBWS), located in the Indo-Burma mega-biodiversity hotspots of northeast India, out of which 19 isolates exhibited significant antimicrobial activity. 16S rRNA gene sequencing was used for the identification and phylogenetic analysis of the 19 potent actinomycetia isolates. The results reveal that the most dominant genus among the isolates was Streptomyces (84.21%), followed by rare actinomycetia genera such as Nocardia, Actinomadura, and Nonomuraea. Furthermore, seventeen of the isolates tested positive for at least one antibiotic biosynthetic gene, specifically type II polyketide synthase (PKS-II) and nonribosomal peptide synthetases (NRPSs). These genes are associated with the production of bioactive compounds with antimicrobial properties. Among the isolated strains, three actinomycetia strains, namely Streptomyces sp. PBR1, Streptomyces sp. PBR36, and Streptomyces sp. DBR11, demonstrated the most potent antimicrobial activity against seven test pathogens. This was determined through in vitro antimicrobial bioassays and the minimum inhibitory concentration (MIC) values of ethyl acetate extracts. Gas chromatography-mass spectrometry (GS-MS) and whole-genome sequencing (WGS) of the three strains revealed a diverse group of bioactive compounds and secondary metabolite biosynthetic gene clusters (smBGCs), respectively, indicating their high therapeutic potential. These findings highlight the potential of these microorganisms to serve as a valuable resource for the discovery and development of novel antibiotics and other therapeutics with high therapeutic potential.

Dataset Information

A general ecophysiological framework for modelling the impact of pests and pathogens on forest ecosystems.

Publications

A general ecophysiological framework for modelling the impact of pests and pathogens on forest ecosystems.

Similar Datasets

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