Christian Wilhelm Mohr

Research Scientist

(+47) 971 30 994
christian.mohr@nibio.no

Place
Ås H8

Visiting address
Høgskoleveien 8, 1433 Ås

Biography

Researcher at the Department of Forest and Climate.

Main role as coordinator for the accounting and reporting of the Norwegian national inventory of greenhouse gasses for the LULUCF-sector (Land Use, Land-Use Change and Forestry) under the United Nations Framework Convention on Climate Change and the Kyoto Protocol. In addition I work on projects related to LULUCF. 

Area of expertise: LULUCF, climate change, biogeochemistry (processes and cycles), environmental chemistry (soil and water), analytical chemistry, and multivariate statistics.

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Abstract

Denne publikasjonen presenterer en ny metodikk for estimering av endringer i lageret av jordkarbon som følge av arealbruksendringer på mineraljord. Metodikken er utviklet for bruk i den nasjonale rapporteringen av arealbrukssektoren under FNs klimakonvensjon. Metodikken baserer seg på den enkleste tilnærming i følge IPCC sine retningslinjer, en såkaldt Tier 1. Tier 1 metodikken baseres i stor grad på standardverdier fra retningslinjene (IPCC default), men trenger en kopling mot nasjonal arealinformasjon. Denne koplingen beskrives i rapporten. Metodikken tar utgangspunkt i standardverdier for lageret av jordkarbon (SOCREF). Disse er basert på jordtype-grupperinger og klimasone som stammer fra en verdensdekkende jorddatabase. Endringer i jordkarbon etter arealbruksendring estimeres ved hjelp av SOCREF i kombinasjon med et sett faktorer (også standardverdier) som er arealbruksavhengige. Metodikken legger til grunn at endringer i jordkarbon skjer lineært over 20 år (ifølge 2006 IPCC Guidelines). Grunnleggende informasjon for å kunne kople standardverdier mot arealer på en konsistent måte er stort sett manglende for Norge på nasjonal skala. Rapporten gir derfor detaljert informasjon om de datakildene som har vært brukt til å kunne definere hvilke standariserte verdier som tilhører et bestemt areal i overgang....

To document

Abstract

Climate change in the Nordic countries is projected to lead to both wetter and warmer seasons. This, in combination with associated vegetation changes and increased animal migration, increases the potential incidence of tick-borne diseases (TBD) where already occurring, and emergence in new places. At the same time, vegetation and animal management influence tick habitat and transmission risks. In this paper, we review the literature on Ixodes ricinus, the primary vector for TBD. Current and projected distribution changes and associated disease transmission risks are related to climate constraints and climate change, and this risk is discussed in the specific context of reindeer management. Our results indicate that climatic limitations for vectors and hosts, and environmental and societal/institutional conditions will have a significant role in determining the spreading of climate-sensitive infections (CSIs) under a changing climate. Management emerges as an important regulatory “tool” for tick and/or risk for disease transfer. In particular, shrub encroachment, and pasture and animal management, are important. The results underscore the need to take a seasonal view of TBD risks, such as (1) grazing and migratory (host) animal presence, (2) tick (vector) activity, (3) climate and vegetation, and (4) land and animal management, which all have seasonal cycles that may or may not coincide with different consequences of climate change on CSI migration. We conclude that risk management must be coordinated across the regions, and with other land-use management plans related to climate mitigation or food production to understand and address the changes in CSI risks.

To document

Abstract

The climate is an aggregate of the mean and variability of a range of meteorological variables, notably temperature (T) and precipitation (P). While the impacts of an increase in global mean surface temperature (GMST) are commonly quantified through changes in regional means and extreme value distributions, a concurrent shift in the shapes of the distributions of daily T and P is arguably equally important. Here, we employ a 30‐member ensemble of coupled climate model simulations (CESM1 LENS) to consistently quantify the changes of regionally and seasonally resolved probability density functions of daily T and P as function of GMST. Focusing on aggregate regions covering both populated and rural zones, we identify large regional and seasonal diversity in the probability density functions and quantify where CESM1 projects the most noticeable changes compared to the preindustrial era. As global temperature increases, Europe and the United States are projected to see a rapid reduction in wintertime cold days, and East Asia to experience a strong increase in intense summertime precipitation. Southern Africa may see a shift to a more intrinsically variable climate but with little change in mean properties. The sensitivities of Arctic and African intrinsic variability to GMST are found to be particularly high. Our results highlight the need to further quantify future changes to daily temperature and precipitation distributions as an integral part of preparing for the societal and ecological impacts of climate change and show how large ensemble simulations can be a useful tool for such research.