Work in progress
2018 |
Stefano, Andrea De; Jacobson, Michael G Soil carbon sequestration in agroforestry systems: a meta-analysis Journal Article Agroforestry systems, 92 (2), pp. 285–299, 2018. @article{de2018soil, title = {Soil carbon sequestration in agroforestry systems: a meta-analysis}, author = {Andrea De Stefano and Michael G Jacobson}, url = {https://link.springer.com/article/10.1007/s10457-017-0147-9}, year = {2018}, date = {2018-01-01}, journal = {Agroforestry systems}, volume = {92}, number = {2}, pages = {285--299}, publisher = {Springer}, abstract = {Agroforestry systems may play an important role in mitigating climate change, having the ability to sequester atmospheric carbon dioxide (CO2) in plant parts and soil. A meta-analysis was carried out to investigate changes in soil organic carbon (SOC) stocks at 0–15, 0–30, 0–60, 0–100, and 0 ≥ 100 cm, after land conversion to agroforestry. Data was collected from 53 published studies. Results revealed a significant decrease in SOC stocks of 26 and 24% in the land-use change from forest to agroforestry at 0–15 and 0–30 cm respectively. The transition from agriculture to agroforestry significantly increased SOC stock of 26, 40, and 34% at 0–15, 0–30, and 0–100 cm respectively. The conversion from pasture/grassland to agroforestry produced significant SOC stock increases at 0–30 cm (9%) and 0–30 cm (10%). Switching from uncultivated/other land-uses to agroforestry increased SOC by 25% at 0–30 cm, while a decrease was observed at 0–60 cm (23%). Among agroforestry systems, significant SOC stocks increases were reported at various soil horizons and depths in the land-use change from agriculture to agrisilviculture and to silvopasture, pasture/grassland to agrosilvopastoral systems, forest to silvopasture, forest plantation to silvopasture, and uncultivated/other to agrisilviculture. On the other hand, significant decreases were observed in the transition from forest to agrisilviculture, agrosilvopastoral and silvopasture systems, and uncultivated/other to silvopasture. Overall, SOC stocks increased when land-use changed from less complex systems, such as agricultural systems. However, heterogeneity, inconsistencies in study design, lack of standardized sampling procedures, failure to report variance estimators, and lack of important explanatory variables, may have influenced the outcomes.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Agroforestry systems may play an important role in mitigating climate change, having the ability to sequester atmospheric carbon dioxide (CO2) in plant parts and soil. A meta-analysis was carried out to investigate changes in soil organic carbon (SOC) stocks at 0–15, 0–30, 0–60, 0–100, and 0 ≥ 100 cm, after land conversion to agroforestry. Data was collected from 53 published studies. Results revealed a significant decrease in SOC stocks of 26 and 24% in the land-use change from forest to agroforestry at 0–15 and 0–30 cm respectively. The transition from agriculture to agroforestry significantly increased SOC stock of 26, 40, and 34% at 0–15, 0–30, and 0–100 cm respectively. The conversion from pasture/grassland to agroforestry produced significant SOC stock increases at 0–30 cm (9%) and 0–30 cm (10%). Switching from uncultivated/other land-uses to agroforestry increased SOC by 25% at 0–30 cm, while a decrease was observed at 0–60 cm (23%). Among agroforestry systems, significant SOC stocks increases were reported at various soil horizons and depths in the land-use change from agriculture to agrisilviculture and to silvopasture, pasture/grassland to agrosilvopastoral systems, forest to silvopasture, forest plantation to silvopasture, and uncultivated/other to agrisilviculture. On the other hand, significant decreases were observed in the transition from forest to agrisilviculture, agrosilvopastoral and silvopasture systems, and uncultivated/other to silvopasture. Overall, SOC stocks increased when land-use changed from less complex systems, such as agricultural systems. However, heterogeneity, inconsistencies in study design, lack of standardized sampling procedures, failure to report variance estimators, and lack of important explanatory variables, may have influenced the outcomes. |
2014 |
Paaijmans, Krijn P; Blanford, Justine I; Crane, Robert G; Mann, Michael E; Ning, Liang; Schreiber, Kathleen V; Thomas, Matthew B Downscaling reveals diverse effects of anthropogenic climate warming on the potential for local environments to support malaria transmission Journal Article Climatic Change, 125 (3), pp. 479–488, 2014, ISSN: 1573-1480. @article{Paaijmans2014, title = {Downscaling reveals diverse effects of anthropogenic climate warming on the potential for local environments to support malaria transmission}, author = {Krijn P Paaijmans and Justine I Blanford and Robert G Crane and Michael E Mann and Liang Ning and Kathleen V Schreiber and Matthew B Thomas}, url = {https://link.springer.com/article/10.1007/s10584-014-1172-6}, doi = {10.1007/s10584-014-1172-6}, issn = {1573-1480}, year = {2014}, date = {2014-08-01}, journal = {Climatic Change}, volume = {125}, number = {3}, pages = {479--488}, abstract = {The potential impact of climate warming on patterns of malaria transmission has been the subject of keen scientific and policy debate. Standard climate models (GCMs) characterize climate change at relatively coarse spatial and temporal scales. However, malaria parasites and the mosquito vectors respond to diurnal variations in conditions at very local scales. Here we bridge this gap by downscaling a series of GCMs to provide high-resolution temperature data for four different sites and show that although outputs from both the GCM and the downscaled models predict diverse but qualitatively similar effects of warming on the potential for adult mosquitoes to transmit malaria, the predicted magnitude of change differs markedly between the different model approaches. Raw GCM model outputs underestimate the effects of climate warming at both hot (3-fold) and cold (8--12 fold) extremes, and overestimate (3-fold) the change under intermediate conditions. Thus, downscaling could add important insights to the standard application of coarse-scale GCMs for biophysical processes driven strongly by local microclimatic conditions.}, keywords = {}, pubstate = {published}, tppubtype = {article} } The potential impact of climate warming on patterns of malaria transmission has been the subject of keen scientific and policy debate. Standard climate models (GCMs) characterize climate change at relatively coarse spatial and temporal scales. However, malaria parasites and the mosquito vectors respond to diurnal variations in conditions at very local scales. Here we bridge this gap by downscaling a series of GCMs to provide high-resolution temperature data for four different sites and show that although outputs from both the GCM and the downscaled models predict diverse but qualitatively similar effects of warming on the potential for adult mosquitoes to transmit malaria, the predicted magnitude of change differs markedly between the different model approaches. Raw GCM model outputs underestimate the effects of climate warming at both hot (3-fold) and cold (8--12 fold) extremes, and overestimate (3-fold) the change under intermediate conditions. Thus, downscaling could add important insights to the standard application of coarse-scale GCMs for biophysical processes driven strongly by local microclimatic conditions. |
2011 |
Bazilian, Morgan; Rogner, Holger; Howells, Mark; Hermann, Sebastian; Arent, Douglas; Gielen, Dolf; Steduto, Pasquale; Mueller, Alexander; Komor, Paul; Tol, Richard SJ; others, Considering the energy, water and food nexus: Towards an integrated modelling approach Journal Article Energy Policy, 39 (12), pp. 7896–7906, 2011. @article{bazilian2011considering, title = {Considering the energy, water and food nexus: Towards an integrated modelling approach}, author = {Morgan Bazilian and Holger Rogner and Mark Howells and Sebastian Hermann and Douglas Arent and Dolf Gielen and Pasquale Steduto and Alexander Mueller and Paul Komor and Richard SJ Tol and others}, url = {https://www.sciencedirect.com/science/article/pii/S0301421511007282}, doi = {10.1016/j.enpol.2011.09.039}, year = {2011}, date = {2011-01-01}, journal = {Energy Policy}, volume = {39}, number = {12}, pages = {7896--7906}, publisher = {Elsevier}, abstract = {The areas of energy, water and food policy have numerous interwoven concerns ranging from ensuring access to services, to environmental impacts to price volatility. These issues manifest in very different ways in each of the three “spheres”, but often the impacts are closely related. Identifying these interrelationships a priori is of great importance to help target synergies and avoid potential tensions. Systems thinking is required to address such a wide swath of possible topics. This paper briefly describes some of the linkages at a high-level of aggregation – primarily from a developing country perspective – and via case studies, to arrive at some promising directions for addressing the nexus. To that end, we also present the attributes of a modelling framework that specifically addresses the nexus, and can thus serve to inform more effective national policies and regulations. While environmental issues are normally the ‘cohesive principle’ from which the three areas are considered jointly, the enormous inequalities arising from a lack of access suggest that economic and security-related issues may be stronger motivators of change. Finally, consideration of the complex interactions will require new institutional capacity both in industrialised and developing countries.}, keywords = {}, pubstate = {published}, tppubtype = {article} } The areas of energy, water and food policy have numerous interwoven concerns ranging from ensuring access to services, to environmental impacts to price volatility. These issues manifest in very different ways in each of the three “spheres”, but often the impacts are closely related. Identifying these interrelationships a priori is of great importance to help target synergies and avoid potential tensions. Systems thinking is required to address such a wide swath of possible topics. This paper briefly describes some of the linkages at a high-level of aggregation – primarily from a developing country perspective – and via case studies, to arrive at some promising directions for addressing the nexus. To that end, we also present the attributes of a modelling framework that specifically addresses the nexus, and can thus serve to inform more effective national policies and regulations. While environmental issues are normally the ‘cohesive principle’ from which the three areas are considered jointly, the enormous inequalities arising from a lack of access suggest that economic and security-related issues may be stronger motivators of change. Finally, consideration of the complex interactions will require new institutional capacity both in industrialised and developing countries. |
2006 |
Hewitson, Bruce C; Crane, Robert G Consensus between GCM climate change projections with empirical downscaling: precipitation downscaling over South Africa Journal Article International Journal of Climatology, 26 (10), pp. 1315–1337, 2006. @article{doi:10.1002/joc.1314, title = {Consensus between GCM climate change projections with empirical downscaling: precipitation downscaling over South Africa}, author = {Bruce C Hewitson and Robert G Crane}, url = {https://rmets.onlinelibrary.wiley.com/doi/abs/10.1002/joc.1314}, doi = {10.1002/joc.1314}, year = {2006}, date = {2006-03-21}, journal = {International Journal of Climatology}, volume = {26}, number = {10}, pages = {1315--1337}, abstract = {Abstract This paper discusses issues that surround the development of empirical downscaling techniques as context for presenting a new approach based on self-organizing maps (SOMs). The technique is applied to the downscaling of daily precipitation over South Africa. SOMs are used to characterize the state of the atmosphere on a localized domain surrounding each target location on the basis of NCEP 6-hourly reanalysis data from 1979 to 2002, and using surface and 700-hPa u and v wind vectors, specific and relative humidities, and surface temperature. Each unique atmospheric state is associated with an observed precipitation probability density function (PDF). Future climate states are derived from three global climate models (GCMs): HadAM3, ECHAM4.5, CSIRO Mk2. In each case, the GCM data are mapped to the NCEP SOMs for each target location and a precipitation value is drawn at random from the associated precipitation PDF. The downscaling approach combines the advantages of a direct transfer function and a stochastic weather generator, and provides an indication of the strength of the regional versus stochastic forcing, as well as a measure of stationarity in the atmosphere–precipitation relationship. The methodology is applied to South Africa. The downscaling reveals a similarity in the projected climate change between the models. Each GCM projects similar changes in atmospheric state and they converge on a downscaled solution that points to increased summer rainfall in the interior and the eastern part of the country, and a decrease in winter rainfall in the Western Cape. The actual GCM precipitation projections from the three models show large areas of intermodel disagreement, suggesting that the model differences may be due to their precipitation parameterization schemes, rather than to basic disagreements in their projections of the changing atmospheric state over South Africa. Copyright © 2006 Royal Meteorological Society.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Abstract This paper discusses issues that surround the development of empirical downscaling techniques as context for presenting a new approach based on self-organizing maps (SOMs). The technique is applied to the downscaling of daily precipitation over South Africa. SOMs are used to characterize the state of the atmosphere on a localized domain surrounding each target location on the basis of NCEP 6-hourly reanalysis data from 1979 to 2002, and using surface and 700-hPa u and v wind vectors, specific and relative humidities, and surface temperature. Each unique atmospheric state is associated with an observed precipitation probability density function (PDF). Future climate states are derived from three global climate models (GCMs): HadAM3, ECHAM4.5, CSIRO Mk2. In each case, the GCM data are mapped to the NCEP SOMs for each target location and a precipitation value is drawn at random from the associated precipitation PDF. The downscaling approach combines the advantages of a direct transfer function and a stochastic weather generator, and provides an indication of the strength of the regional versus stochastic forcing, as well as a measure of stationarity in the atmosphere–precipitation relationship. The methodology is applied to South Africa. The downscaling reveals a similarity in the projected climate change between the models. Each GCM projects similar changes in atmospheric state and they converge on a downscaled solution that points to increased summer rainfall in the interior and the eastern part of the country, and a decrease in winter rainfall in the Western Cape. The actual GCM precipitation projections from the three models show large areas of intermodel disagreement, suggesting that the model differences may be due to their precipitation parameterization schemes, rather than to basic disagreements in their projections of the changing atmospheric state over South Africa. Copyright © 2006 Royal Meteorological Society. |