ORCID Profile
0000-0003-4607-9204
Current Organisation
Universidad del Rosario
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Publisher: Copernicus GmbH
Date: 20-01-2020
DOI: 10.5194/EGUSPHERE-EGU23-12604
Abstract: Fire-enabled dynamic global vegetation models (DGVMs) can be used to study how fire activity responds to its main drivers, including climate/weather, vegetation and human activities, at coarse spatial scales. Such models can also be used to examine the effects of fire on vegetation, and, when embedded in Earth system models, investigate the feedback of fire on the climate system. Thus they are valuable tools for studying wildfires. Accordingly, the Fire Model Intercomparison Project (FireMIP) was established to evaluate and utilise these models using consistent protocols.Here we present the second round of FireMIP simulations to focus historic wildfire drivers (1901 to present). A six-member ensemble of simulations from fire-enabled DGVMs was compared to remotely-sensed burnt area observations and to the previous round of historical FireMIP simulations. We found that the model skill when simulating spatial patterns of burnt area shows modest improvements compared to the previous FireMIP round, and that the simulations mostly reproduce the decreasing trend in global burnt area found over the last two decades. However, whilst the broad global patterns are reasonable, there are considerable discrepancies with regards to regional agreement and timing of burnt area. Furthermore, the models show erging trends in the pre-satellite era.To investigate further and inform future model development, we explored the residuals between simulated burnt area from the FireMIP models and remotely-sensed burnt area as a function of climate, vegetation, anthropogenic and topographic variables using generalised additive models (GAMs). We found some common responses across the models, with many over-predicting fire activity in arid/low productivity areas and all models under-predicting at low road density. However, with respect to other variables, such as wind speed and cropland fraction, the models residuals showed ergent responses. It is anticipated that these results should aid further development of global fire models in terms of driving variables, process representations and model structure.
Publisher: Oxford University Press (OUP)
Date: 07-2022
DOI: 10.1093/PNASNEXUS/PGAC115
Abstract: Fire is an integral component of ecosystems globally and a tool that humans have harnessed for millennia. Altered fire regimes are a fundamental cause and consequence of global change, impacting people and the biophysical systems on which they depend. As part of the newly emerging Anthropocene, marked by human-caused climate change and radical changes to ecosystems, fire danger is increasing, and fires are having increasingly devastating impacts on human health, infrastructure, and ecosystem services. Increasing fire danger is a vexing problem that requires deep transdisciplinary, trans-sector, and inclusive partnerships to address. Here, we outline barriers and opportunities in the next generation of fire science and provide guidance for investment in future research. We synthesize insights needed to better address the long-standing challenges of innovation across disciplines to (i) promote coordinated research efforts (ii) embrace different ways of knowing and knowledge generation (iii) promote exploration of fundamental science (iv) capitalize on the “firehose” of data for societal benefit and (v) integrate human and natural systems into models across multiple scales. Fire science is thus at a critical transitional moment. We need to shift from observation and modeled representations of varying components of climate, people, vegetation, and fire to more integrative and predictive approaches that support pathways toward mitigating and adapting to our increasingly flammable world, including the utilization of fire for human safety and benefit. Only through overcoming institutional silos and accessing knowledge across erse communities can we effectively undertake research that improves outcomes in our more fiery future.
Publisher: CSIRO Publishing
Date: 2014
DOI: 10.1071/WF12052
Abstract: Fire risk assessment should take into account the most relevant components associated to fire occurrence. To estimate when and where the fire will produce undesired effects, we need to model both (a) fire ignition and propagation potential and (b) fire vulnerability. Following these ideas, a comprehensive fire risk assessment system is proposed in this paper, which makes extensive use of geographic information technologies to offer a spatially explicit evaluation of fire risk conditions. The paper first describes the conceptual model, then the methods to generate the different input variables, the approaches to merge those variables into synthetic risk indices and finally the validation of the outputs. The model has been applied at a national level for the whole Spanish Iberian territory at 1-km2 spatial resolution. Fire danger included human factors, lightning probability, fuel moisture content of both dead and live fuels and propagation potential. Fire vulnerability was assessed by analysing values-at-risk and landscape resilience. Each input variable included a particular accuracy assessment, whereas the synthetic indices were validated using the most recent fire statistics available. Significant relations (P 0.001) with fire occurrence were found for the main synthetic danger indices, particularly for those associated to fuel moisture content conditions.
Publisher: Copernicus GmbH
Date: 10-02-2020
Publisher: Cold Spring Harbor Laboratory
Date: 08-02-2023
DOI: 10.1101/2023.02.07.527551
Abstract: Human activity has fundamentally altered wildfire on Earth, creating serious consequences for human health, global bio ersity, and climate change. However, it remains difficult to predict fire interactions with land use, management, and climate change, representing a serious knowledge gap and vulnerability. We used expert assessment to combine opinions about past and future fire regimes from 98 wildfire researchers. We asked for quantitative and qualitative assessments of the frequency, type, and implications of fire regime change from the beginning of the Holocene through the year 2300. Respondents indicated that direct human activity was already influencing wildfires locally since at least ~ 12,000 years BP, though natural climate variability remained the dominant driver of fire regime until around 5000 years BP. Responses showed a ten-fold increase in the rate of wildfire regime change during the last 250 years compared with the rest of the Holocene, corresponding first with the intensification and extensification of land use and later with anthropogenic climate change. Looking to the future, fire regimes were predicted to intensify, with increases in fire frequency, severity, and/or size in all biomes except grassland ecosystems. Fire regime showed quite different climate sensitivities across biomes, but the likelihood of fire regime change increased with higher greenhouse gas emission scenarios for all biomes. Bio ersity, carbon storage, and other ecosystem services were predicted to decrease for most biomes under higher emission scenarios. We present recommendations for adaptation and mitigation under emerging fire regimes, concluding that management options are seriously constrained under higher emission scenarios.
Publisher: Copernicus GmbH
Date: 10-02-2020
DOI: 10.5194/BG-2019-491
Abstract: Abstract. The length of time that carbon remains in forest biomass is one of the largest uncertainties in the global carbon cycle, with both recent-historical baselines and future responses to environmental change poorly constrained by available observations. In the absence of large-scale observations, models tend to fall back on simplified assumptions of the turnover rates of biomass and soil carbon pools to make global assessments. In this study, the biomass carbon turnover times calculated by an ensemble of contemporary terrestrial biosphere models (TBMs) are analysed to assess their current capability to accurately estimate biomass carbon turnover times in forests and how these times are anticipated to change in the future. Modelled baseline 1985–2014 global forest biomass turnover times vary from 12.2 to 23.5 years between models. TBM differences in phenological processes, which control allocation to and turnover rate of leaves and fine roots, are as important as tree mortality with regard to explaining the variation in total turnover among TBMs. The different governing mechanisms exhibited by each TBM result in a wide range of plausible turnover time projections for the end of the century. Based on these simulations, it is not possible to draw robust conclusions regarding likely future changes in turnover time for different regions. Both spatial and temporal uncertainty in turnover time are strongly linked to model assumptions concerning plant functional type distributions and their controls. Twelve model-based hypotheses are identified, along with recommendations for pragmatic steps to test them using existing and novel observations, which would help to reduce both spatial and temporal uncertainty in turnover time. Efforts to resolve uncertainty in turnover time will need to address both mortality and establishment components of forest demography, as well as key drivers of demography such as allocation of carbon to woody versus non-woody biomass growth.
Publisher: Elsevier BV
Date: 12-2013
Publisher: Copernicus GmbH
Date: 15-05-2023
DOI: 10.5194/EGUSPHERE-EGU23-14756
Abstract: Recent long and intensive wildfire seasons in many regions have highlighted the urgency to understand the shift in worldwide fire regimes, raising the question if human induced climate change has played a role therein. However, attributing changes in fire to anthropogenic climate change is difficult, since possible signals are confounded by multiple drivers including fire weather, fuel availability and sources of ignition. Therefore, fire indices or in idual input variables are often used as proxies. There have been some attempts to model drivers of recent trends in fire, though assessment of overall anthropogenic climate change is still lacking. Recent integration of fire models into ISIMIP now allow us to perform a fire impact attribution analysis using multiple coupled fire-vegetation models. Here, we combine both ISIMIP factual and counterfactual simulations with remote sensed observations to understand how burnt area has changed over the historical period due to a changing climate.
Publisher: Copernicus GmbH
Date: 08-01-2020
Publisher: Copernicus GmbH
Date: 17-07-2020
Abstract: Abstract. Global fire-vegetation models are widely used to assess impacts of environmental change on fire regimes and the carbon cycle and to infer relationships between climate, land use and fire. However, differences in model structure and parameterizations, in both the vegetation and fire components of these models, could influence overall model performance, and to date there has been limited evaluation of how well different models represent various aspects of fire regimes. The Fire Model Intercomparison Project (FireMIP) is coordinating the evaluation of state-of-the-art global fire models, in order to improve projections of fire characteristics and fire impacts on ecosystems and human societies in the context of global environmental change. Here we perform a systematic evaluation of historical simulations made by nine FireMIP models to quantify their ability to reproduce a range of fire and vegetation benchmarks. The FireMIP models simulate a wide range in global annual total burnt area (39–536 Mha) and global annual fire carbon emission (0.91–4.75 Pg C yr−1) for modern conditions (2002–2012), but most of the range in burnt area is within observational uncertainty (345–468 Mha). Benchmarking scores indicate that seven out of nine FireMIP models are able to represent the spatial pattern in burnt area. The models also reproduce the seasonality in burnt area reasonably well but struggle to simulate fire season length and are largely unable to represent interannual variations in burnt area. However, models that represent cropland fires see improved simulation of fire seasonality in the Northern Hemisphere. The three FireMIP models which explicitly simulate in idual fires are able to reproduce the spatial pattern in number of fires, but fire sizes are too small in key regions, and this results in an underestimation of burnt area. The correct representation of spatial and seasonal patterns in vegetation appears to correlate with a better representation of burnt area. The two older fire models included in the FireMIP ensemble (LPJ–GUESS–GlobFIRM, MC2) clearly perform less well globally than other models, but it is difficult to distinguish between the remaining ensemble members some of these models are better at representing certain aspects of the fire regime none clearly outperforms all other models across the full range of variables assessed.
Publisher: Copernicus GmbH
Date: 05-08-2020
Abstract: Abstract. The length of time that carbon remains in forest biomass is one of the largest uncertainties in the global carbon cycle, with both recent historical baselines and future responses to environmental change poorly constrained by available observations. In the absence of large-scale observations, models used for global assessments tend to fall back on simplified assumptions of the turnover rates of biomass and soil carbon pools. In this study, the biomass carbon turnover times calculated by an ensemble of contemporary terrestrial biosphere models (TBMs) are analysed to assess their current capability to accurately estimate biomass carbon turnover times in forests and how these times are anticipated to change in the future. Modelled baseline 1985–2014 global average forest biomass turnover times vary from 12.2 to 23.5 years between TBMs. TBM differences in phenological processes, which control allocation to, and turnover rate of, leaves and fine roots, are as important as tree mortality with regard to explaining the variation in total turnover among TBMs. The different governing mechanisms exhibited by each TBM result in a wide range of plausible turnover time projections for the end of the century. Based on these simulations, it is not possible to draw robust conclusions regarding likely future changes in turnover time, and thus biomass change, for different regions. Both spatial and temporal uncertainty in turnover time are strongly linked to model assumptions concerning plant functional type distributions and their controls. Thirteen model-based hypotheses of controls on turnover time are identified, along with recommendations for pragmatic steps to test them using existing and novel observations. Efforts to resolve uncertainty in turnover time, and thus its impacts on the future evolution of biomass carbon stocks across the world's forests, will need to address both mortality and establishment components of forest demography, as well as allocation of carbon to woody versus non-woody biomass growth.
Publisher: Copernicus GmbH
Date: 08-01-2020
DOI: 10.5194/GMD-2019-261
Abstract: Abstract. Global fire-vegetation models are widely used to assess impacts of environmental change on fire regimes and the carbon cycle, and to infer relationships between climate, land use, and fire. However, differences in model structure and parameterizations, in both the vegetation and fire components of these models, could influence overall model performance, and to date there has been limited evaluation of how well different models represent various aspects of fire regimes. The Fire Model Intercomparison Project (FireMIP) is coordinating the evaluation of state-of-the-art global fire models, with the aim of improving projections of fire regime characteristic and fire impacts on ecosystems and human societies under the context of global environmental change. Here we perform a systematic evaluation of historical simulations made by nine FireMIP models in order to quantify their ability to reproduce a range of fire and vegetation benchmarks. The FireMIP models simulate a wide range in global annual total burnt area (39–536 Mha), and global annual fire carbon emission (0.91–4.75 Pg C a−1) for modern conditions (2002–2012), but most of the range in burnt area is within observational uncertainty (345–468 Mha). Benchmarking scores indicate that seven out of nine FireMIP models are able to represent the spatial pattern in burnt area. The models also reproduce the seasonality in burnt area reasonably well but struggle to simulate fire season length and are largely unable to represent inter-annual variations in burnt area. However, models that represent cropland fires see improved simulation of fire seasonality in the northern hemisphere. The three FireMIP models which explicitly simulate in idual fires are able to reproduce the spatial pattern in number of fires, but fire sizes are too small in key regions and this results in an underestimation of burnt area. The correct representation of spatial and seasonal patterns in vegetation appears to correlate with a better representation of burnt area. While some FireMIP models are better at representing certain aspects of the fire regime, no model clearly outperforms all other models across the full range of variables assessed.
No related grants have been discovered for Stijn Hantson.