scholarly journals Simulating Peatland Methane Dynamics Coupled to a Mechanistic Model of Biogeochemistry, Hydrology, and Energy: Implications to Climate Change

10.5772/9815 ◽  
2010 ◽  
Author(s):  
Takeshi Ise ◽  
Allison Dunn ◽  
Steven Wofsy ◽  
Paul Moorcroft
Keyword(s):  
Climate Change ◽  
Mechanistic Model ◽  
Methane Dynamics

scholarly journals Simulating the Effects of Intensifying Silviculture on Desired Species Yields across a Broad Environmental Gradient

Forests ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 755
Author(s):  
Eric B. Searle ◽  
F. Wayne Bell ◽  
Guy R. Larocque ◽  
Mathieu Fortin ◽  
Jennifer Dacosta ◽  
...  
Keyword(s):  
Climate Change ◽  
Forest Management ◽  
Planning Process ◽  
Mechanistic Model ◽  
Natural Disturbance ◽  
Fine Tuning ◽  
Mechanistic Models ◽  
Paradigm Shifts ◽  
Ecological Processes ◽  
Forest Modelling

In the past two decades, forest management has undergone major paradigm shifts that are challenging the current forest modelling architecture. New silvicultural systems, guidelines for natural disturbance emulation, a desire to enhance structural complexity, major advances in successional theory, and climate change have all highlighted the limitations of current empirical models in covering this range of conditions. Mechanistic models, which focus on modelling underlying ecological processes rather than specific forest conditions, have the potential to meet these new paradigm shifts in a consistent framework, thereby streamlining the planning process. Here we use the NEBIE (a silvicultural intervention scale that classifies management intensities as natural, extensive, basic, intensive, and elite) plot network, from across Ontario, Canada, to examine the applicability of a mechanistic model, ZELIG-CFS (a version of the ZELIG tree growth model developed by the Canadian Forest Service), to simulate yields and species compositions. As silvicultural intensity increased, overall yield generally increased. Species compositions met the desired outcomes when specific silvicultural treatments were implemented and otherwise generally moved from more shade-intolerant to more shade-tolerant species through time. Our results indicated that a mechanistic model can simulate complex stands across a range of forest types and silvicultural systems while accounting for climate change. Finally, we highlight the need to improve the modelling of regeneration processes in ZELIG-CFS to better represent regeneration dynamics in plantations. While fine-tuning is needed, mechanistic models present an option to incorporate adaptive complexity into modelling forest management outcomes.

scholarly journals Modelling the impact of climate change on the distribution and abundance of tsetse in Northern Zimbabwe

2020 ◽  
Vol 13 (1) ◽  
Author(s):  
Joshua Longbottom ◽  
Cyril Caminade ◽  
Harry S. Gibson ◽  
Daniel J. Weiss ◽  
Steve Torr ◽  
...  
Keyword(s):  
Climate Change ◽  
Population Dynamics ◽  
Spatial Resolution ◽  
Air Temperature ◽  
Mechanistic Model ◽  
Tsetse Flies ◽  
Weather Station ◽  
Catch Data ◽  
Tsetse Population ◽  
The Impact

Abstract Background Climate change is predicted to impact the transmission dynamics of vector-borne diseases. Tsetse flies (Glossina) transmit species of Trypanosoma that cause human and animal African trypanosomiasis. A previous modelling study showed that temperature increases between 1990 and 2017 can explain the observed decline in abundance of tsetse at a single site in the Mana Pools National Park of Zimbabwe. Here, we apply a mechanistic model of tsetse population dynamics to predict how increases in temperature may have changed the distribution and relative abundance of Glossina pallidipes across northern Zimbabwe. Methods Local weather station temperature measurements were previously used to fit the mechanistic model to longitudinal G. pallidipes catch data. To extend the use of the model, we converted MODIS land surface temperature to air temperature, compared the converted temperatures with available weather station data to confirm they aligned, and then re-fitted the mechanistic model using G. pallidipes catch data and air temperature estimates. We projected this fitted model across northern Zimbabwe, using simulations at a 1 km × 1 km spatial resolution, between 2000 to 2016. Results We produced estimates of relative changes in G. pallidipes mortality, larviposition, emergence rates and abundance, for northern Zimbabwe. Our model predicts decreasing tsetse populations within low elevation areas in response to increasing temperature trends during 2000–2016. Conversely, we show that high elevation areas (> 1000 m above sea level), previously considered too cold to sustain tsetse, may now be climatically suitable. Conclusions To our knowledge, the results of this research represent the first regional-scale assessment of temperature related tsetse population dynamics, and the first high spatial-resolution estimates of this metric for northern Zimbabwe. Our results suggest that tsetse abundance may have declined across much of the Zambezi Valley in response to changing climatic conditions during the study period. Future research including empirical studies is planned to improve model accuracy and validate predictions for other field sites in Zimbabwe.

Multi-model projections of evaporation in a sub-tropical lake

2021 ◽  
Author(s):  
Sofia La Fuente ◽  
Iestyn Woolway ◽  
Eleanor Jennings ◽  
Gideon Gal ◽  
Georgiy Kirillin ◽  
...  
Keyword(s):  
Climate Change ◽  
Mechanistic Model ◽  
Lake Kinneret ◽  
Energy Budgets ◽  
Climate Change Scenarios ◽  
Evaporative Water ◽  
Historic Period ◽  
Future Projections ◽  
Lake Ecosystems ◽  
Lake Evaporation

<p>Evaporation of surface water is critical to the basic functioning of lakes. It directly and, in some cases, substantially modifies the hydrologic, chemical, and energy budgets, making evaporation one of the most important physical controls on lake ecosystems. Predicting lake evaporation response to climate change is, therefore, of paramount importance. Most studies that simulate climate change impacts on lake evaporation have utilised only a single mechanistic model. Whilst such studies have merit, the advantage of applying multiple, independently developed models (i.e., an ensemble approach), is that some of the inherent uncertainties in the individual lake models due to, for example, different model structures, can be reduced thus enabling increased robustness of historic and future projections. In this study, we present results from the Inter-Sectoral Impact Model Intercomparison Project phase 2b (ISIMIP) Lake Sector, where lake evaporation responses to 20<sup>th</sup> and 21<sup>st</sup> century (1901-2099) climate change has been simulated with a suite of independently developed lake models under different climate change scenarios (Representative Concentration Pathways, RCP, 2.6, 6.0 and 8.5). Our study focuses on Lake Kinneret (Israel), a sub-tropical monomictic lake of socioeconomic importance. Our simulations are validated during the historic period with bulk evaporation estimates calculated from high frequency meteorological and in-lake observations. Our results demonstrate that the lake models provide an accurate representation of historical variability in lake evaporation, with promising comparisons of the magnitude, timing and seasonality of evaporative water loss. Future evaporation projections at Lake Kinneret show that evaporation anomalies will increase by the end of the century. We show that multi-model projections of lake evaporation can accurately represent the historic period and hence provide reliable future projections that will be vital for water management.</p>

Evaluation of climate change impacts on streamflow to a multiple reservoir system using a data-based mechanistic model

2014 ◽  
Vol 5 (4) ◽  
pp. 610-624 ◽  
Author(s):  
Sara Nazif ◽  
Mohammad Karamouz
Keyword(s):  
Climate Change ◽  
General Circulation ◽  
Mechanistic Model ◽  
Moving Average ◽  
Daily Rainfall ◽  
Circulation Model ◽  
Climate Change Impacts ◽  
Climate Change Scenarios ◽  
Daily Streamflow ◽  
Global Mean Temperature

Recent investigations have demonstrated scientists' consensus on the increase in global mean temperature and climate variability. These changes alter the hydro-climatic condition of regions. Investigation of surface water changes is an important issue in water resources planning as well as for the operation of reservoirs. In this study a data-based mechanistic (DBM) model has been used for daily streamflow simulation. This model is a data-driven statistical base simulation model that can take advantage of additional climate variables with time variable configurations. The model has been developed for simulation of streamflow to three reservoirs, located in central Iran, using the daily rainfall, temperature and streamflow data. Comparison of the DBM results with the autoregressive integrated moving average model, as an alternative model, shows its higher performance. To include climate change impacts in study, an artificial neural network-based statistical downscaling model is developed for rainfall and temperature downscaling. The downscaled temperature and rainfall data under climate change scenarios based on HadCM3 general circulation model outputs are used to evaluate the climate change impacts on streamflow for the 2000–2050 time horizon. The results demonstrate the considerable impact of climate change on streamflow variability with significantly different behaviour in the three adjacent basins.

scholarly journals Large Pelagic Fish Are Most Sensitive to Climate Change Despite Pelagification of Ocean Food Webs

2020 ◽  
Vol 7 ◽  
Author(s):  
Colleen M. Petrik ◽  
Charles A. Stock ◽  
Ken H. Andersen ◽  
P. Daniël van Denderen ◽  
James R. Watson
Keyword(s):  
Climate Change ◽  
Temperature Dependence ◽  
Food Webs ◽  
Fish Assemblages ◽  
Mechanistic Model ◽  
Global Environmental Change ◽  
Pelagic Fish ◽  
Trophic Levels ◽  
Predatory Fish ◽  
Functional Types

Global climate change is expected to impact ocean ecosystems through increases in temperature, decreases in pH and oxygen, increased stratification, with subsequent declines in primary productivity. These impacts propagate through the food chain leading to amplified effects on secondary producers and higher trophic levels. Similarly, climate change may disproportionately affect different species, with impacts depending on their ecological niche. To investigate how global environmental change will alter fish assemblages and productivity, we used a spatially explicit mechanistic model of the three main fish functional types reflected in fisheries catches (FEISTY) coupled to an Earth system model (GFDL-ESM2M) to make projections out to 2100. We additionally explored the sensitivity of projections to uncertainties in widely used metabolic allometries and their temperature dependence. When integrated globally, the biomass and production of all types of fish decreased under a high emissions scenario (RCP 8.5) compared to mean contemporary conditions. Projections also revealed strong increases in the ratio of pelagic zooplankton production to benthic production, a dominant driver of the abundance of large pelagic fish vs. demersal fish under historical conditions. Increases in this ratio led to a “pelagification” of ecosystems exemplified by shifts from benthic-based food webs toward pelagic-based ones. The resulting pelagic systems, however, were dominated by forage fish, as large pelagic fish suffered from increasing metabolic demands in a warming ocean and from declines in zooplankton productivity that were amplified at higher trophic levels. Patterns of relative change between functional types were robust to uncertainty in metabolic allometries and temperature dependence, though projections of the large pelagic fish had the greatest uncertainty. The same accumulation of trophic impacts that underlies the amplification of productivity trends at higher trophic levels propagates to the projection spread, creating an acutely uncertain future for the ocean’s largest predatory fish.

scholarly journals Modelling the impact of climate change on the distribution and abundance of tsetse in Northern Zimbabwe

2020 ◽  
Author(s):  
Joshua Longbottom ◽  
Cyril Caminade ◽  
Harry S. Gibson ◽  
Daniel J. Weiss ◽  
Steve Torr ◽  
...  
Keyword(s):  
Climate Change ◽  
Population Dynamics ◽  
Spatial Resolution ◽  
Air Temperature ◽  
Mechanistic Model ◽  
Tsetse Flies ◽  
Weather Station ◽  
Catch Data ◽  
Tsetse Population ◽  
The Impact

AbstractBackgroundClimate change is predicted to impact the transmission dynamics of vector-borne diseases. Tsetse flies (Glossina) transmit species of Trypanosoma that cause human and animal African trypanosomiasis. A previous modelling study showed that temperature increases between 1990 and 2017 can explain the observed decline in abundance of tsetse at a single site in the Mana Pools National Park of Zimbabwe. Here, we apply a mechanistic model of tsetse population dynamics to predict how increases in temperature may have changed the distribution and relative abundance of Glossina pallidipes across northern Zimbabwe.MethodsLocal weather station temperature measurements were previously used to fit the mechanistic model to longitudinal G. pallidipes catch data. To extend the use of the model, we converted MODIS land surface temperature to air temperature, compared the converted temperatures with available weather station data to confirm they aligned, and then re-fitted the mechanistic model using G. pallidipes catch data and air temperature estimates. We projected this fitted model across northern Zimbabwe, using simulations at a 1 km × 1 km spatial resolution, between 2000 to 2016.ResultsWe produce estimates of relative changes in G. pallidipes mortality, larviposition, emergence rates and abundance, for northern Zimbabwe. Our model predicts decreasing tsetse populations within low elevation areas in response to increasing temperature trends during 2000-2016. Conversely, we show that high elevation areas (>1000 M.A.S.L), previously considered too cold to sustain tsetse, may now be climatically suitable.ConclusionsThe results of this research represent the first regional-scale assessment of temperature related tsetse population dynamics, and the first high spatial-resolution estimates of this metric for northern Zimbabwe. Our results suggest that tsetse abundance may have declined across much of the Zambezi valley in response to changing climatic conditions during the study period. Future research including empirical studies is planned to improve model accuracy and validate predictions for other field sites in Zimbabwe.

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