Simulations of Human Settlements in Arid Environments with the SeDD (Settlement Dynamics in Drylands) Model.

JULIETA N. ARANIBAR; SILVANA GOIRÁN; EMMANUEL MILLAN; EDUARDO BRINGA

Tunuyán

Conferencia; IV Southern Deserts Conference; 2014

FCEN, UNCuyo

p { margin-bottom: 0.21cm; direction: ltr; color: rgb(0, 0, 0); text-align: left; widows: 2; orphans: 2; }p.western { font-family: "Times New Roman",serif; font-size: 12pt; }p.cjk { font-family: "Times New Roman",serif; font-size: 12pt; }p.ctl { font-family: "Times New Roman",serif; font-size: 12pt; }a:link { color: rgb(0, 0, 255); } In arid environments, water is the main determinant of ecologicprocesses, and also influences cultural and economic activities. Wepostulate that the spatial distribution of human settlements in aridenvironments is mostly determined by water availability, althoughforest resources and access roads may have a secondary effects. Weevaluate this hypothesis with a Monte Carlo model, SeDD (SettlementDynamics in Drylands), that simulates human settlements on a grid,based on six environmental conditions: groundwater depth, vegetationtype, presence or distance to rivers, old river beds, existingsettlements, and roads. The model has an stochastic component, andassumes that settlers have a knowledge of the environmentalconditions in the entire region. We applied this model to the centralMonte desert, Mendoza, where the main economic activity of the localsettlers, mostly descendants and/or identified as Huarpe aboriginals,is extensive livestock production. We also model vegetationdegradation aroundsettlements.Simulation results are compared with real settlement patterns andvegetation maps.Wefound that distances to rivers and old river beds are critical toexplain the current distribution of settlements. The simulatedvegetation, including degradationaroundsettlements, matched the spatial distribution of remotely sensedvegetation, although with highercoversfor extreme vegetation classes (degraded areas and well conservedwoodlands). The model could be a useful tool to simulatethespatial distribution of past human settlements, and analyze theirinteractions with environmental changes. p { margin-bottom: 0.21cm; direction: ltr; color: rgb(0, 0, 0); text-align: left; widows: 2; orphans: 2; }p.western { font-family: "Times New Roman",serif; font-size: 12pt; }p.cjk { font-family: "Times New Roman",serif; font-size: 12pt; }p.ctl { font-family: "Times New Roman",serif; font-size: 12pt; }a:link { color: rgb(0, 0, 255); }In arid environments, water is the main determinant of ecologicprocesses, and also influences cultural and economic activities. Wepostulate that the spatial distribution of human settlements in aridenvironments is mostly determined by water availability, althoughforest resources and access roads may have a secondary effects. Weevaluate this hypothesis with a Monte Carlo model, SeDD (SettlementDynamics in Drylands), that simulates human settlements on a grid,based on six environmental conditions: groundwater depth, vegetationtype, presence or distance to rivers, old river beds, existingsettlements, and roads. The model has an stochastic component, andassumes that settlers have a knowledge of the environmentalconditions in the entire region. We applied this model to the centralMonte desert, Mendoza, where the main economic activity of the localsettlers, mostly descendants and/or identified as Huarpe aboriginals,is extensive livestock production. We also model vegetationdegradation aroundsettlements.Simulation results are compared with real settlement patterns andvegetation maps.Wefound that distances to rivers and old river beds are critical toexplain the current distribution of settlements. The simulatedvegetation, including degradationaroundsettlements, matched the spatial distribution of remotely sensedvegetation, although with highercoversfor extreme vegetation classes (degraded areas and well conservedwoodlands). The model could be a useful tool to simulatethespatial distribution of past human settlements, and analyze theirinteractions with environmental changes.