DOI: 10.5061/dryad.pg4f4qrxd
title: Biomass production at 2085 horizon for the Maurienne valley (French Alps) estimated using a Bayesian Belief Network

description: In mountains, grasslands managed for livestock production sustain local
 economies, culture and identity. However, their future fodder production
 is highly uncertain under climate change: while an extended growing season
 may be beneficial, more frequent and intense summer droughts could also
 reduce fodder quantity and quality. Land use and land cover (LULC) changes
 are another major driver of regional grassland biomass production, but
 combined effects of future land use transitions and climate change are
 rarely quantified. We modelled combined climate and LULC scenarios for
 grassland production of the Maurienne Valley (French Alps) by 2100. We
 built a Bayesian Belief Network (BBN) from long-term grassland production
 monitoring data complemented with expert knowledge. We assessed the
 potential of two candidate adaptations, intensification as an incremental
 solution, and silvopastoralism as a transformative solution to compensate
 combined impacts of two climate scenarios and three land use change
 scenarios. Total biomass production was far more sensitive to LULC than to
 climate scenarios. Production losses were largest under the Conservation
 LULC scenario (-28% on average between 2020 and 2085), followed by the
 Tourism development scenario (-7%) and the Business-as-Usual scenario
 (+3%). Climate change under RCP 8.5 altered the seasonality of production
 by increasing potential production from May to July while decreasing
 summer regrowth. Intensification somewhat compensated effects of climate
 and LULC changes on biomass production, whereas silvopastoralism offered
 only marginal gains. The Bayesian network model explicitly captured a
 future increase in interannual variability in biomass production.
 Synthesis and application: Changes in LULC are more decisive for global
 biomass production than climate change. However, under the most extreme
 climate change scenario (RCP8.5), the seasonal shift in production and
 increased interannnual variability threaten the current grass-based
 Protected Designation of Origin production system. Only the
 intensification adaptation solution showed significant gains in total
 biomass production. Still, the silvopastoralism would require less
 investment compared to the intensification and have a similar efficiency
 when assessing the gains of biomass by the surface concerned with
 adaptation solutions.  
description: This dataset was produced using a Bayesian Belief Network that
 estimate the biomass production across time and scenarios of future land
 use and land cover change.  For a full description of
 the methodology see: A Bayesian analysis of adaptation of mountain
 grassland production to global change published in JOAE in 2024.
description: # Biomass production at 2085 horizon for the Maurienne valley (French
 Alps) estimated using a Bayesian Belief Network
 [https://doi.org/10.5061/dryad.pg4f4qrxd](https://doi.org/10.5061/dryad.pg4f4qrxd) This datasets comprise raster of biomass production for the Maurienne valley (French Alps). Values are expressed in 10^3 kg.km^-2.year^-1 of dry biomass matter. Rasters are in EPSG: 4326. Those results are the product of a Bayesian Belief Network, a full description of the model is available in the main publication linked to this deposit. ## Description of the data and file structure We provide several rasters of biomass production for time periods: 2020, 2050, 2085; across three future scenarios of land use and land cover change (see 10.5061/dryad.83bk3jb0h); across two future scenarios of climate change (RCP 4.5 and RCP 8.5) and across three modalities of adaptation solution implementation (Control, Silvopastoralism, Irrigation and fertilization). Scenarios of future Land Use and Land Cover change (LULC) : Three scenarios of future change are provided (Buisiness as Usual - **S1**, Conservation - **S2**, Tourism - **S3**). For each of those scenarios two dates are provided : 2050 and 2085. In 2020 only one map is available (for S1) as it is the current state of LULC. For a full description of those LULC scenarios, see the main article. All scenarios are also accessible on : [https://doi.org/10.5061/dryad.83bk3jb0h](https://doi.org/10.5061/dryad.83bk3jb0h) Control : No adaptation Solution Silvopastoralism: two modalities: Only Grassland (no silvopastoralim), Grassland and Shrub (the silvopastoralism is implemented and recently encroached surfaces are producing biomass) Irrigation and Fertilization: Control no implementation; Lowland, implemented only in low altitudes; Wide, implemented on low and medium altitudes. We also provide an intermediary product of the model as raster: the precited grassland ecological type. Before estimating the biomass production, our model predict the likelyhood of each pixel to belong to a specific grassland type that controls its biomass production range. The model assigns at each pixel a probability to belong to each of those ecological type and we provide here the raster of the most probable state over our study site. | Code | Grassland type | | :--- | :------------- | | 1 | Thermophilous | | 2 | Snowbed | | 3 | Intermediate | | 4 | Productive | | 5 | Lowland |