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Janus is an open source Python package for agent-based modeling (ABM) of land use and land cover change (LULCC). Many ABMs of LULCC have been created across platforms, some of which are not ideal for large scale, high resolution scenarios. This model provides a simple object-oriented framework for creating ABMs specific to LULCC. The organizational philosophy of the modeling framework is to create software objects (agents) that are associated with specific and contextual attributes which are isolated from where those agents exist in the spatial setting of the model, and still provide clear linkages between the agent, their environment, and other agents in the simulation. In this way, the framework allows for assembly of LULCC ABMs with low (programmatic) overhead, making the models extensible and providing clear mechanisms for integrating them with process-oriented biophysical models. Provided with Janus is a suite of geospatial data preprocessing tools that can use arbitrary land cover products as an input. Crop choice decisions are based on potential crop prices, these can be created synthetically, or drawn from integrated human-Earth systems models such as the Global Change Assessment Model. Janus is publicly accessible through GitHub and provides an example dataset for testing.

Relationships between methane (CH4) fluxes and environmental conditions have been extensively explored in saturated soils, while research has been less prevalent in aerated soils because of the relatively small magnitudes of CH4 fluxes that occur in dry soils. Our study builds on previous carbon cycle research at Tenderfoot Creek Experimental Forest, Montana, to identify how environmental conditions reflected by topographic metrics can be leveraged to estimate watershed scale CH4 fluxes from point scale measurements. Here, we measured soil CH4 concentrations and fluxes across a range of landscape positions (7 riparian, 25 upland), utilizing topographic and seasonal (29 May–12 September) gradients to examine the relationships between environmental variables, hydrologic dynamics, and CH4 emission and uptake. Riparian areas emitted small fluxes of CH4 throughout the study (median: 0.186 µg CH4–C m−2 h−1) and uplands increased in sink strength with dry-down of the watershed (median: −22.9 µg CH4–C m−2 h−1). Locations with volumetric water content (VWC) below 38 % were methane sinks, and uptake increased with decreasing VWC. Above 43 % VWC, net CH4 efflux occurred, and at intermediate VWC net fluxes were near zero. Riparian sites had near-neutral cumulative seasonal flux, and cumulative uptake of CH4 in the uplands was significantly related to topographic indices. These relationships were used to model the net seasonal CH4 flux of the upper Stringer Creek watershed (−1.75 kg CH4–C ha−1). This spatially distributed estimate was 111 % larger than that obtained by simply extrapolating the mean CH4 flux to the entire watershed area. Our results highlight the importance of quantifying the space–time variability of net CH4 fluxes as predicted by the frequency distribution of landscape positions when assessing watershed scale greenhouse gas balances.