Integrating information derived from different knowledge systems into natural resource management decision-making can be challenging. As an example of how this can be done effectively, a recent paper in the journal Conservation Science and Practice outlines a unique process whereby Local Ecological Knowledge was combined with scientific knowledge in order to inform the management of a muskox herd in southern Greenland. A key component of this work was running the DG-Sim population model with local stakeholders, allowing them to review and modify model assumptions, explore alternative future harvest scenarios, and ultimately achieve consensus with government regarding future harvest levels for the herd.
Attendees at the International Association of Landscape Ecology (IALE) North America Meeting in Toronto will have the opportunity to participate in a hands-on SyncroSim and ST-Sim Workshop on Tuesday, May 12, from 1:00 pm to 5:00 pm. SyncroSim is a free software platform designed to streamline data management tasks associated with ecological forecasting, in order to facilitate scenario and uncertainty analyses. SyncroSim allows modelers to develop “packages” to bundle and share collections of linked GitHub-based model scripts. One such package has been developed for a model called ST-Sim. ST-Sim uses a state-and-transition simulation model approach to forecast landscape dynamics, including projecting changes in both vegetation and land use. This half day workshop will introduce developing and running spatially explicit models of landscape change using the open-source ST-Sim package within SyncroSim. The workshop will also introduce developing custom packages in SyncroSim, including packages to extend the core functionality of ST-Sim. Workshop registration opens in February.
Learn more about our current work modeling wetland carbon cycling at the AGU Fall Meeting 2019 in San Francisco this week. This work is part of the U.S. Geological Survey’s LandCarbon Program, which produces national assessments of carbon storage and greenhouse gas (GHG) fluxes in ecosystems under current and future conditions of climate and land use change.
ApexRMS is collaborating with the Quebec Government and Andrew Gonzalez from McGill University to assess forest habitat connectivity within the St. Lawrence Lowlands under scenarios of climate and landuse change. We recently published a report and webinar identifying connectivity conservation priorities based on current land use and land cover. Work is now underway to combine climate projections with land use and land cover projections (using ST-Sim) for the St. Lawrence Lowlands so that we can identify priority areas to protect that have a higher probability of maintaining habitat connectivity into the future.
The Natural Sciences and Engineering Research Council of Canada (NSERC) has announced funding for an exciting new project led by Elena Bennett at McGill University – NSERC ResNet: A network for monitoring, modeling, and managing Canada’s ecosystem services for sustainability and resilience. ApexRMS is proud to be an industry partner and work with this talented network of scientists to help measure Canada’s progress towards its sustainability goals. Positions are open for network managers, data managers, grad students, undergrads, postdocs and other researchers. Stay up to date by following @NSERC_ResNet.
Links between climate change and land use are in the news around the world this week following the publication of a special report on the topic by the Intergovernmental Panel on Climate Change (IPCC). A recent paper published in Global Change Biology conducts an in depth scientific investigation of the interactions between climate and land use change in the state of California. The authors used ST-Sim software to build an integrated model of landscape change and carbon dynamics that estimated carbon stocks and fluxes for California’s forest, grassland, shrubland, and agricultural ecosystems. Carbon storage in California’s terrestrial ecosystems was projected to decline in nearly all of the 32 alternative future scenarios considered but there were large uncertainties associated with these projections stemming from underlying uncertainties about increasing CO2 and its effect on ecosystem carbon storage and flux.
A recent study published in the journal Ecosphere showcases the development of a landscape model that combines a state-and-transition simulation model developed in ST-Sim with a dynamically linked fire behaviour model, FARSITE. These dynamically linked models allow land managers at Saguaro National Park to consider alternative scenarios for novel processes including invasive grasses and fire dynamics not seen before in this ecosystem. The paper is the first published example of how the SyncroSim framework can be used to dynamically link individual models, thus allowing simulations to address complex ecological and management questions.
A recent report by the Nature Conservancy and Next 10 shows that nature based solutions to climate change can be a cost-effective means of reducing carbon emissions and can produce many co-benefits. The authors used ST-Sim software to build an integrated model of landscape change and carbon dynamics for the state of California which allowed them to quantify emissions associated with different land use interventions in forests, farms, and rangelands. The effectiveness of these land use interventions to reduce emissions was evaluated under two different climate scenarios out to 2030, 2050, and 2100.
A recent paper published in Frontiers in Ecology and Evolution proposes that traditional networks of permanent protected areas may be more effective at conserving biodiversity under climate change if they are augmented with dynamic conservation areas. The paper was the brain child of a working group funded by the Canadian Institute for Ecology and Evolution that was made up of researchers from academia, government, NGOs, and ApexRMS.
Early registration ends Tuesday, Feb 19!
This two-day online course establishes the fundamentals attendees need to use the free ST-Sim software to develop spatially-explicit, integrated models of both landscape change and carbon dynamics.
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