Integrating social and ecological data to model metapopulation dynamics in coupled human and natural systems.

Understanding how metapopulations persist in dynamic working landscapes requires assessing the behaviors of key actors that change patches as well as intrinsic factors driving turnover. Coupled human and natural systems (CHANS) research uses a multidisciplinary approach to identify the key actors, processes, and feedbacks that drive metapopulation and landscape dynamics. We describe a framework for modeling metapopulations in CHANS that integrates ecological and social data by coupling stochastic patch occupancy models of metapopulation dynamics with agent-based models of land-use change. We then apply this framework to metapopulations of the threatened black rail (Laterallus jamaicensis) and widespread Virginia rail (Rallus limicola) that inhabit patchy, irrigation-fed wetlands in the rangelands of the California Sierra Nevada foothills. We collected data from five diverse sources (rail occupancy surveys, land-use change mapping, a survey of landowner decision making, climate and reservoir databases, and mosquito trapping and West Nile virus testing) and integrated them into an agent-based stochastic patch occupancy model. We used the model to (1) quantify the drivers of metapopulation dynamics, and the potential interactions and feedbacks among them; (2) test predictions of the behavior of metapopulations in dynamic working landscapes; and (3) evaluate the impact of three policy options on metapopulation persistence (irrigation district water cutbacks during drought, incentives for landowners to create wetlands, and incentives for landowners to protect wetlands). Complex metapopulation dynamics emerged when landscapes functioned as CHANS, highlighting the importance of integrating human activities and other ecological processes into metapopulation models. Rail metapopulations were strongly top-down regulated by precipitation, and the black rail's decade-long decline was caused by the combination of West Nile virus and drought. Theoretical predictions of the two metapopulations' responses to dynamic landscapes and incentive programs were complicated by heterogeneity in patch quality and CHANS couplings, respectively. Irrigation cutbacks during drought posed a serious extinction risk that neither incentive policy effectively ameliorated.

Grazing exclusion reduced soil respiration but increased its temperature sensitivity in a Meadow Grassland on the Tibetan Plateau.

Understanding anthropogenic influences on soil respiration (R s) is critical for accurate predictions of soil carbon fluxes, but it is not known how R s responds to grazing exclusion (GE). Here, we conducted a manipulative experiment in a meadow grassland on the Tibetan Plateau to investigate the effects of GE on R s. The exclusion of livestock significantly increased soil moisture and above-ground biomass, but it decreased soil temperature, microbial biomass carbon (MBC), and R s. Regression analysis indicated that the effects of GE on R s were mainly due to changes in soil temperature, soil moisture, and MBC. Compared with the grazed blocks, GE significantly decreased soil carbon release by 23.6% over the growing season and 21.4% annually, but it increased the temperature sensitivity (Q10) of R s by 6.5% and 14.2% for the growing season and annually respectively. Therefore, GE may reduce the release of soil carbon from the Tibetan Plateau, but under future climate warming scenarios, the increases in Q10 induced by GE could lead to increased carbon emissions.