RESUMEN
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.
Asunto(s)
Ecología , Modelos Biológicos , Animales , Aves , California , Ecosistema , Humanos , Dinámica PoblacionalRESUMEN
United States (U.S.) energy policy includes an expectation that bioenergy will be a substantial future energy source. In particular, the Energy Independence and Security Act of 2007 (EISA) aims to increase annual U.S. biofuel (secondary bioenergy) production by more than 3-fold, from 40 to 136 billion liters ethanol, which implies an even larger increase in biomass demand (primary energy), from roughly 2.9 to 7.4 EJ yr(-1). However, our understanding of many of the factors used to establish such energy targets is far from complete, introducing significgant uncertainty into the feasibility of current estimates of bioenergy potential. Here, we utilized satellite-derived net primary productivity (NPP) data-measured for every 1 km(2) of the 7.2 million km(2) of vegetated land in the conterminous U.S.-to estimate primary bioenergy potential (PBP). Our results indicate that PBP of the conterminous U.S. ranges from roughly 5.9 to 22.2 EJ yr(-1), depending on land use. The low end of this range represents the potential when harvesting residues only, while the high end would require an annual biomass harvest over an area more than three times current U.S. agricultural extent. While EISA energy targets are theoretically achievable, we show that meeting these targets utilizing current technology would require either an 80% displacement of current crop harvest or the conversion of 60% of rangeland productivity. Accordingly, realistically constrained estimates of bioenergy potential are critical for effective incorporation of bioenergy into the national energy portfolio.
Asunto(s)
Biocombustibles/provisión & distribución , Agricultura , Comunicaciones por Satélite , Árboles , Estados UnidosRESUMEN
The magnitude of future climate change depends substantially on the greenhouse gas emission pathways we choose. Here we explore the implications of the highest and lowest Intergovernmental Panel on Climate Change emissions pathways for climate change and associated impacts in California. Based on climate projections from two state-of-the-art climate models with low and medium sensitivity (Parallel Climate Model and Hadley Centre Climate Model, version 3, respectively), we find that annual temperature increases nearly double from the lower B1 to the higher A1fi emissions scenario before 2100. Three of four simulations also show greater increases in summer temperatures as compared with winter. Extreme heat and the associated impacts on a range of temperature-sensitive sectors are substantially greater under the higher emissions scenario, with some interscenario differences apparent before midcentury. By the end of the century under the B1 scenario, heatwaves and extreme heat in Los Angeles quadruple in frequency while heat-related mortality increases two to three times; alpine/subalpine forests are reduced by 50-75%; and Sierra snowpack is reduced 30-70%. Under A1fi, heatwaves in Los Angeles are six to eight times more frequent, with heat-related excess mortality increasing five to seven times; alpine/subalpine forests are reduced by 75-90%; and snowpack declines 73-90%, with cascading impacts on runoff and streamflow that, combined with projected modest declines in winter precipitation, could fundamentally disrupt California's water rights system. Although interscenario differences in climate impacts and costs of adaptation emerge mainly in the second half of the century, they are strongly dependent on emissions from preceding decades.