Extinction rates are expected to increase during the Anthropocene. Current extinction rates of plants and many animals remain unknown. We quantified extinctions among the vascular flora of the continental United States and Canada since European settlement. We compiled data on apparently extinct species by querying plant conservation databases, searching the literature, and vetting the resulting list with botanical experts. Because taxonomic opinion varies widely, we developed an index of taxonomic uncertainty (ITU). The ITU ranges from A to F, with A indicating unanimous taxonomic recognition and F indicating taxonomic recognition by only a single author. The ITU allowed us to rigorously evaluate extinction rates. Our data suggest that 51 species and 14 infraspecific taxa, representing 33 families and 49 genera of vascular plants, have become extinct in our study area since European settlement. Seven of these taxa exist in cultivation but are extinct in the wild. Most extinctions occurred in the west, but this outcome may reflect the timing of botanical exploration relative to settlement. Sixty-four percent of extinct plants were single-site endemics, and many occurred outside recognized biodiversity hotspots. Given the paucity of plant surveys in many areas, particularly prior to European settlement, the actual extinction rate of vascular plants is undoubtedly much higher than indicated here. 相似文献
Experimentally increasing atmospheric CO2 often stimulates plant growth and ecosystem carbon (C) uptake. Biogeochemical theory predicts that these initial responses will immobilize nitrogen (N) in plant biomass and soil organic matter, causing N availability to plants to decline, and reducing the long-term CO2-stimulation of C storage in N limited ecosystems. While many experiments have examined changes in N cycling in response to elevated CO2, empirical tests of this theoretical prediction are scarce. During seven years of postfire recovery in a scrub oak ecosystem, elevated CO2 initially increased plant N accumulation and plant uptake of tracer 15N, peaking after four years of CO2 enrichment. Between years four and seven, these responses to CO2 declined. Elevated CO2 also increased N and tracer 15N accumulation in the O horizon, and reduced 15N recovery in underlying mineral soil. These responses are consistent with progressive N limitation: the initial CO2 stimulation of plant growth immobilized N in plant biomass and in the O horizon, progressively reducing N availability to plants. Litterfall production (one measure of aboveground primary productivity) increased initially in response to elevated CO2, but the CO2 stimulation declined during years five through seven, concurrent with the accumulation of N in the O horizon and the apparent restriction of plant N availability. Yet, at the level of aboveground plant biomass (estimated by allometry), progressive N limitation was less apparent, initially because of increased N acquisition from soil and later because of reduced N concentration in biomass as N availability declined. Over this seven-year period, elevated CO2 caused a redistribution of N within the ecosystem, from mineral soils, to plants, to surface organic matter. In N limited ecosystems, such changes in N cycling are likely to reduce the response of plant production to elevated CO2. 相似文献
Robust decision making, a growing approach to infrastructure planning under climate change uncertainty, aims to evaluate infrastructure performance across a wide range of possible conditions and identify the most robust strategies and designs. Robust decision making seeks to find potential weaknesses in systems in order to gird these through a combination of policy, infrastructure, and, in some cases, resilient or recovery strategies. A system can be explored by simulating many combinations of uncertain climatic and economic parameters; statistical clustering can identify parameter thresholds that lead to unacceptable performance. Often, however, uncertain variables are correlated, complicating the robustness analysis and casting doubt upon the thresholds identified. Here, we evaluate the impact of ordinary, hidden correlations in uncertainty parameters that drive simulation in robust decision making. We induced correlations between temperature and key climatic and economic parameters. We tested correlations of 0%, 30%, 60%, and 90% between temperature and the absolute value of precipitation, coefficient of variation, and downward surface solar radiation, and negative correlations between temperature and net variable benefit and the discount rate. We used a calibrated simulation model of a dam system regulating Lake Tana, Ethiopia, to compute the agricultural supply and net present value of the reservoirs. As the correlation strength increased, the results converged in a smaller region. We found that strong correlations depressed robustness scores of lower-performing alternatives and conversely increased results of the higher-performing alternatives. As the correlations increased in favorable alternatives, the failure thresholds became more extreme, speciously suggesting that only intense changes would result in poor performance. This overall analysis highlights the degree to which correlations of an interconnected climatic and economic system can impact outcomes of robust decision making and suggests methods to avoid confounding results.