Anthropocene最新文献

This study provides estimates of climate change impacts on U.S. agricultural yields and the agricultural economy through the end of the 21st century, utilizing multiple climate scenarios. Results from a process-based crop model project future increases in wheat, grassland, and soybean yield due to climate change and atmospheric CO₂ change; corn and sorghum show more muted responses. Results using yields from econometric models show less positive results. Both the econometric and process-based models tend to show more positive yields by the end of the century than several other similar studies. Using the process-based model to provide future yield estimates to an integrated agricultural sector model, the welfare gain is roughly $16B/year (2019 USD) for domestic producers and $6.2B/year for international trade, but domestic consumers lose $10.6B/year, resulting in a total welfare gain of $11.7B/year. When yield projections for major crops are drawn instead from econometric models, total welfare losses of more than $28B/year arise. Simulations using the process-based model as input to the agricultural sector model show large future production increases for soybean, wheat, and sorghum and large price reductions for corn and wheat. The most important factors are those about economic growth, flooding, international trade, and the type of yield model used. Somewhat less, but not insignificant factors include adaptation, livestock productivity, and damages from surface ozone, waterlogging, and pests and diseases.

Urban flooding is a growing threat due to land use and climate change. Vulnerable populations tend to have greater exposure to flooding as a result of historical societal and institutional processes. Most flood vulnerability studies focus on a single large flood, neglecting the impact of small, frequent floods. Therefore, there is a need to investigate inequitable flood exposure across a range of event magnitudes and frequencies. To explore this question, we develop a novel score of inequitable flood risk by defining risk as a function of frequency, exposure, and vulnerability. This analysis combines high-resolution, parcel-scale compounded fluvial and pluvial flood data with census data at the census block group scale. We focus on six census tracts within Athens-Clarke County, Georgia that are highly developed with diverse populations. We define vulnerable populations as non-Hispanic Black, Hispanic, and households under the poverty level and use dasymetric mapping techniques to calculate the over-representation of these populations in flood zones. Inequitable risks at each census tract (approximately neighborhood scale) were estimated for multiple (e.g., 5-, 10-, 20-, 50-, and 100-year) flood return periods. Results show that the relatively greatest flood risk inequities occur for the 10-year flood and not at the largest event. We also found that the size of inequity is dynamic, depending on the flood magnitude. Therefore, addressing a range of events including smaller, more frequent floods can increase equity and reveal opportunities that may be missed if only one event is considered.

Relics of past agricultural practices, former field systems have strongly imprinted many modern landscapes and have thus significantly disrupted forest ecosystems over the last centuries. Former field systems in the Hautes-Vosges mountain range (north-eastern France) date primarily to the medieval period (6–15th century C.E.) and consist of parcelled or linear structures on hillslopes and valley floors. These residual features fall into three categories: ridge and furrow, terraced slopes, and stone walls. LiDAR (light detection and ranging) can detect microrelief features, such as the topographical imprints of these field systems over extended areas, and thereby establish a new temporal baseline for reconstructing forest changes over relatively long timescales, i.e., before the first historical topographic maps. Here, we digitize former field systems in the south-eastern Vosges from a high-resolution LiDAR-derived DEM to assess their spatial distribution at the mountain-range scale (1185 km²) and in relation to topography. Former field systems cover approx. 6.6 % of the study area (78.5 km²), with terraced slopes (55.5 km²) and stone walls (20.6 km²) covering a greater extent than ridge and furrow (2.4 km²). Former field systems are preferentially located on south-facing slopes above an 800 m a.s.l. threshold; this pattern indicates systematic past agricultural practices across the entire region. We then compare the LiDAR-derived spatial features with a 19th-century map of France and a modern regional land-cover database to derive the spatio-temporal trajectories of landscapes. We observe that former field systems were progressively, but unevenly, abandoned and transformed into grasslands or forests. This mid-19th century abandonment of agricultural fields and their conversion to grassland and forest is highly dependent on slope and elevation (grassland and forest: 18–19° and 610–620 m). These values differ from those associated with agricultural sites that remain under cultivation today (approx. 16° and 550 m). Finally, we demonstrate the relevance of integrating former field systems for characterizing areas of ancient forest. Less than 2 % of the area mapped as forest in the 19th century was cultivated between the 6th and 15th century. Most importantly, our approach quantifies disturbed and undisturbed ancient forest areas at the mountain-range scale. While this study opens new perspectives for accurately assessing the age of forest ecosystems, it also reveals an evolutionary pattern of land-use change in the Hautes-Vosges that is similar to that observed in other European mountainous regions.

The Argentine Puna is an example of rewilding of the herbivore community, with wild camelids recovering (mainly vicuñas, Vicugna vicugna and guanacos Lama guanicoe) while livestock decreases. Peatlands are the most diverse ecosystem in the region and are key resources for herbivores. Here, we tested the hypothesis that herbivore rewilding is associated with higher biodiversity of three biological groups: plants, aquatic macroinvertebrates, and birds. We sampled 50 peatlands distributed in the Argentine Puna, along an elevation range from 3200 to 4700 m asl. Using Non-metric multidimensional scaling (NMDS), we developed a “wilderness index” that combines different proxies of pastoral use (herbivore feces, “puestos”, accessibility to human settlements, field counts of herbivores). In general, the diversity of the different groups was negatively correlated with elevation and positively correlated with peatland area, thus we used the residuals of a model to control for these two variables and test for the correlation between biodiversity patterns (Shannon index and richness) and peatland wilderness index. Contrary to our expectations, diversity of plant and macroinvertebrate communities’ showed slightly negative statistically significant correlations with wilderness, while birds showed no statistical association. Potential explanations for this pattern include (1) diversity of microhabitats generated by a more diverse herbivore's community associated with livestock (e.g., different trampling, browsing, and movement patterns, effects on water quality through feces), (2) management of hydrological regimes and stocking rates to provide stability, (3) herbivory dynamics that promote the dominance of certain plants. Overall, the results reject the hypothesis that herbivore rewilding automatically results in biodiversity gains, and emphasize the importance of understanding the socio-ecological mechanisms by which human land use (including exotic livestock) contributes to the biodiversity maintenance in these key ecosystems.

Lack of integrated approaches in the assessment of land, water, and climate-related problems leads to the development of ineffective solutions at the country level. It put further challenges to achieve regional-level sustainable development targets. This is particularly true for countries like India where water, land, and climate problems are very complex and interconnected starting from the watershed level to the regional level. Interlinked synergies work as the key to achieving collective action to target multiple sustainable development goals (SDG). The land, water, and climate components are prioritized in SDG 6, 13, and 15 goals respectively, which are assessed through an integrated approach using a Soil and Water Assessment Tool (SWAT) model. A semi-arid ungauged Khari basin is selected for the sustainability assessment and hydrologic response study. As the region is critical in terms of shortage of water, land conversions, and climate change and can present a way to address challenges in regional-level sustainability assessments. SWAT model is considered for two land-use scenarios, 1990 and 2015, for the period 1990–2019 and two climate scenarios, Representative Concentrated Pathways (RCP 4.5 and RCP 8.5), for the period 2021–2050 while keeping the slope and soil data same in both models. The simulated discharge data matched well with the observed discharge data, with NSE of 0.72, PBIAS of − 1.9, R² of 0.72 during calibration, and NSE of 0.72, PBIAS of − 4.7, and R² of 0.73 during validation. It can be observed from the Land use change scenario assessment that an increase in the fallow agriculture land area shows a positive relation with surface runoff and a negative relation with percolation. Similarly, climate change scenario assessment shows that in future scenarios temperature will increase in both the RCPs 4.5 and 8.5 but hydrological components are more responsive to the changes in rainfall than temperature changes. Study results pointed out that both land use change and climate change can significantly affect the surface as well as groundwater availability of the region and it also highlights the functionality of an integrated assessment approach that assesses land, water, and climate components of SDGs through a hydrological model. It supplies an understanding of important interlinked influences and responses that are to be studied and managed collectively at the regional level in future studies.

Climatic extremes and violent conflicts can play a significant role in reducing a country’s population. However, the occasional coexistence and interplay of climatic extremes and violent conflicts make it difficult to quantify their individual or collective demographic impacts and associated spatial dynamics, and thus to determine which plays the more important part. Can long-term historical data shed more light on this conundrum? This study explores the effect of climatic extremes and violent conflicts on China’s population, using data from 1741 to 1910 and spatial econometrics. It differs from other quantitative historical studies by addressing the spatial autocorrelation property of population data and the spatial spillover effect of those population-determining factors. The statistical results show that, in general, violent conflicts reduce population density, and that their demographic impact is stronger than those of climatic extremes. Specifically, while violent conflicts reduce population density in the areas they directly affect, they also increase the population density in neighboring areas, as people flee the affected area and take refuge elsewhere. Alternatively, floods, droughts, and extreme floods cannot suppress the local population density but negatively affect the population density in the surrounding areas. Furthermore, violent conflicts and extreme droughts have a significant synergistic effect in reducing population density. This study provides a more detailed picture of the impact of climatic extremes and violent conflicts on historical population densities, and draws attention to the nuanced spatial dynamics embedded in the nexus between the population and its determinants. More generally, its findings may help future researchers to determine the demographic impact of more frequent climatic extremes and violent conflicts brought on by global climate change.

Land-use change plays an important role in shaping plant and insect diversity over long time timescales. Great Britain provides an ideal case study to investigate patterns of long-term vegetation and insect diversity change owing to the existence of spatially and temporally extensive environmental archives (lake sediments, peatlands, and archaeological sites) and a long history of landscape transformation through agrarian change. The trends identified in past environmental datasets allow the impacts of land-use change on plant and insect diversity trends to be investigated alongside exploration of the emergence of ecological novelty. Using fossil pollen, insect (beetle), archaeodemographic, archaeobotanical and modern landscape datasets covering Britain, similarities are identified between insect diversity and pollen sample evenness indicating that vegetation heterogeneity influences insect diversity. Changing land use captured by archaeobotanical data is significantly correlated with pollen diversity demonstrating the role of human activity in shaping past diversity trends with shifts towards ecosystem novelty identified in the form of non-analogue pollen taxa assemblages (unique species combinations). Modern landscapes with higher agricultural suitability are less likely to have pollen analogues beyond the last 1000 years, whilst those in areas less suited to agriculture and on more variable topography are more likely to have analogues older than 1000 years. This signifies the role of agriculture in the creation of novel ecosystems. Ecological assemblages characteristic of earlier periods of the Holocene may persist in areas less affected by agriculture. The last 200 years has witnessed major shifts in novelty in a low number of pollen sites suggesting that novel ecosystems emerged over a longer time period resulting from the cumulative impacts of land-use change.

Siberia occupies a significant part of the Eurasian continent and environmental changes in this region can have an important impact on the climate system of the Northern Hemisphere. The sediment flux of Siberian rivers is sensitive to changes in physical, chemical, and biological processes taking place on the continent, and these changes can be recorded in marine sediments on the Siberian Arctic Shelf. This paper presents data on grain-size distribution of the sediments, the sedimentation rates, and the mass accumulation rates on the shelf over the past 100 years. Age models are based on the decay rate of excess lead isotope ²¹⁰Pb, taking into account the sorption capacity of the marine sediments, and the presence of cesium isotope ¹³⁷Cs peaks in the sediment cores. The highest sedimentation and mass accumulation rates were observed prior to the 1920–40 and coincide with larger particle sizes, indicate a period of active sediment-laden sea ice and iceberg melt. Systematic decrease in the sedimentation and mass accumulation rates against the background of an increase in the proportion of silt fractions in the shelf sediments in the second half of the 20th century can be explained by an acceleration of the arctic hydrological cycle.

Climate change and Land Use/Cover Change, affected by human activity, are the two main factors influencing the regional water cycle and water management. However, studies of co-impacts based on future scenario predictions are still lacking. This study proposed a complete methodology for simulating future changes in water resources and distinguishing the independent and synergistic effects of climate change and land use change. The coupling prediction model of land use and the global climate models were used for scenario predictions; the hydrological model and statistical methods were used for simulations and analyses. The Ganjiang River, the largest tributary of Poyang Lake, is chosen as the study area. In the future, the main trend of change in land use would be the expansion of construction land in the northern part of the basin, and the future annual precipitation and temperature (p < 0.5) would increase. In this basin, runoff is more sensitive to climate change than to land use/cover change, and the synergistic effects are not substantial. Most climate scenarios showed a significant change in monthly peak runoff. The current peak is in June; this is projected to decrease with the simulated future peak in August, causing problems in basin flood control and Poyang Lake water level regulation. This study proposed a methodology integrating the global climate models with predicted land use scenarios and tested the feasibility at the watershed scale by the case study. It can serve as a reference for co-impact studies considering different scenarios and be extended to basins with similar areas, underlying surface variation intensity, or hydro-climatic characteristics, valuable for sustainable water resources management in the Anthropocene.