59 resultados para Spatiotemporal change model
Resumo:
Our understanding of Earth's carbon climate system depends critically upon interactions between rising atmospheric CO2, changing land use, and nitrogen limitation on vegetation growth. Using a global land model, we show how these factors interact locally to generate the global land carbon sink over the past 200 years. Nitrogen constraints were alleviated by N2 fixation in the tropics and by atmospheric nitrogen deposition in extratropical regions. Nonlinear interactions between land use change and land carbon and nitrogen cycling originated from three major mechanisms: (i) a sink foregone that would have occurred without land use conversion; (ii) an accelerated response of secondary vegetation to CO2 and nitrogen, and (iii) a compounded clearance loss from deforestation. Over time, these nonlinear effects have become increasingly important and reduce the present-day net carbon sink by ~40% or 0.4 PgC yr−1.
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Semi-arid ecosystems play an important role in regulating global climate with the fate of these ecosystems in the Anthropocene depending upon interactions among temperature, precipitation, and CO2. However, in cool-arid environments, precipitation is not the only limitation to forest productivity. Interactions between changes in precipitation and air temperature may enhance soil moisture stress while simultaneously extending growing season length, with unclear consequences for net carbon uptake. This study evaluates recent trends in productivity and phenology of Inner Asian forests (in Mongolia and Northern China) using satellite remote sensing, dendrochronology, and dynamic global vegetation model (DGVM) simulations to quantify the sensitivity of forest dynamics to decadal climate variability and trends. Trends in photosynthetically active radiation fraction (FPAR) between 1982 and 2010 show a greening of about 7% of the region in spring (March, April, May), and 3% of the area ‘browning’ during summertime (June, July, August). These satellite observations of FPAR are corroborated by trends in NPP simulated by the LPJ DGVM. Spring greening trends in FPAR are mainly explained by long-term trends in precipitation whereas summer browning trends are correlated with decreasing precipitation. Tree ring data from 25 sites confirm annual growth increments are mainly limited by summer precipitation (June, July, August) in Mongolia, and spring precipitation in northern China (March, April, May), with relatively weak prior-year lag effects. An ensemble of climate projections from the IPCC CMIP3 models indicates that warming temperatures (spring, summer) are expected to be associated with higher summer precipitation, which combined with CO2 causes large increases in NPP and possibly even greater forest cover in the Mongolian steppe. In the absence of a strong direct CO2 fertilization effect on plant growth (e.g., due to nutrient limitation), water stress or decreased carbon gain from higher autotrophic respiration results in decreased productivity and loss of forest cover. The fate of these semi-arid ecosystems thus appears to hinge upon the magnitude and subtleties of CO2 fertilization effects, for which experimental observations in arid systems are needed to test and refine vegetation models.
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The past 1500 years provide a valuable opportunity to study the response of the climate system to external forcings. However, the integration of paleoclimate proxies with climate modeling is critical to improving the understanding of climate dynamics. In this paper, a climate system model and proxy records are therefore used to study the role of natural and anthropogenic forcings in driving the global climate. The inverse and forward approaches to paleoclimate data–model comparison are applied, and sources of uncertainty are identified and discussed. In the first of two case studies, the climate model simulations are compared with multiproxy temperature reconstructions. Robust solar and volcanic signals are detected in Southern Hemisphere temperatures, with a possible volcanic signal detected in the Northern Hemisphere. The anthropogenic signal dominates during the industrial period. It is also found that seasonal and geographical biases may cause multiproxy reconstructions to overestimate the magnitude of the long-term preindustrial cooling trend. In the second case study, the model simulations are compared with a coral δ18O record from the central Pacific Ocean. It is found that greenhouse gases, solar irradiance, and volcanic eruptions all influence the mean state of the central Pacific, but there is no evidence that natural or anthropogenic forcings have any systematic impact on El Niño–Southern Oscillation. The proxy climate relationship is found to change over time, challenging the assumption of stationarity that underlies the interpretation of paleoclimate proxies. These case studies demonstrate the value of paleoclimate data–model comparison but also highlight the limitations of current techniques and demonstrate the need to develop alternative approaches.
Resumo:
Growing evidence suggests environmental change to be most severe across the semi-arid subtropics, with past, present and projected drying of the Mediterranean Basin posing a key multidisciplinary challenge. Consideration of a single climatic factor, however, often fails to explain spatiotemporal growth dynamics of drought-prone ecosystems. Here, we present annually resolved and absolutely dated ring width measurements of 871 Scots pines (Pinus sylvestris) from 18 individual plot sites in the Central Spanish Pinar Grande forest reserve. Although comprising tree ages from 6 to 175 years, this network correlates surprisingly well with the inverse May–July diurnal temperature range (r = 0.84; p < 0.00011956–2011). Ring width extremes were triggered by pressure anomalies of the North Atlantic Oscillation, and the long-term growth decline coincided with Iberian-wide drying since the mid-1970s. Climate model simulations not only confirm this negative trend over the last decades but also project drought to continuously increase over the 21st century. Associated ecological effects and socio-economic consequences should be considered to improve adaptation strategies of agricultural and forest management, as well as biodiversity conservation and ecosystem service.
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This is the second part of a two-part paper which offers a new approach to the valuation of ecosystem goods and services. In the first part a simple pre-industrial model was introduced to show how the interdependencies between the three subsystems, society, economy and nature, influence values, and how values change over time. In this second part the assumption of perfect foresight is dropped. I argue that due to novelty and complexity ex ante unpredictable change occurs within the three subsystems society, economy and nature. Again the simple pre-industrial model, which was introduced in part 1, serves as a simple paradigm to show how unpredictable novel change limits the possibility to derive accurate estimates of values.
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Climate change mitigation policy is driven by scientific knowledge and involves actors from the international, national and local decision-making levels. This multi-level and cross-sectoral context requires collaborative management when designing mitigation solutions over time and space. But collaboration in general policymaking settings, and particularly in the complex domain of climate mitigation, is not an easy task. This paper addresses the question of what drives collaboration among collective actors involved in climate mitigation policy. We wish to investigate whether common beliefs or power structures influence collaboration among actors. We adopt a longitudinal approach to grasp differences between the early and more advanced stages of mitigation policy design. We use survey data to investigate actors’ collaboration, beliefs and power, and apply a Stochastic Actor-oriented Model for network dynamics to three subsequent networks in Swiss climate policy between 1995 and 2012. Results show that common beliefs among actors, as well as formal power structures, have a higher impact on collaboration relations than perceived power structures. Furthermore, those effects hold true for decision-making about initial mitigation strategies, but less so for the implementation of those measures.
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Mountain vegetation is strongly affected by temperature and is expected to shift upwards with climate change. Dynamic vegetation models are often used to assess the impact of climate on vegetation and model output can be compared with paleobotanical data as a reality check. Recent paleoecological studies have revealed regional variation in the upward shift of timberlines in the Northern and Central European Alps in response to rapid warming at the Younger Dryas/Preboreal transition ca. 11700years ago, probably caused by a climatic gradient across the Alps. This contrasts with previous studies that successfully simulated the early Holocene afforestation in the (warmer) Central Alps with a chironomid-inferred temperature reconstruction from the (colder) Northern Alps. We use LandClim, a dynamic landscape vegetation model to simulate mountain forests under different temperature, soil and precipitation scenarios around Iffigsee (2065m a.s.l.) a lake in the Northwestern Swiss Alps, and compare the model output with the paleobotanical records. The model clearly overestimates the upward shift of timberline in a climate scenario that applies chironomid-inferred July-temperature anomalies to all months. However, forest establishment at 9800 cal. BP at Iffigsee is successfully simulated with lower moisture availability and monthly temperatures corrected for stronger seasonality during the early Holocene. The model-data comparison reveals a contraction in the realized niche of Abies alba due to the prominent role of anthropogenic disturbance after ca. 5000 cal. BP, which has important implications for species distribution models (SDMs) that rely on equilibrium with climate and niche stability. Under future climate projections, LandClim indicates a rapid upward shift of mountain vegetation belts by ca. 500m and treeline positions of ca. 2500m a.s.l. by the end of this century. Resulting biodiversity losses in the alpine vegetation belt might be mitigated with low-impact pastoralism to preserve species-rich alpine meadows.
Resumo:
Carbon emissions from anthropogenic land use (LU) and land use change (LUC) are quantified with a Dynamic Global Vegetation Model for the past and the 21st century following Representative Concentration Pathways (RCPs). Wood harvesting and parallel abandonment and expansion of agricultural land in areas of shifting cultivation are explicitly simulated (gross LUC) based on the Land Use Harmonization (LUH) dataset and a proposed alternative method that relies on minimum input data and generically accounts for gross LUC. Cumulative global LUC emissions are 72 GtC by 1850 and 243 GtC by 2004 and 27–151 GtC for the next 95 yr following the different RCP scenarios. The alternative method reproduces results based on LUH data with full transition information within <0.1 GtC/yr over the last decades and bears potential for applications in combination with other LU scenarios. In the last decade, shifting cultivation and wood harvest within remaining forests including slash each contributed 19% to the mean annual emissions of 1.2 GtC/yr. These factors, in combination with amplification effects under elevated CO2, contribute substantially to future emissions from LUC in all RCPs.
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The evolution of the Atlantic Meridional Overturning Circulation (MOC) in 30 models of varying complexity is examined under four distinct Representative Concentration Pathways. The models include 25 Atmosphere-Ocean General Circulation Models (AOGCMs) or Earth System Models (ESMs) that submitted simulations in support of the 5th phase of the Coupled Model Intercomparison Project (CMIP5) and 5 Earth System Models of Intermediate Complexity (EMICs). While none of the models incorporated the additional effects of ice sheet melting, they all projected very similar behaviour during the 21st century. Over this period the strength of MOC reduced by a best estimate of 22% (18%–25%; 5%–95% confidence limits) for RCP2.6, 26% (23%–30%) for RCP4.5, 29% (23%–35%) for RCP6.0 and 40% (36%–44%) for RCP8.5. Two of the models eventually realized a slow shutdown of the MOC under RCP8.5, although no model exhibited an abrupt change of the MOC. Through analysis of the freshwater flux across 30°–32°S into the Atlantic, it was found that 40% of the CMIP5 models were in a bistable regime of the MOC for the duration of their RCP integrations. The results support previous assessments that it is very unlikely that the MOC will undergo an abrupt change to an off state as a consequence of global warming.
Resumo:
Transport of radioactive iodide 131I− in a structured clay loam soil under maize in a final growing phase was monitored during five consecutive irrigation experiments under ponding. Each time, 27 mm of water were applied. The water of the second experiment was spiked with 200 MBq of 131I− tracer. Its activity was monitored as functions of depth and time with Geiger-Müller (G-M) detectors in 11 vertically installed access tubes. The aim of the study was to widen our current knowledge of water and solute transport in unsaturated soil under different agriculturally cultivated settings. It was supposed that the change in 131I− activity (or counting rate) is proportional to the change in soil water content. Rapid increase followed by a gradual decrease in 131I− activity occurred at all depths and was attributed to preferential flow. The iodide transport through structured soil profile was simulated by the HYDRUS 1D model. The model predicted relatively deep percolation of iodide within a short time, in a good agreement with the observed vertical iodide distribution in soil. We found that the top 30 cm of the soil profile is the most vulnerable layer in terms of water and solute movement, which is the same depth where the root structure of maize can extend.
Resumo:
Species adapted to cold-climatic mountain environments are expected to face a high risk of range contractions, if not local extinctions under climate change. Yet, the populations of many endothermic species may not be primarily affected by physiological constraints, but indirectly by climate-induced changes of habitat characteristics. In mountain forests, where vertebrate species largely depend on vegetation composition and structure, deteriorating habitat suitability may thus be mitigated or even compensated by habitat management aiming at compositional and structural enhancement. We tested this possibility using four cold-adapted bird species with complementary habitat requirements as model organisms. Based on species data and environmental information collected in 300 1-km2 grid cells distributed across four mountain ranges in central Europe, we investigated (1) how species’ occurrence is explained by climate, landscape, and vegetation, (2) to what extent climate change and climate-induced vegetation changes will affect habitat suitability, and (3) whether these changes could be compensated by adaptive habitat management. Species presence was modelled as a function of climate, landscape and vegetation variables under current climate; moreover, vegetation-climate relationships were assessed. The models were extrapolated to the climatic conditions of 2050, assuming the moderate IPCC-scenario A1B, and changes in species’ occurrence probability were quantified. Finally, we assessed the maximum increase in occurrence probability that could be achieved by modifying one or multiple vegetation variables under altered climate conditions. Climate variables contributed significantly to explaining species occurrence, and expected climatic changes, as well as climate-induced vegetation trends, decreased the occurrence probability of all four species, particularly at the low-altitudinal margins of their distribution. These effects could be partly compensated by modifying single vegetation factors, but full compensation would only be achieved if several factors were changed in concert. The results illustrate the possibilities and limitations of adaptive species conservation management under climate change.
Resumo:
The potential and adaptive flexibility of population dynamic P-systems (PDP) to study population dynamics suggests that they may be suitable for modelling complex fluvial ecosystems, characterized by a composition of dynamic habitats with many variables that interact simultaneously. Using as a model a reservoir occupied by the zebra mussel Dreissena polymorpha, we designed a computational model based on P systems to study the population dynamics of larvae, in order to evaluate management actions to control or eradicate this invasive species. The population dynamics of this species was simulated under different scenarios ranging from the absence of water flow change to a weekly variation with different flow rates, to the actual hydrodynamic situation of an intermediate flow rate. Our results show that PDP models can be very useful tools to model complex, partially desynchronized, processes that work in parallel. This allows the study of complex hydroecological processes such as the one presented, where reproductive cycles, temperature and water dynamics are involved in the desynchronization of the population dynamics both, within areas and among them. The results obtained may be useful in the management of other reservoirs with similar hydrodynamic situations in which the presence of this invasive species has been documented.
Resumo:
Lumbar spinal instability (LSI) is a common spinal disorder and can be associated with substantial disability. The concept of defining clinically relevant classifications of disease or 'target condition' is used in diagnostic research. Applying this concept to LSI we hypothesize that a set of clinical and radiological criteria can be developed to identify patients with this target condition who are at high risk of 'irreversible' decompensated LSI for whom surgery becomes the treatment of choice. In LSI, structural deterioration of the lumbar disc initiates a degenerative cascade of segmental instability. Over time, radiographic signs become visible: traction spurs, facet joint degeneration, misalignment, stenosis, olisthesis and de novo scoliosis. Ligaments, joint capsules, local and distant musculature are the functional elements of the lumbar motion segment. Influenced by non-functional factors, these functional elements allow a compensation of degeneration of the motion segment. Compensation may happen on each step of the degenerative cascade but cannot reverse it. However, compensation of LSI may lead to an alleviation or resolution of clinical symptoms. In return, the target condition of decompensation of LSI may cause the new occurrence of symptoms and pain. Functional compensation and decompensation are subject to numerous factors that can change which makes estimation of an individual's long-term prognosis difficult. Compensation and decompensation may influence radiographic signs of degeneration, e.g. the degree of misalignment and segmental angulation caused by LSI is influenced by the tonus of the local musculature. This conceptual model of compensation/decompensation may help solve the debate on functional and psychosocial factors that influence low back pain and to establish a new definition of non-specific low back pain. Individual differences of identical structural disorders could be explained by compensated or decompensated LSI leading to changes in clinical symptoms and pain. Future spine surgery will have to carefully define and measure functional aspects of LSI, e.g. to identify a point of no return where multidisciplinary interventions do not allow a re-compensation and surgery becomes the treatment of choice.
Resumo:
Existing evidence of plant phenological change to temperature increase demonstrates that the phenological responsiveness is greater at warmer locations and in early-season plant species. Explanations of these findings are scarce and not settled. Some studies suggest considering phenology as one functional trait within a plant's life history strategy. In this study, we adapt an existing phenological model to derive a generalized sensitivity in space (SpaceSens) model for calculating temperature sensitivity of spring plant phenophases across species and locations. The SpaceSens model have three parameters, including the temperature at the onset date of phenophases (Tp), base temperature threshold (Tb) and the length of period (L) used to calculate the mean temperature when performing regression analysis between phenology and temperature. A case study on first leaf date of 20 plant species from eastern China shows that the change of Tp and Tb among different species accounts for interspecific difference in temperature sensitivity. Moreover, lower Tp at lower latitude is the main reason why spring phenological responsiveness is greater there. These results suggest that spring phenophases of more responsive, early-season plants (especially in low latitude) will probably continue to diverge from the other late-season plants with temperatures warming in the future.