A mechanistic-bioclimatic modeling analysis of the potential impact of climate change on biomes of the Tibetan Plateau

Predicting community traits along an alpine grassland transect using field imaging spectroscopy

Assessing plant community traits is important for understanding how terrestrial ecosystems respond and adapt to global climate change. Field hyperspectral remote sensing is effective for quantitatively estimating vegetation properties in most terrestrial ecosystems, although it remains to be tested in areas with dwarf and sparse vegetation, such as the Tibetan Plateau. We measured canopy reflectance in the Tibetan Plateau using a handheld imaging spectrometer and conducted plant community investigations along an alpine grassland transect. We estimated community structural and functional traits, as well as community function based on a field survey and laboratory analysis using 14 spectral vegetation indices (VIs) derived from hyperspectral images. We quantified the contributions of environmental drivers, VIs, and community traits to community function by structural equation modelling (SEM). Univariate linear regression analysis showed that plant community traits are best predicted by the normalized difference vegetation index, enhanced vegetation index, and simple ratio. Structural equation modelling showed that VIs and community traits positively affected community function, whereas environmental drivers and specific leaf area had the opposite effect. Additionally, VIs integrated with environmental drivers were indirectly linked to community function by characterizing the variations in community structural and functional traits. This study demonstrates that community-level spectral reflectance will help scale plant trait information measured at the leaf level to larger-scale ecological processes. Field imaging spectroscopy represents a promising tool to predict the responses of alpine grassland communities to climate change.

Climate change and primary production: Forty years in a bunchgrass prairie

Over the past 109 years, a Montana intermountain bunchgrass prairie annually became warmer (0.7°C) and drier (27%). The temperature and precipitation trends continued since 1978, as we studied nitrogen availability, annual aboveground primary production (ANPP), plant phenology and species composition. Given the annual increase in temperature and decrease in precipitation, ANPP might be expected to decline; however, it increased by 110%, as the period of greatest production (late-May-June) became wetter and cooler, counter to the annual pattern, and this was strongest at lower elevations. Grass production increased by 251%, while dicot production declined by 65%, which increased grass relative abundance by 54%. Summer temperatures increased 12.5% which increased plant senescence by 119% and decreased fall plant regrowth by 68%. More intense summer senescence changed plant species composition in favor of more drought tolerant species. The greater ANPP and summer senescence may increase susceptibility for fire, but fire tolerance of the plant species composition did not change. Invasive plant species increased 108% over the study with annual grasses accounting for >50% of this increase, which further increased summer plant senescence. Therefore, seasonal climate changes at a smaller geographical scale (local), rather than average annual climate changes over a larger geographical scale (regional), may better reflect plant community responses, and this makes ecological forecasting of climate change more difficult.

Indirect effects of water availability in driving and predicting productivity in the Gobi desert

Climate is the fundamental determinant of plant metabolism and net primary productivity (NPP). However, whether climate drives NPP directly or indirectly is not well understand. The Gobi desert across a precipitation gradient in the arid zone provides an ideal naturally-controlled platform for studying the precipitation-productivity relationships. We conducted 3-year experiments in four Gobi desert shrublands across an aridity gradient in Gansu Province of China to test the relationship between water availability and shrub productivity as well as the relative importance of the possible factors driving productivity (using piecewise structural equation modeling) and to explore the appropriate variables for predicting productivity (using three spatial models). The results showed that water availability indirectly affected the NPP via stand biomass, while stand biomass had a significant direct effect on NPP regardless of whether the leaf water content and stand height were considered. The model based on stand size (71.6%) and the model that contained both stand size and water availability (72.3%) explained more of the variation in the water-NPP relationships than the model based on water availability (37.3%). Our findings suggest that even in extremely water-limited areas, the effects of water availability on plant growth and the kinetics of plant metabolism could be indirect via plant size, demonstrating the importance of plant size as an indicator of shrub productivity. This study explains the mechanisms underlying the NPP driving pattern and proposes a practical NPP model for arid ecosystems.

Increasing microbial carbon use efficiency with warming predicts soil heterotrophic respiration globally

The degree to which climate warming will stimulate soil organic carbon (SOC) losses via heterotrophic respiration remains uncertain, in part because different or even opposite microbial physiology and temperature relationships have been proposed in SOC models. We incorporated competing microbial carbon use efficiency (CUE)-mean annual temperature (MAT) and enzyme kinetic-MAT relationships into SOC models, and compared the simulated mass-specific soil heterotrophic respiration rates with multiple published datasets of measured respiration. The measured data included 110 dryland soils globally distributed and two continental to global-scale cross-biome datasets. Model-data comparisons suggested that a positive CUE-MAT relationship best predicts the measured mass-specific soil heterotrophic respiration rates in soils distributed globally. These results are robust when considering models of increasing complexity and competing mechanisms driving soil heterotrophic respiration-MAT relationships (e.g., carbon substrate availability). Our findings suggest that a warmer climate selects for microbial communities with higher CUE, as opposed to the often hypothesized reductions in CUE by warming based on soil laboratory assays. Our results help to build the impetus for, and confidence in, including microbial mechanisms in soil biogeochemical models used to forecast changes in global soil carbon stocks in response to warming.

Under which climate and soil conditions the plant productivity-precipitation relationship is linear or nonlinear?

Understanding under which climate and soil conditions the plant productivity-precipitation relationship is linear or nonlinear is useful for accurately predicting the response of ecosystem function to global environmental change. Using long-term (2000-2016) net primary productivity (NPP)-precipitation datasets derived from satellite observations, we identify >5600pixels in the North Hemisphere landmass that fit either linear or nonlinear temporal NPP-precipitation relationships. Differences in climate (precipitation, radiation, ratio of actual to potential evapotranspiration, temperature) and soil factors (nitrogen, phosphorous, organic carbon, field capacity) between the linear and nonlinear types are evaluated. Our analysis shows that both linear and nonlinear types exhibit similar interannual precipitation variabilities and occurrences of extreme precipitation. Permutational multivariate analysis of variance suggests that linear and nonlinear types differ significantly regarding to radiation, ratio of actual to potential evapotranspiration, and soil factors. The nonlinear type possesses lower radiation and/or less soil nutrients than the linear type, thereby suggesting that nonlinear type features higher degree of limitation from resources other than precipitation. This study suggests several factors limiting the responses of plant productivity to changes in precipitation, thus causing nonlinear NPP-precipitation pattern. Precipitation manipulation and modeling experiments should combine with changes in other climate and soil factors to better predict the response of plant productivity under future climate.

Bacterial responses to environmental change on the Tibetan Plateau over the past half century

Climate change and anthropogenic factors can alter biodiversity and can lead to changes in community structure and function. Despite the potential impacts, no long-term records of climatic influences on microbial communities exist. The Tibetan Plateau is a highly sensitive region that is currently undergoing significant alteration resulting from both climate change and increased human activity. Ice cores from glaciers in this region serve as unique natural archives of bacterial abundance and community composition, and contain concomitant records of climate and environmental change. We report high-resolution profiles of bacterial density and community composition over the past half century in ice cores from three glaciers on the Tibetan Plateau. Statistical analysis showed that the bacterial community composition in the three ice cores converged starting in the 1990s. Changes in bacterial community composition were related to changing precipitation, increasing air temperature and anthropogenic activities in the vicinity of the plateau. Collectively, our ice core data on bacteria in concert with environmental and anthropogenic proxies indicate that the convergence of bacterial communities deposited on glaciers across a wide geographical area and situated in diverse habitat types was likely induced by climatic and anthropogenic drivers.