Uncertainty analysis of vegetation distribution in the northern high latitudes during the 21st century with a dynamic vegetation model

Climate change threatens the distribution of major woody species and ecosystem services provision in southern Africa

In southern Africa, woody vegetation provides essential ecological, regulation, and cultural ecosystem services (ES), yet many species and ecosystems are increasingly threatened by climate change and land-use transformations. We investigated the effect of climate change on the distribution of eight species in 18 countries in southern Africa, covering 36% of the continent. We proposed a loser/winner ranking of the species based on the changes in land climatic suitability within their historical distribution and future gains and losses of suitable areas. We interpreted these findings in terms of changes in key ES (timber, food, and energy) provision and identified hotspots of ES provision decline. We used species presence data from the Global Biodiversity Information Facility, climatic data from the AfriClim dataset, and the MaxEnt algorithm to project the changes in species-specific land climatic suitability. Among the eight investigated species, the baseline suitability range of Mopane (Colophosperm mopane) was least affected by climate change. At the same time, the area of its future distribution was projected to double, rendering it a regional winner. Another two species, manketti (Schinziophyton rautanenii) and leadwood (Combretum imberbe) showed high future gains too; however, the impact on their baseline suitability range differed between the climatic scenarios. The baseline range of African rosewood (Guibourtia coleosperma) declined entirely, and the future gains were negligible, rendering the species a regional loser. The effect of climate change was particularly severe on timber-producing species (four out of eight species), while species providing food (four species) and energy (four species) were affected less. Our projections portrayed distinct hotspot and coldspot areas, where climatic suitability for multiple species was concurrently projected to decline or persist. This assessment can inform spatially targeted adaptation and conservation actions and strategies, which are currently lacking in many African regions.

The Influence of Climate Change on Three Dominant Alpine Species under Different Scenarios on the Qinghai–Tibetan Plateau

The Qinghai–Tibetan Plateau (QTP) with high altitude and low temperature is one of the most sensitive areas to climate change and has recently experienced continuous warming. The species distribution on the QTP has undergone significant changes especially an upward shift with global warming in the past decades. In this study, two dominant trees (Picea crassifolia Kom and Sabina przewalskii Kom) and one dominant shrub (Potentilla parvifolia Fisch) were selected and their potential distributions using the MaxEnt model during three periods (current, the 2050s and the 2070s) were predicted. The predictions were based on four shared socio-economic pathway (SSPs) scenarios, namely, SSP2.6, SSP4.5, SSP7.0, SSP8.5. The predicted current potential distribution of three species was basically located in the northeastern of QTP, and the distribution of three species was most impacted by aspect, elevation, temperature seasonality, annual precipitation, precipitation of driest month, Subsoil CEC (clay), Subsoil bulk density and Subsoil CEC (soil). There were significant differences in the potential distribution of three species under four climate scenarios in the 2050s and 2070s including expanding, shifting, and shrinking. The total suitable habitat for Picea crassifolia shrank under SSP2.6, SSP4.5, SSP7.0 and enlarged under SSP8.5 in the 2070s. On the contrary, the total suitable habitat for Sabina przewalskii enlarged under SSP2.6, SSP4.5, SSP7.0 and shrank under SSP8.5 in the 2070s. The total suitable habitat for Potentilla parvifolia continued to increase with SSP2.6 to SSP8.5 in the 2070s. The average elevation in potentially suitable habitat for Potentilla parvifolia all increased except under SSP8.5 in the 2050s. Our study provides an important reference for the conservation of Picea crassifolia, Sabina przewalskii, Potentilla parvifolia and other dominant plant species on the QTP under future climate change.

Predicting Soil Respiration from Plant Productivity (NDVI) in a Sub-Arctic Tundra Ecosystem

Soils represent the largest store of carbon in the biosphere with soils at high latitudes containing twice as much carbon (C) than the atmosphere. High latitude tundra vegetation communities show increases in the relative abundance and cover of deciduous shrubs which may influence net ecosystem exchange of CO2 from this C-rich ecosystem. Monitoring soil respiration (Rs) as a crucial component of the ecosystem carbon balance at regional scales is difficult given the remoteness of these ecosystems and the intensiveness of measurements that is required. Here we use direct measurements of Rs from contrasting tundra plant communities combined with direct measurements of aboveground plant productivity via Normalised Difference Vegetation Index (NDVI) to predict soil respiration across four key vegetation communities in a tundra ecosystem. Soil respiration exhibited a nonlinear relationship with NDVI (y = 0.202e3.508 x, p < 0.001). Our results further suggest that NDVI and soil temperature can help predict Rs if vegetation type is taken into consideration. We observed, however, that NDVI is not a relevant explanatory variable in the estimation of SOC in a single-study analysis.

Modeling long-term changes in tundra carbon balance following wildfire, climate change, and potential nutrient addition

To investigate the underlying mechanisms that control long-term recovery of tundra carbon (C) and nutrients after fire, we employed the Multiple Element Limitation (MEL) model to simulate 200-yr post-fire changes in the biogeochemistry of three sites along a burn severity gradient in response to increases in air temperature, CO₂ concentration, nitrogen (N) deposition, and phosphorus (P) weathering rates. The simulations were conducted for severely burned, moderately burned, and unburned arctic tundra. Our simulations indicated that recovery of C balance after fire was mainly determined by the internal redistribution of nutrients among ecosystem components (controlled by air temperature), rather than the supply of nutrients from external sources (e.g., nitrogen deposition and fixation, phosphorus weathering). Increases in air temperature and atmospheric CO₂ concentration resulted in (1) a net transfer of nutrient from soil organic matter to vegetation and (2) higher C : nutrient ratios in vegetation and soil organic matter. These changes led to gains in vegetation biomass C but net losses in soil organic C stocks. Under a warming climate, nutrients lost in wildfire were difficult to recover because the warming-induced acceleration in nutrient cycles caused further net nutrient loss from the system through leaching. In both burned and unburned tundra, the warming-caused acceleration in nutrient cycles and increases in ecosystem C stocks were eventually constrained by increases in soil C : nutrient ratios, which increased microbial retention of plant-available nutrients in the soil. Accelerated nutrient turnover, loss of C, and increasing soil temperatures will likely result in vegetation changes, which further regulate the long-term biogeochemical succession. Our analysis should help in the assessment of tundra C budgets and of the recovery of biogeochemical function following fire, which is in turn necessary for the maintenance of wildlife habitat and tundra vegetation.

Modeling carbon-nutrient interactions during the early recovery of tundra after fire

Fire frequency has dramatically increased in the tundra of northern Alaska, USA, which has major implications for the carbon budget of the region and the functioning of these ecosystems, which support important wildlife species. We investigated the postfire succession of plant and soil carbon (C), nitrogen (N), and phosphorus (P) fluxes and stocks along a burn severity gradient in the 2007 Anaktuvuk River fire scar in northern Alaska. Modeling results indicated that the early regrowth of postfire tundra vegetation was limited primarily by its canopy photosynthetic potential, rather than nutrient availability, because of the initially low leaf area and relatively high inorganic N and P concentrations in soil. Our simulations indicated that the postfire recovery of tundra vegetation was sustained predominantly by the uptake of residual inorganic N (i.e., in the remaining ash), and the redistribution of N and P from soil organic matter to vegetation. Although residual nutrients in ash were higher in the severe burn than the moderate burn, the moderate burn recovered faster because of the higher remaining biomass and consequent photosynthetic potential. Residual nutrients in ash allowed both burn sites to recover and exceed the unburned site in both aboveground biomass and production five years after the fire. The investigation of interactions among postfire C, N, and P cycles has contributed to a mechanistic understanding of the response of tundra ecosystems to fire disturbance. Our study provided insight on how the trajectory of recovery of tundra from wildfire is regulated during early succession.

Plant functional types in Earth system models: past experiences and future directions for application of dynamic vegetation models in high-latitude ecosystems

BACKGROUND

Earth system models describe the physical, chemical and biological processes that govern our global climate. While it is difficult to single out one component as being more important than another in these sophisticated models, terrestrial vegetation is a critical player in the biogeochemical and biophysical dynamics of the Earth system. There is much debate, however, as to how plant diversity and function should be represented in these models.

SCOPE

Plant functional types (PFTs) have been adopted by modellers to represent broad groupings of plant species that share similar characteristics (e.g. growth form) and roles (e.g. photosynthetic pathway) in ecosystem function. In this review, the PFT concept is traced from its origin in the early 1800s to its current use in regional and global dynamic vegetation models (DVMs). Special attention is given to the representation and parameterization of PFTs and to validation and benchmarking of predicted patterns of vegetation distribution in high-latitude ecosystems. These ecosystems are sensitive to changing climate and thus provide a useful test case for model-based simulations of past, current and future distribution of vegetation.

CONCLUSIONS

Models that incorporate the PFT concept predict many of the emerging patterns of vegetation change in tundra and boreal forests, given known processes of tree mortality, treeline migration and shrub expansion. However, representation of above- and especially below-ground traits for specific PFTs continues to be problematic. Potential solutions include developing trait databases and replacing fixed parameters for PFTs with formulations based on trait co-variance and empirical trait-environment relationships. Surprisingly, despite being important to land-atmosphere interactions of carbon, water and energy, PFTs such as moss and lichen are largely absent from DVMs. Close collaboration among those involved in modelling with the disciplines of taxonomy, biogeography, ecology and remote sensing will be required if we are to overcome these and other shortcomings.