Accounting for tree line shift, glacier retreat and primary succession in mountain plant distribution models

Multi-level determinants of land use land cover change in Tigray, Ethiopia: A mixed-effects approach using socioeconomic panel and satellite data

This study examined land use land cover change and its determinants in Tigray, Ethiopia and its livelihood zones. We used socioeconomic panel, and satellite data, and applied a mixed-effects model to analyse the factors influencing land allocation among different uses, and transition matrix to analyse land cover dynamics. The results revealed that; land use choices were influenced by plot level factors (such as plot elevation, distance, soil type and quality, and land tenure), household characteristics (such as education, dependency ratio, plot size and number owned, income, livestock and asset, perception of climate change, and access to market and main road), and community level factors (precipitation, product price, population density and livelihood zone variations). Transition matrix analysis showed that between 1986 and 2016, 12.8% of forest was converted to bare land, 6.26% bare land was converted to pasture, and 5.84% of cropland was converted to forest. However, net deforestation occurred in most of the livelihood zones. Therefore, local communities faced environmental and socio-economic challenges from capital constraints induced land fallowing, land fragmentation, and unmanaged land cover change. The study recommended sustainable land use planning and management, market linkages, improved access to roads, forestry subsidies, land tenure security, and land consolidation programs.

Topoclimate effect on treeline elevation depends on the regional framework: A contrast between Southern Alps (New Zealand) and Apennines (Italy) forests

Deciphering the spatial patterns of alpine treelines is critical for understanding the ecosystem processes involved in the persistence of tree species and their altitudinal limit. Treelines are thought to be controlled by temperature, and other environmental variables but they have rarely been investigated in regions with different land-use change legacies. Here, we systematically investigated treeline elevation in the Apennines (Italy) and Southern Alps (New Zealand) with contrasting human history but similar biogeographic trajectories, intending to identify distinct drivers that affect their current elevation and highlight their respective peculiarities. Over 3622 km of Apennines, treeline elevation was assessed in 302 mountain peaks and in 294 peaks along 4504 km of Southern Alps. The major difference between the Southern Alps and Apennines treeline limit is associated with their mountain aspects. In the Southern Alps, the scarcely anthropized Nothofagus treeline elevation was higher on the warmer equator-facing slopes than on the pole-facing ones. Contrary to what would be expected based on temperature limitation, the elevation of Fagus sylvatica treelines in the Apennines was higher on colder, pole-facing slopes than on human-shaped equator-facing, warmer mountainsides. Pervasive positive correlations were found between treeline elevation and temperature in the Southern Alps but not in the Apennines. While the position of the Fagus and Nothofagus treelines converge on similar isotherms of annual average temperature, a striking isothermal difference between the temperatures of the hottest month on which the two taxonomic groups grow exists. We conclude that actual treeline elevation reflects the ecological processes driven by a combination of local-scale topoclimatic conditions, and human disturbance legacy. Predicting dynamic processes affecting current and future alpine treeline position requires further insight into the modulating influences that are currently understood at a regional scale.

Tree Line Identification and Dynamics under Climate Change in Wuyishan National Park Based on Landsat Images

The alpine tree line ecotone, reflecting interactions between climate and ecology, is very sensitive to climate change. To identify tree line responses to climate change, including intensity and local variations in tree line advancement, the use of Landsat images with long-term data series and fine spatial resolution is an option. However, it is a challenge to extract tree line data from Landsat images due to classification issues with outliers and temporal inconsistency. More importantly, direct classification results in sharp boundaries between forest and non-forest pixels/segments instead of representing the tree line ecotone (three ecological regions—tree species line, tree line, and timber line—are closely related to the tree line ecotone and are all significant for ecological processes). Therefore, it is important to develop a method that is able to accurately extract the tree line from Landsat images with a high temporal consistency and to identify the appropriate ecological boundary. In this study, a new methodology was developed based on the concept of a local indicator of spatial autocorrelation (LISA) to extract the tree line automatically from Landsat images. Tree line responses to climate change from 1987 to 2018 in Wuyishan National Park, China, were evaluated, and topographic effects on local variations in tree line advancement were explored. The findings supported the methodology based on the LISA concept as a valuable classifier for assessing the local spatial clusters of alpine meadows from images acquired in nongrowing seasons. The results showed that the automatically extracted line from Landsat images was the timber line due to the restriction in spatial autocorrelation. The results also indicate that parts of the tree line in the study area shifted upward vertically by 50 m under a 1 °C temperature increase during the period from 1987 to 2018, with local variations influenced by slope, elevation, and interactions with aspect. Our study contributes a novel result regarding the response of the alpine tree line to global warming in a subtropical region. Our method for automatic tree line extraction can provide fundamental information for ecosystem managers.

Climate-human interactions contributed to historical forest recruitment dynamics in Mediterranean subalpine ecosystems

Long-term tree recruitment dynamics of subalpine forests mainly depend on temperature changes, but little is known about the feedbacks between historical land use and climate. Here, we analyze a southern European, millennium-long dataset of tree recruitment from three high-elevation pine forests located in Mediterranean mountains (Pyrenees, northeastern Spain; Pollino, southern Italy; and Mt. Smolikas, northern Greece). We identify synchronized recruitment peaks in the late 15th and early 16th centuries, following prolonged periods of societal and climate instability. Major European population crises in the 14th and 15th centuries associated with recurrent famines, the Black Death pandemic, and political turmoil are likely to have reduced the deforestation of subalpine environments and caused widespread rewilding. We suggest that a distinct cold phase in the Little Ice Age around 1450 ce could also have accelerated the cessation of grazing pressure, particularly in the Pyrenees, where the demographic crisis was less severe. Most pronounced in the Pyrenees, the enhanced pine recruitment from around 1500-1550 ce coincides with temporarily warmer temperatures associated with a positive phase of the North Atlantic Oscillation. We diagnose that a mixture of human and climate factors has influenced past forest recruitment dynamics in Mediterranean subalpine ecosystems. Our results highlight how complex human-climate interactions shaped forest dynamics during pre-industrial times and provide historical analogies to recent rewilding.

Diversity and community structure of ectomycorrhizal fungi associated with Larix chinensis across the alpine treeline ecotone of Taibai Mountain

Alpine treeline ecotones represent ecosystems that are vulnerable to climate change. We investigated the ectomycorrhizal (ECM) community, which has potential to stabilize alpine ecosystems. ECM communities associated with Larix chinensis were studied in four zones along a natural ecotone from a mixed forest stand over pure forest stands, the timberline, and eventually, the treeline (3050-3450 m) in Tabai Mountain, China. Sixty operational taxonomic units (OTUs) of ECM fungi were identified by sequencing the rDNA internal transcribed spacer of ECM tips. The richness of ECM species increased with elevation. The soil C/N ratio was the most important factor explaining ECM species richness. The treeline zone harbored some unique ECM fungi whereas no unique genera were observed in the timberline and pure forest zone. Elevation and topography were equally important factors influencing ECM communities in the alpine region. We suggest that a higher diversity of the ECM fungal community associated with L. chinensis in the treeline zone could result from niche differentiation.

Modelling snow cover duration improves predictions of functional and taxonomic diversity for alpine plant communities

BACKGROUND AND AIMS

Quantifying relationships between snow cover duration and plant community properties remains an important challenge in alpine ecology. This study develops a method to estimate spatial variation in energy availability in the context of a topographically complex, high-elevation watershed, which was used to test the explanatory power of environmental gradients both with and without snow cover in relation to taxonomic and functional plant diversity.

METHODS

Snow cover in the French Alps was mapped at 15-m resolution using Landsat imagery for five recent years, and a generalized additive model (GAM) was fitted for each year linking snow to time and topography. Predicted snow cover maps were combined with air temperature and solar radiation data at daily resolution, summed for each year and averaged across years. Equivalent growing season energy gradients were also estimated without accounting for snow cover duration. Relationships were tested between environmental gradients and diversity metrics measured for 100 plots, including species richness, community-weighted mean traits, functional diversity and hyperspectral estimates of canopy chlorophyll content.

KEY RESULTS

Accounting for snow cover in environmental variables consistently led to improved predictive power as well as more ecologically meaningful characterizations of plant diversity. Model parameters differed significantly when fitted with and without snow cover. Filtering solar radiation with snow as compared without led to an average gain in R(2) of 0·26 and reversed slope direction to more intuitive relationships for several diversity metrics.

CONCLUSIONS

The results show that in alpine environments high-resolution data on snow cover duration are pivotal for capturing the spatial heterogeneity of both taxonomic and functional diversity. The use of climate variables without consideration of snow cover can lead to erroneous predictions of plant diversity. The results further indicate that studies seeking to predict the response of alpine plant communities to climate change need to consider shifts in both temperature and nival regimes.

Potential Effects of Climate Change on the Distribution of Cold-Tolerant Evergreen Broadleaved Woody Plants in the Korean Peninsula

Climate change has caused shifts in species' ranges and extinctions of high-latitude and altitude species. Most cold-tolerant evergreen broadleaved woody plants (shortened to cold-evergreens below) are rare species occurring in a few sites in the alpine and subalpine zones in the Korean Peninsula. The aim of this research is to 1) identify climate factors controlling the range of cold-evergreens in the Korean Peninsula; and 2) predict the climate change effects on the range of cold-evergreens. We used multimodel inference based on combinations of climate variables to develop distribution models of cold-evergreens at a physiognomic-level. Presence/absence data of 12 species at 204 sites and 6 climatic factors, selected from among 23 candidate variables, were used for modeling. Model uncertainty was estimated by mapping a total variance calculated by adding the weighted average of within-model variation to the between-model variation. The range of cold-evergreens and model performance were validated by true skill statistics, the receiver operating characteristic curve and the kappa statistic. Climate change effects on the cold-evergreens were predicted according to the RCP 4.5 and RCP 8.5 scenarios. Multimodel inference approach excellently projected the spatial distribution of cold-evergreens (AUC = 0.95, kappa = 0.62 and TSS = 0.77). Temperature was a dominant factor in model-average estimates, while precipitation was minor. The climatic suitability increased from the southwest, lowland areas, to the northeast, high mountains. The range of cold-evergreens declined under climate change. Mountain-tops in the south and most of the area in the north remained suitable in 2050 and 2070 under the RCP 4.5 projection and 2050 under the RCP 8.5 projection. Only high-elevations in the northeastern Peninsula remained suitable under the RCP 8.5 projection. A northward and upper-elevational range shift indicates change in species composition at the alpine and subalpine ecosystems in the Korean Peninsula.