Factors determining the treeline position
Treeline is a significant bioclimatic boundary for thermal life zones and aligns with the broader thermal constraints for temperate zone agriculture (Körner and Paulsen 2004). While altitudinal treelines are associated with decreasing temperatures at higher elevations (Wieser and Tausz 2007; Holtmeier 2009), there is less clarity about their underlying drivers (Grace 2002; Richardson and Friedland 2009). Our findings corroborate the results of several researches suggesting that warm season temperatures, rather than cold season lows, primarily dictate the upper bounds of tree growth (Tranquillini 1979; Wieser and Tausz 2007; Harsch et al. 2009; Davis et al. 2020). This explains higher treeline positions in central (core) parts of mountains compared to their peripheries as well as in continental climates versus adjacent maritime regions (Malinovsky 1980; Wieser and Tausz 2007; Holtmeier 2009; Czajka et al. 2015b), given the positive impact of increased climate continentality on summer temperatures. We observe this phenomenon, which has been extensively documented in the Alps (Quervain 1904) and also in the Carpathians, where it manifests as an overall treeline elevation increase from west to east and from the peripheries to the cores of certain massifs (Malinovsky 1980; Czajka et al. 2015b).
We tested several suggestions regarding the driving factors behind climatic treelines in the case of Carpathians. Notably, temperature-related climatic variables are often strongly correlated, especially within a single region. This makes it difficult to single out the only “true” predictor of the climatic treeline. Our findings align with the threshold values of climatic variables suggested by several researchers. The mean July temperature recorded for our treeline parcels is 10.5⁰C (see Table 4, Appendix), which is close to the 10°C threshold suggested by the earlier authors (Grace 2002; Wieser and Tausz 2007; Richardson and Friedland 2009; Körner 2021). According to the model indicated in (Körner and Paulsen 2004), it corresponds to the tree root zone temperature of 8.5⁰C, in line with their lower boundary for the Alps (9.2 ± 0.7⁰C) and equal to the 8.5⁰C estimated for the boreal zone (Körner and Paulsen 2004). The mean growing season above 0.9°C temperature converted to root zone is 7⁰C, consistent with the average value reported for the Alps (7.0 ± 0.4⁰C) and with the global estimate of 6.7 ± 0.8⁰C as detailed in (Körner and Paulsen 2004). It is a little higher than the 6.4°C suggested in the later work by these authors (Körner et al. 2011).
Our findings are consistent with the notion that warm-season temperatures are predominant in governing the upper limits of tree growth (Tranquillini 1979; Wieser and Tausz 2007; Harsch et al. 2009). Our analysis revealed that the AGDD above 5°C, an indicator of cumulative heat during the warmest period of the year, exhibits the strongest correlation with treeline location in the Carpathians. The mean temperature of the warmest quarter was closely following in importance. This variable is more readily estimated and included in the standardized set of bioclimatic variables under the BIO10 code (Hijmans et al. 2005). Our findings align with the study of treeline changes in the northeastern United States, where AGDD was found to significantly account for variations in the extent of treeline advancement (Tourville et al. 2023). We do not, however, assert the universal applicability of these results. While it may be enticing to establish parameters and thresholds for climatic treelines that apply globally, it is probably unfeasible because actual biome distribution patterns are often divergent even under a fixed climate. Biome variations can emerge from diverse historical contexts, resulting in unique trait pools, differing ecosystem equilibrium states, and varied disturbance regimes (Higgins and Scheiter 2012; Moncrieff et al. 2016). However, the method that we apply for revealing the most relevant climatic factors determining treeline positions, namely – the identifications of the parcels of extant climatic treelines on high-resolution satellite images and the statistical analysis and machine learning modeling of the distribution of climatic variables within and outside these parcels – can be applied to other mountain regions as well. This would allow obtaining sufficiently large samples without the need to physically access remote locations in mountains with rugged terrain.
Many European mountains with relatively dense and long-lasting human presence now feature treelines significantly lower than the climatic limits for tree growth since forests were cut for fuel and construction material and cleared out for pastures (Holtmeier and Broll 2007; Weisberg et al. 2013; Vincze et al. 2017). Traces of human influence that shaped the Carpathian treelines date back as far as 4,200 years and intensified around 2,000 years ago (Vincze et al. 2017). Since medieval times, practices like transhumance in the Carpathian Mountains involved slash-and-burn techniques to expand grazing fields (Vincze et al. 2017). As a result, the actual (anthropogenic) treeline in the Carpathians is commonly located 250–300 m lower than the climatic treeline, sometimes descending below 1,000 m AMSL, particularly on shallow slopes above densely populated valleys (Malinovsky 1980). In some parts of the Carpathians, treelines of anthropogenic origin are formed by deciduous European beech forests (Weisberg, Shandra, and Becker 2013), similar to those in southern Europe where Fagus species treelines are depressed hundreds of meters below the climatic treeline (Körner and Paulsen 2004). The effects of anthropogenic influences on treelines can persist long after their cessation (Holtmeier and Broll 2007; Malanson et al. 2011; Körner 2021).
Some natural factors and disturbances interact with climatic factors to influence the location of treelines. Snow avalanches and debris flows significantly lower their position in susceptible concave terrain elements (Holtmeier and Broll 2007; Treml and Migoń 2015), while extremely convex and exposed terrain elements are not conducive to tree advancement either due to strong winds. Additionally, edaphic factors can affect treeline position, with treelines typically higher on carbonate rocks than on quartzite rocks and lower on coarse glacial deposits (Czajka et al. 2015b; Treml and Migoń 2015).
Treeline changes as a response to rising temperatures.
Warming temperatures lead to shifts in species' and ecosystems' distributions, with a global meta-analysis estimating an average uphill movement rate of 11.1 meters per decade (Chen et al. 2011). The floras and faunas of Central European mountains are particularly vulnerable to climate change due to narrow habitat tolerances and marginal habitats for many species (e.g., Thuiller et al. 2005). Treelines have been observed to shift upwards in many regions worldwide, including Europe, Asia, and North America (Holtmeier 2009; see bibliography for additional sources). A global meta-analysis of data from 166 treeline sites found that 52% had notably advanced since 1900 AD, with only two sites showing receded treelines, both with evidence of disturbance (Harsch et al. 2009). Another study reported the advancement of 67% of 438 altitudinal treeline sites (Hansson et al. 2021). Data analysis from two surveys in the Swiss Alps in 1979/1985 and 1992/1997 revealed 893 hectares of new forests above the former treeline, with a median upward shift of 28 meters (Gehrig-Fasel et al. 2007).
The Carpathian Mountains are no exception. A study comparing timberline altitudes in 2009 to those in 1964 on the south-facing slopes of the Babia Gora massif in the western Carpathians observed an upward progression of up to 30 meters (Czajka et al. 2015a), while (Szwagrzyk 2015) noticed the young age of spruce trees on its north slopes, suggesting recent advances in the treeline. A comparison of historical maps from the 1930s with recent Landsat images of the Ukrainian Carpathians revealed significant treeline advancement on the highest ridges (Martazinova et al., 2011). It is, however, unclear how much of these effects can be attributed to climate change as opposed to the regeneration of forests previously destroyed by human activity below the climatic treeline.
However, the observed changes are far more conservative than our projections of climatic treeline shifts, which, even under optimistic SSP scenarios, would typically rise by a few hundred meters. Apart from the accelerating nature of climate warming, this can be explained by the delayed ecological response, as trees have limited seed dispersal rates and require time to establish (Holtmeier and Broll 2007; Harsch et al. 2009; Holtmeier 2009; Smith et al. 2009). The extent to which the treeline lags behind climate change is debatable. While tree species migration rates were estimated to be less than 100 m per year, preventing them from occupying all suitable sites in Central and Northern Europe in the course of dispersion from the Last Glacial Maximum refugia (Svenning and Skov 2007), research on lake sediments in the central Alps near the modern treeline revealed a swift response of the treeline to climate changes at the Late Glacial-Holocene transition, suggesting that global warming could also trigger large-scale displacements of plant species and rapid upslope movements of the treeline (Tinner and Kaltenrieder 2005). Before the mid 20 century, tree radial stem increment noticeably decreased when approaching a treeline in the Swiss and Austrian Alps; by the end of the century, this relationship had almost vanished, indicating that these tree stands are now located far enough from the climatic treeline (Paulsen et al. 2000). Another study revealed that the rates of treeline advance reconstructed for study sites in the Canadian Rocky Mountains were much lower than expected based on changes in growing-season temperature, with a median percentage of observed versus expected movement of only 39% (Davis et al. 2020).
Our study focused, like most others, on changes in average temperatures. However, knowledge about the impacts of extreme weather events on changes in treelines remains patchy, and they are predicted to increase in intensity and frequency with climate change (Smith et al. 2009). Climate change will also affect other treeline-related factors, such as snow avalanches, which are predicted to decrease in frequency and severity in a warming climate. Lower avalanche activity due to climate warming has already led to the expansion of forested areas in some Carpathian valleys (Kaczka et al. 2015). A study in Romania revealed significant forest regeneration on former avalanche paths, accounting for approximately 50% of the total increase in forest surface area (Mihai et al. 2007). Nonlinear relations created by positive feedback loops could further complicate the response of treelines to climatic factors, possibly resulting in alternative stable states of forest and alpine vegetation and abrupt treeline transitions driven by internal ecosystem dynamics (Malanson et al. 2011). Elevated atmospheric CO2 concentrations could facilitate tree growth at treeline on their own through enhanced photosynthetic activity (Handa et al. 2005; Reyes-Fox et al. 2014), which could amplify and even outweigh the effects of predicted temperature increases (Higgins and Scheiter 2012).
If our assumption of the summer temperatures as the leading factor behind climatic treelines is valid, the drastic decrease in the climatic envelope for alpine ecosystems in the Carpathians should be expected by the end of the century. This means that the efforts for the conservation of alpine communities, including their endemic and endangered species, should be spatially directed towards the highest ridges and peaks in the Carpathians, in particular Tatras and the southern Carpathians, where favorable climatic conditions for these ecosystems would sustain for a longer while. It can be seen in Fig. 3 that different SSPs indeed make a difference, and the divergence of predicted areas above the climatic treeline for four SSPs tends to grow larger with time. This means that global measures to slow climate warming would mean a lot in taming down the detrimental effects of climate change on ecosystems.