How much does climate change threaten European forest tree species distributions?

Abstract

Although numerous species distribution models have been developed, most were based on insufficient distribution data or used older climate change scenarios. We aimed to quantify changes in projected ranges and threat level by the years 2061-2080, for 12 European forest tree species under three climate change scenarios. We combined tree distribution data from the Global Biodiversity Information Facility, EUFORGEN, and forest inventories, and we developed species distribution models using MaxEnt and 19 bioclimatic variables. Models were developed for three climate change scenarios-optimistic (RCP2.6), moderate (RCP4.5), and pessimistic (RPC8.5)-using three General Circulation Models, for the period 2061-2080. Our study revealed different responses of tree species to projected climate change. The species may be divided into three groups: "winners"-mostly late-successional species: Abies alba, Fagus sylvatica, Fraxinus excelsior, Quercus robur, and Quercus petraea; "losers"-mostly pioneer species: Betula pendula, Larix decidua, Picea abies, and Pinus sylvestris; and alien species-Pseudotsuga menziesii, Quercus rubra, and Robinia pseudoacacia, which may be also considered as "winners." Assuming limited migration, most of the species studied would face a significant decrease in suitable habitat area. The threat level was highest for species that currently have the northernmost distribution centers. Ecological consequences of the projected range contractions would be serious for both forest management and nature conservation.

Functional response of Quercus robur L. to taproot pruning: a 5-year case study

“…Significance level p <0.05 is matched as italics SLA specific leaf area, SSL specific stem length, SRL specific root length, LMF leaf mass fraction, SMF stem mass fraction, RMF root mass fraction, fRMF fine root mass fraction, TNC total non-structural carbohydrates environmental changes than seedlings of other species (Dyderski et al 2017). SLA specific leaf area, SSL specific stem length, SRL specific root length, LMF leaf mass fraction, SMF stem mass fraction, RMF root mass fraction, fRMF fine root mass fraction Significance level p <0.05 is matched as italics …”

“…This is especially important to consider since the demands of aerial portions of a plant for nutrients and water will not be met by a reduced root system. Given that anticipated changes in climate, particularly in water availability, will have striking effects on the environmental conditions to which plants are exposed (Dyderski et al 2017), additional research should focus on determining whether or not root pruning exacerbates water and nutrient stress.…”

“…Pedunculate oak (Quercus robur L.) is an economically important tree species that is widely distributed in Europe (Köble and Seufert 2001), although the future range of this species may change distinctly within the next 50 years (Dyderski et al 2017). Poor tree survival in oak plantations has been frequently linked to restricted access to soil nutrients and the poor quality of seedlings grown in forest nurseries (Retana et al 1999;Tsakaldimi et al 2005;Valdecantos et al 2006).…”

Advantages of mixed tree stands in restoration of upper soil layers on postmining sites: A five‐year leaf litter decomposition experiment

“…Therefore, the question arises: Why is the highest share of European postindustrial sites afforested mainly with monocultures? Planting admixture species in a high share of stands improves ecosystem functionality (Horodecki & Jagodziński, ; Sroka et al, ) and enhances ecosystem subsistence because climate change‐mediated threats to single tree species existence have lesser impacts in mixed tree stands (Dyderski et al, ).…”

Niches and radiations: a case study on the Andean sapphire‐vented puffleg Eriocnemis luciani and coppery‐naped puffleg E. sapphiropygia (Aves, Trochilidae)

“…The interplay between the conservatism and divergence of niches in shaping lineage differentiation is far from completely understood (Pyron and Burbrink 2009, Peterson 2011, Hu et al 2015, despite its relevance for forecasting changes in biodiversity under changing environmental conditions or invasion risks (Hadly et al 2009, Hortal et al 2011, Lavergne et al 2013, Torres et al 2018. The use of ENMs has become instrumental in recent years (Lobo et al 2010) and is applied in a wide range of fields, such as those pertaining to geographic distributions (Ramoni-Perazzi et al 2012, 2017, past and potential future distributions in response to climate change (Dyderski et al 2018, Simpson et al 2018, Warren et al 2018, species invasions (Lins et al 2018, Oliveira et al 2018, diseases and agricultural pest organisms (Carmona-Castro et al 2018, Carvajal et al 2019, Marchioro and Krechemer 2018, biodiversity conservation priorities (Bonfim et al 2018), and even archaeology (Banks 2017, d'Errico et al 2017. The use of ENMs has become instrumental in recent years (Lobo et al 2010) and is applied in a wide range of fields, such as those pertaining to geographic distributions (Ramoni-Perazzi et al 2012, 2017, past and potential future distributions in response to climate change (Dyderski et al 2018, Simpson et al 2018, Warren et al 2018, species invasions (Lins et al 2018, Oliveira et al 2018, diseases and agricultural pest organisms (Carmona-Castro et al 2018, Carvajal et al 2019…”