Predicted climate change will increase the truffle cultivation potential in central Europe

Anthropogenic climate change is altering the elevational and latitudinal distributions of many ectomycorrhizal fungi, key components of ecosystems and agriculture. Shifts to higher latitudes and elevations are expected to continue, expanding or contracting species-specific habitats. Species distribution models (SDMs), including correlative and mechanistic approaches, are used to predict potential distributions under future climates. While correlative SDMs are simplistic and omit some ecological processes, they remain the most feasible approach for many species, including fungi. Environmental information can be synthesized from literature to parameterize knowledge-based niche models. This study focuses on Burgundy truffle (Tuber aestivum) and Périgord truffle (Tuber melanosporum). Burgundy truffle has a broad ecological range across Europe and may expand under climate change, whereas Périgord truffle is currently more restricted to Mediterranean climates but shows signs of northward migration attributed to warming. Given their high economic value and growing cultivation interest in central Europe, the study aims to: (1) review ecological requirements of both species; (2) model current (2020) and future (2050) cultivation potential in the Czech Republic; (3) discuss model uncertainties; and (4) outline implications for truffle cultivation under climate change.

The authors synthesized ecological requirements for Tuber aestivum and Tuber melanosporum from 57 scientific publications. Extracted variables included annual and seasonal temperatures, precipitation totals, elevational ranges, soil pH thresholds, and host tree associations. Numerical values from the literature were used to define each species’ viable ecological range as probability distributions, subsequently divided into five suitability classes (scores 1–5). Because both species require alkaline soils, pH > 7 was partitioned into five decimal intervals (7.00–7.09 up to >7.40) mapped to suitability classes. Relative importance weights for parameters were derived via a rank-sum multicriteria approach informed by expert judgment from the literature, prioritizing soil pH, annual climate means, January temperature (frost risk), July temperature and precipitation (summer drought), and elevation. The review also compiled host tree species known to associate with each truffle species for contextual interpretation, although hosts were not explicitly included in the suitability mapping.

Study area: Czech Republic (49–51°N, 12–19°E), encompassing diverse biogeographic zones and calcareous bedrock favorable for truffles (limestone karst, secondary/tertiary deposits, Quaternary sediments). Preferred soils: chernozems, phaeozems in low elevations (≤300–400 m a.s.l.), and calcareous leptosols. Climate data: Baseline (1989–2018) monthly, seasonal, and annual temperature means and precipitation totals were produced from 268 stations via regression kriging with altitude as predictor, gridded at 500×500 m. Bias at station locations was removed by adding delta values to reduce kriging error to zero. Future climate (2041–2060, expressed as 2050) was computed using delta-change applied to baseline at 500 m resolution for RCP2.6, RCP4.5, and RCP8.5, using an ensemble mean of five GCMs (BNU-ESM, CNRM-CM5, HadGEM2-ES, IPSL-CM5A-MR, MRI-CGCM3) pre-selected via an established evaluation method. Soil pH: Combined two national datasets: ~150,000 field pH measurements (mainly agricultural lowlands) and a typological map of ~100 soil units lacking pH. Field pH measurements were attributed to corresponding soil survey units, and for each typological unit the median pH of associated field measures was used to extrapolate pH over the country. This covered 64% of the territory at 500 m resolution. Elevation: National LIDAR-derived DEM (5×5 m original; aggregated to 500 m), used as a static proxy for climate. Truffle ecology and modelling: Literature-derived numeric ranges for each species’ ecological requirements (annual mean temperature, January and July temperatures, annual and summer precipitation, soil pH, elevation) were transformed to probability distributions and binned into five suitability classes (scores 1–5). Soil pH > 7 was divided into five decimal intervals mapped to classes. Multicriteria analysis assigned weights (rank-sum): soil pH 0.1842, annual mean temperature 0.1579, annual precipitation 0.1579, January temperature 0.1316, July temperature 0.1316, July precipitation 0.1316, elevation 0.1053. Weighted scores were summed to produce final suitability values, converted to percentages and classified into five suitability categories for mapping. Mapping and analysis: Overlay Algebra in ArcGIS Pro 2.3.0 was used to generate suitability maps for 2020 and 2050 under RCP2.6/4.5/8.5. Suitability areas (km²) for each class were quantified and differences relative to baseline were computed.

Ecological optima and ranges: - Burgundy truffle (T. aestivum): optimal annual temperature ~10 °C; July ~19.8 °C; January ~2.1 °C; annual precipitation ~700 mm with ~160 mm in summer; optimal soil pH ~7.5; grows across a broader temperature range (1.5–2.5× wider than Périgord) and is ~50% more tolerant to changes in summer precipitation; similar rainfall, elevation, and pH tolerance to Périgord overall. - Périgord truffle (T. melanosporum): optimal annual temperature ~12 °C; July ~20.5 °C; January ~3.8 °C; annual precipitation ~780 mm with at least ~140 mm in summer; favors soil pH ~8; typical elevation ~620 m a.s.l. Current (2020) Czech Republic suitability: - Burgundy: High suitability on ~14% of the country (8486 km²; 77% of cultivatable area). Very high: 2 km². Central Bohemia and southern Moravia show 50–80% suitability. - Périgord: Mostly low (~8%; 6418 km²) and moderate (~6%; 4482 km²) suitability; highest potential in southern Moravia (30–50%). Projected changes by 2050: - Burgundy (T. aestivum): • Total potential cultivation area changes slightly: +~98 km² (RCP2.6/4.5), −~57 km² (RCP8.5). • High suitability area: +250 km² (+3%) under RCP2.6; −39 km² (−1.5%) under RCP4.5; −572 km² (−7%) under RCP8.5. • Very high suitability increases from 2 km² to 141–197 km² across scenarios. • Annual rate of suitability change ~−4 km² yr⁻¹ from 2020 to 2050 (slow change). - Périgord (T. melanosporum): • Suitable land expands much faster: ~83 km² yr⁻¹ (nearly 20× faster than Burgundy). • Moderate suitability area nearly doubles by 2050: from 4482 km² to ~9316 km² (RCP ensemble mean). • High suitability emerges substantially under warming, reaching up to 352 km² (RCP8.5). • Low and very low suitability areas decline sharply under RCP8.5: low −5313 km² (−~82%), very low −82 km² (−~75%). Interpretation: - Burgundy truffle benefits modestly under low-emission warming; strong warming and increased summer droughts may reduce highly suitable areas. - Périgord truffle, currently restricted to Mediterranean climates, sees substantial increases in central European cultivation potential under all scenarios.

The study’s niche models, parameterized from literature and environmental datasets, address whether climate change will alter cultivation suitability for Burgundy and Périgord truffles in central Europe. Findings indicate that moderate warming (RCP2.6) slightly enhances Burgundy truffle suitability and area, consistent with its broader thermal niche and climate plasticity. Under stronger warming (RCP8.5), reductions in highly suitable land likely reflect combined effects of higher temperatures and summer drought, suggesting a northward shift of optimal conditions in line with observed and projected migrations of ectomycorrhizal fungi. Périgord truffle, with a narrower current climatic envelope, shows pronounced gains in moderate-to-high suitability areas under all scenarios, aligning with reports of northward expansion and indicating that central European regions with alkaline soils could become viable cultivation zones. Uncertainties are acknowledged due to limited validated occurrence/fruiting data in the Czech Republic (legal protection of Burgundy truffle, scarce historical records, and uncertainty in PCR-based mycorrhiza detection), partial soil pH coverage, and model structural simplifications (knowledge-based, correlative weighting). Despite these, the mapped patterns are ecologically plausible and corroborated by regional observations. Practical implications include the potential need for irrigation to mitigate increased evapotranspiration and agricultural drought risk by 2050, particularly given the lag (up to ~15 years) between plantation establishment and harvest. Host tree availability appears adequate, with several suitable native or expanding species (e.g., Quercus spp.) present in target regions. Socio-economic benefits could include diversified land use, increased land value, mycotourism, and habitat conservation.

A literature-informed ecological niche modelling approach suggests that climate change will likely increase the cultivation potential of both Burgundy (Tuber aestivum) and Périgord (Tuber melanosporum) truffles on alkaline soils (pH > 7) in central Europe, particularly in the Czech Republic. Burgundy truffle suitability modestly improves under low-emission warming but may decline in highly suitable areas under strong warming due to drought and heat. Périgord truffle exhibits substantial expansion of moderate and high suitability areas across all scenarios, indicating emerging opportunities north of its traditional Mediterranean range. The results support considering truffles as high-value crops that can deliver ecological and economic benefits under future climates. Future research should prioritize field validation of fruiting occurrences, refined soil pH mapping, incorporation of host species distribution dynamics, and evaluation of irrigation strategies and management practices under increasing drought risk.

- Limited occurrence and validated fruiting data in the Czech Republic (legal protection of Burgundy truffle; scarce, imprecise historical records) prevent robust model validation. - PCR-based detection of mycorrhiza has uncertainties and does not guarantee fruiting, limiting its use for validation. - Soil pH coverage is incomplete (mapped for ~64% of the country) and extrapolated from heterogeneous field measurements; spatial gaps and variability may affect suitability estimates. - Knowledge-based, correlative niche modelling with expert-derived weights may omit ecological processes (e.g., population dynamics, source–sink, management effects) and assumes stationarity of species–environment relationships. - Climate projections rely on ensemble GCM means and a delta-change method at 500 m resolution; scenario and model uncertainties persist, particularly regarding summer drought frequency and extremes. - Host tree distributions were not explicitly modelled in suitability maps, though assessed qualitatively; future shifts in hosts and management practices could influence outcomes. - Irrigation availability and adoption were not modelled but may be critical under increased evapotranspiration and drought risk.