Reversing forest regression: Effects of shrub removal and grazing on thermophilous oak forests herb layer (Central Poland)

Abstract
Thermophilous oak forests rank among the most species-rich forest ecosystems in Central Europe. Preserving their centuries-old, human-shaped biodiversity now requires active management.

This study evaluates the effects of three restoration treatments – shrub removal, controlled grazing, and their combination – on the herb-layer composition of an oak forest. Research was conducted on permanent plots before and after three consecutive years of treatment, assessing changes in species frequency in relation to their functional traits.

All treatments contributed to partial restoration of the characteristic herb-layer composition, with the strongest response in the combined variant and the weakest in the control plots. Initial thinning, applied to enhance light availability, increased species frequency across all variants, though effects were much stronger under management. Species responding most positively included hemicryptophytes and geophytes, mainly CSR strategists, shaded forest and oak forest species, light demanding species and species tolerant to disturbances. All this changes indicate a shift in the composition of the herb layer towards thermophilous oak-forest.

Overall, the combination of shrub removal and grazing proved most effective in restoring the herb-layer composition, while thinning alone produced similar but weaker effects. The historical proximity approach may support short-term forecasting of changes in species frequency.

摘要
嗜温栎林（Thermophilous oak forests）是中欧物种最为丰富的森林生态系统之一。保护其历经数百年形成、受人类活动塑造的生物多样性，如今亟需开展主动管理。
本研究评估了三种恢复处理措施——灌丛清除、控制性放牧及其联合处理——对某栎林草本层群落组成的影响。研究于连续三年实施处理前后，在永久样地开展调查，结合物种功能性状分析物种频度的变化。
所有处理均实现了典型草本层组成的部分恢复，其中联合处理组的响应效果最强，对照组样地的响应最弱。为提升光照可利用性而实施的初始疏伐，提升了所有样地的物种频度，但该效应在实施管理的样地中更为显著。正向响应最为显著的物种包括地面芽植物（hemicryptophytes）与地下芽植物（geophytes），主要为CSR策略物种、阴生林及栎林物种、喜光物种以及耐干扰物种。上述所有变化均表明，草本层群落组成正朝着嗜温栎林的特征方向转变。
总体而言，灌丛清除与放牧的联合处理在恢复草本层组成方面效果最佳，而单独疏伐虽也能产生类似效果，但作用强度较弱。历史邻近性方法可为物种频度变化的短期预测提供支撑。