Woodland ectomycorrhizal (ECM) fungal species declined considerably in the Netherlands in the late 20th century, mainly due to raised levels of atmospheric nitrogen deposition. Environmental measures have been taken to reduce this deposition, but it remains unclear whether and to what extent ECM species have benefitted from these. We hypothesized that ECM species, especially those species that are known to be nitrophobic, that is, sensitive to nitrogen loading, have recovered to some extent from the reduction in nitrogen deposition after 1994. We further hypothesized that, due to legacy effects of deposition, recovery has been stronger in regions where deposition levels have previously been lower. To test these hypotheses, we analysed long-term opportunistic data, that is, observations collected without standardized field method. We applied data filtering and a modified List Length method to adjust for potential biases in these data. The removal of bias left us with two periods to examine ECM species trends: before (1965-1985) and after (1994-2013) deposition reduction started [in 1994]. We compared trends in ECM species in 1965-1985 with those in 1994-2013. Multispecies indicators were used to summarize the findings of ECM species, and to compare these with results of litter saprotrophic species and wood saprotrophic and wood parasitic species. We found that (1) most trends switched in direction from negative to positive after the reduction in nitrogen deposition began; (2) these trends were more pronounced for nitrophobic ECM species than for nitrotolerant ECM species; (3) trends for ECM species differed from those of the other functional groups; and (4) recovery was stronger in the region with a history of lower deposition. Policy implications. Our results suggest that woodland ectomycorrhizal species benefit substantially from environmental measures to reduce nitrogen deposition. Our study is one of few scientific studies to date documenting evidence of success of large-scale (nation-wide) environmental measures. We have demonstrated that opportunistic citizen science data can be used for the detection of species trends, but it is essential to examine and control for potential bias in the data.