Estimating nitrogen risk to Himalayan forests using thresholds for lichen bioindicators. (January 2022)

• Record Type: Journal Article
• Authors: Ellis, Christopher J.; Steadman, Claudia E.; Vieno, Massimo; Chatterjee, Sudipto; Jones, Matthew R.; Negi, Sidharth; Pandey, Bishnu Prasad; Rai, Himanshu; Tshering, Dendup; Weerakoon, Gothamie; Wolseley, Pat; Reay, David; Sharma, Subodh; Sutton, Mark
• Is Part Of: Biological conservation. Volume 265(2022)
• Publication Date: 2022-01
• Subjects: Ammonia -- Critical level -- Critical load -- Himalayan forests -- Lichen -- Nitrogen pollution; Conservation of natural resources -- Periodicals; Nature conservation -- Periodicals; Ecology -- Periodicals; Environment -- Periodicals; Environmental Pollution -- Periodicals; Electronic journals; 333.9516
• DOI: 10.1016/j.biocon.2021.109401
• Languages: English
• ISSNs: 0006-3207

Abstract

Abstract: Himalayan forests are biodiverse and support the cultural and economic livelihoods of their human communities. They are bounded to the south by the Indo-Gangetic Plain, which has among the highest concentrations of atmospheric ammonia globally. This source of excess nitrogen pushes northwards into the Himalaya, generating concern that Himalayan forests will be impacted. To estimate the extent to which atmospheric nitrogen is impacting Himalayan forests we focussed on lichen epiphytes, which are a well-established bioindicator for atmospheric nitrogen pollution. First, we reviewed published literature describing nitrogen thresholds (critical levels and loads) at which lichen epiphytes are affected, identifying a mean and confidence intervals based on previous research conducted across a diverse set of biogeographic and ecological settings. Second, we used estimates from previously published atmospheric chemistry models (EMEP-WRF and UKCA-CLASSIC) projected to the Himalaya with contrasting spatial resolution and timescales to characterise model variability. Comparing the lichen epiphyte critical levels and loads with the atmospheric chemistry model projections, we created preliminary estimates of the extent to which Himalayan forests are impacted by excess nitrogen; this equated to c. 80–85% and c. 95–98% with respect to ammonia and total nitrogen deposition, respectively. Recognising that lichens are one of the most sensitive bioindicators for atmospheric nitrogen pollution, our new synthesis of previous studies on this topic generated concern that most Himalayan forests are at risk from excess nitrogen. This is a desk-based study that now requires verification through biological surveillance, for which we provide key recommendations. Highlights: We reviewed nitrogen critical levels and loads for lichen biodindicators. These thresholds were applied to Himalayan forests based on modelled nitrogen. Over 80% of Himalayan forests exceeded critical levels and loads. Lichen bioindicators signal potential for widespread negative effects associated with atmospheric nitrogen pollution.