Reindeer carcasses modulate vegetation composition and greenness in High-Arctic tundra

Milder winters over High Arctic regions have dramatic impacts on local biodiversity on Svalbard, with rain-on-snow events directly correlated with reindeer mortality. Vertebrate carrion can have disproportionately larger impacts on vegetation in nutrient-limited systems, compared with warmer biomes. We conducted a ground survey on the cover of five plant functional groups at paired carcass and control sites and analysed the relationship between cover and carcass presence with generalised linear mixed effect models. Vegetation indices from RGB imagery captured by drones complemented this, assessing plant productivity in terms of ‘spectral greening’. We modelled the relationship between vegetation index values and carcass distance with generalised additive models. We show that graminoids capitalised most from carcass presence, whereas bryophytes and lichen showed decreases in cover. Woody plants and herb covers were not significantly impacted by carcass presence. The Red Green Blue Vegetation Index (RGBVI, our proxy for vegetation productivity) decreased locally at fresh carcasses (i.e. <1 year old) but showed an increase at more established carcass sites (i.e. >1 year). We show that carcasses have differential impacts on the plant functional groups of Svalbard’s tundra and induce a local ‘green-up’ with secondary succession within 2 metres. Given their non-random distribution, carcasses may contribute to vegetation heterogeneity at landscape scales. This is relevant for understanding how climate change-induced reindeer mortalities will impact Arctic tundra composition in the future.

Methods
33 reindeer carcasses were visited in Adventdalen (and surrounding valleys) Svalbard, in August 2021. Carcasses were of varying ages, ranging from approximately half a year to four years (n = 8 [reindeer dead in 2021] (termed ‘new’); and n = 3 [2020], n = 20 [2019] and n = 2 [2017] (termed ‘old’). There were two forms of data collection. 

Vegetation surveys, where a 5m × 5m grid was laid over the carcass site and a nearby control (paired surveys per site)
Drone imaging surveys over the carcass and its surroundings

The 5 × 5 m grid was further subdivided into 1 × 1 m grid cells (subplots), with the central cell over the carcass 'centre', i.e. the rumen content/abdomen. The paired control sites were placed 30 – 50 m away from the carcass. Total cover (to the nearest 5%) was estimated for five functional groups, namely; forbs, graminoids, woody plants, bryophytes, and lichens, within each subplot. The subplots were categorised into three ‘bands’ describing their position within the overall grid, i.e. ‘core’ being the centre cell, ‘inner’ being the cells immediately neighbouring the centre cell, and ‘edge’ being the subplots in the outer perimeter. The relationship between these proportional covers ("vegetation composition") and subplot category was modelled with generalised linear mixed effect models.

The drone images were captured in a survey conducted 70m altitude above the carcass, with 80% image overlap. Images were stiched per survey in Agisoft Metashape Professional. Non-terrain/carcass features such as people/rope/research materials were manually masked out of each orthophoto. The orthophoto was then cropped to a 50m radius from the carcass and used for further analysis - these cropped orthomosaics are uploaded here. Stratified random sampling of pixel reflectances from these orthophotos was used to compute vegetation indices, and model the relationship with distance from carcass using generalised additive models.

All data analysis and model creation was carried out in R.