Lawson, C. S. | Search bioRxiv

bioRxiv2023

Experimental drought reduces the productivity and stability of a recovering calcareous grassland

O_LIGrasslands comprise 40% of terrestrial ecosystems and are globally important for food production, carbon storage, and other ecosystem services. However, grasslands in many areas are becoming increasingly exposed to extreme wet and dry periods resulting from global temperature increases. C_LIO_LITherefore, understanding how grasslands will respond to climate change is a pressing issue for managing changes to biodiversity and ecosystem service provision. C_LIO_LIHere, we use experimental manipulations of precipitation (50% increase and 50% decrease of growing-season precipitation) to investigate the resistance of the diversity and productivity of a calcareous grassland community recovering from historical agricultural conversion. C_LIO_LIWe found that decreasing growing season precipitation led to reductions of mean productivity (25 % decrease in peak above-ground biomass) and its temporal stability (54 % increase in biomass variance across years). However, the grassland community composition was resistant to the precipitation manipulations, with no clear difference in community compositional turnover, dissimilarity, or biodiversity indices. Furthermore, the precipitation manipulations had no effect on the path of ongoing (30 year) recovery of grassland plant diversity from the period of previous agricultural conversion. C_LIO_LIWhile the diversity of this calcareous grassland was resistant to precipitation extremes (at least in the short term), sustained reductions in growing-season precipitation reduced productivity and its temporal stability demonstrating that different properties of grasslands can vary in their responses to changes in precipitation. C_LI

ecology↗

bioRxiv2022

Flexible estimation of biodiversity with short-range multispectral imaging in a temperate grassland

O_LIImage sensing technologies are rapidly increasing the cost-effectiveness of biodiversity monitoring efforts. Species differences in the reflectance of electromagnetic radiation have recently been highlighted as a promising target to estimate plant biodiversity using multispectral image data. C_LIO_LIHowever, these efforts are currently hampered by logistical difficulties in broad-scale implementation and their use in characterizing biodiversity at different spatial scales. C_LIO_LIHere, we investigate the utility of multispectral imaging technology from commercially available unmanned aerial vehicles (UAVs, or drones) in estimating biodiversity metrics at short-range (<10 m image recording height) in a temperate calcareous grassland ecosystem in Oxfordshire, UK. We calculate a suite of moments (coefficient of variation, standard deviation, skew, kurtosis) for the distribution of radiance from multispectral images at five wavelength bands (Blue 450{+/-}16 nm; Green 560{+/-}16 nm; Red 650{+/-}16 nm; Red Edge 730{+/-}16 nm; Near Infrared 840{+/-}16 nm) and test their effectiveness at estimating ground-truthed biodiversity metrics from in-situ botanical surveys for 37 - 1 m x 1 m quadrats. C_LIO_LIWe find positive associations between the average coefficient of variation in spectral radiance and both the Shannon-Weiner and Simpsons biodiversity indices. Furthermore, we find that the average coefficient of variation in spectral radiance is consistent and highly repeatable, across sampling days and recording heights. Positive associations with biodiversity indices hold irrespective of the image recording height (2-8 m), but we report reductions in estimates of spectral diversity with increases to UAV recording height. UAV imaging reduced sampling time by 16-fold relative to in-situ botanical surveys. C_LIO_LISynthesis - We demonstrate the utility of multispectral radiance moments as an indicator of grassland biodiversity metrics at high spatial resolution using a widely available UAV monitoring system at a coarse spectral resolution. The use of UAV technology with multispectral sensors has far-reaching potential to provide cost-effective and high-resolution monitoring of biodiversity in complex environments. C_LI

ecology↗