What is an otter's favourite food? - a molecular investigation into the dietary preferences of the Eurasian otter (Lutra lutra) across the River Hull Catchment

Knowledge of top predator diets is fundamental to designing appropriate management strategies which ensure the protection of both predator and prey populations. The Eurasian otter (Lutra lutra) has traditionally been described as an opportunist; however, modern studies have demonstrated clear feeding preferences towards slow moving fish species. Prior dietary studies on the Eurasian otter have used morphological analysis of spraints to determine the prey eaten, and electrofishing to inform the fish communities present locally. Traditional morphological analyses are challenging, as it is difficult to identify bones down to the species level. Meanwhile, electrofishing may underestimate rare fish species present in the catchment. This study usesa non-invasive molecular methodology,whichprovidesgreater resolutionon the available fish community,to understand thedietary preferences of otters along the River Hull. Theresearchquestionswere: 1) Doesotter diet vary spatially in response to local fish communities?2) Doesotter diet vary seasonally in response to changes in fish activity?3) Is a single DNA extraction sufficient to investigate otter diets?4) Do otter and mink diets overlap in the River Hull catchment?DNA extracted from otter spraints (n= 81) was sequenced using broad scale vertebrate primers to inform the prey eaten; and compared with eDNA from water samples (n= 48) collected along the River Hull to inform the prey available. Otterdiet varied significantly across the upper, middle,and lower River Hull depending on the available fish community, and a consistent selective preference was observed towards the European bullhead (Cottus gobio). Overall otter diet did not vary significantly between seasons, however, Eurasian otters fed on significantly more different prey items in spring (Mean= 3.125) than winter (Mean= 2.482). The replicate DNA extraction experiment demonstrated that a single extraction replicate is sufficient for detecting most prey items. Finally, comparisons between the Eurasian otter and American mink have provided further evidence of niche differentiation between the two species, thus allowing for coexistence with minimal overlap

Field spectroscopy and spectral reflectance modelling of Calluna vulgaris

Boreal peatlands store carbon sequestered from the atmosphere over millennia and the importance of this and the other ecosystem services these areas provide is now widely recognised. However, a changing climate will affect these environments and, consequently, the services they provide to the global population. The rate and direction of environmental change to peatlands is currently unclear and they have not yet been included in many climate models. This may in part be due to the ecological heterogeneity and spatial extent of these areas and the sparse sampling survey methods currently adopted. Hyperspectral remote sensing from satellite platforms may in future offer an approach to surveying and do so at the high spectral and spatial resolutions necessary to infer ecological change in these peatlands. However, work is required to develop methods of analysis to determine if hyperspectral data can be used to measure the overstorey vegetation of these areas. This will require an understanding of how annual and inter-annual cyclical changes affect the peatland plant canopy reflectances that would be recorded by hyperspectral sensors and how these reflectances can be related to state variable of interest to climate scientists, ecologists and peatland managers. There are significant areas of peatland within Scotland and, as it is towards the southern extreme of the boreal peatlands, these may be an early indicator of environment change to the wider boreal region. Calluna vulgaris, a hardy dwarf shrub, is the dominant overstorey species over much of these peatlands and could serve as a proxy for ecological, and consequently, environmental change. However, little has been done to understand how variations in leaf pigments or canopy structural parameters influence the spectral reflectance of Calluna through annual and inter-annual growth and senescence cycles. Nor has much work been done to develop methods of analysis to enable images acquired by hyperspectral remote sensing to be utilised to monitor change to these Calluna dominated peatlands over time. To advance understanding of the optical properties of Calluna leaves and canopies and develop methods to analyse hyperspectral images laboratory, field and modelling studies have been carried out in time series over a number of years. The leaf and canopy parameters significantly affecting reflectance have been identified and quantified. Differences between published Chlorophyll(a+b) in vivo absorption spectra and those determined were found. Carotenoids and Anthocyanins were also identified and quantified. The absorption spectra of these pigments were incorporated into a canopy reflectance model and this was coupled to a Calluna growth model. This combined model enabled the reflectance of Calluna canopies to be modelled in daily increments through annual and inter-annual growth and senescence cycles. Reasonable results were achieved in spectral regions where reflectance changed systematically but only for homogeneous Calluna stands. However, it was noted during this research that the area of support for the spectral measurements appeared to differ from that assumed from the specification provided by the spectroradiometer manufacturers. The directional response functions (DRFs) of two spectroradiometers were investigated and wavelength, or wavelength region, specific spatial dependences were noted. The effect that the DRFs of the spectroradiometers would have on reflectances recorded from Calluna canopies was investigated through a modelling study. Errors and inaccuracies in the spectra that would be recorded from these canopies, and commonly used biochemical indices derived from them, have been quantified

Assessing the impact of non-linear responses of field spectroradiometers on the estimation of biophysical parameters and light use efficiency

Tommaso Julitta’s Short Term Scientific Mission was funded by the Cost Action ES0903 – Eurospec. Javier Pacheco-Labrador’s stay was partially funded by the Biospec project “Linking spectral information at different spatial scales with biophysical parameters of Mediterranean vegetation in the context of Global Change” (CGL2008-02301/CLI, Ministry of Science and Innovation).Peer reviewe

Investigating Forest Photosynthetic Response to Elevated CO2 Using UAV-Based Measurements of Solar Induced Fluorescence

The response of ecosystems to increasing atmospheric CO2 will have significant, but still uncertain, impacts on the global carbon and water cycles. A lot of infounation has been gained from Free Air CO2 Enrichment (FACE) experiments, but the response of mature forest ecosystems remains a significant knowledge gap. One of the challenges in FACE studies is obtaining an integrated measure of canopy photosynthesis at the scale of the treatment ring. A new remote sensing approach for measuring photosynthetic activity is based on Solar Induced Fluorescence (SIF), which is emitted by plants during photosynthesis, and is closely linked to the rates and regulation of photosynthesis. We proposed that UAV-based SIF measurements, that enable the spectrometer field of view to be targeted to the treatment ring, provide a unique opportunity for investigating the dynamics of photosynthetic responses to elevated CO2. We have successfully tested this approach in a new FACE site, located in a mature oak forest in the UK. We flew a series of flights across the experiment arrays, collecting a number of spectra. We combined these with ground-based physiological and optical measurements, and see great promise in the use of UAV-based SIF measurements in FACE and other global change experiments.Peer reviewe

Upscaling of solar induced chlorophyll fluorescence from leaf to canopy using the DART model and a realistic 3D forest scene

Non peer reviewe

Characterisation of the HDRF (as a proxy for BRDF) of snow surfaces at Dome C, Antarctica, for the inter-calibration and inter-comparison of satellite optical data

Measurements of the Hemispherical Directional Reflectance Factor (HDRF) of snow surfaces were performed at Dome C, Antarctica, during the Australis Summer 2011–2012 to support the inter-comparison and inter-calibration of satellite optical sensors. HDRF data were collected with the Gonio Radiometric Spectrometer System (GRASS) which performs hyper-spectral measurements of radiance from the same target surface with independent collectors at a number of viewing and azimuth angles in the 0–60° and 0–360° angular ranges, respectively. The radiance collectors, installed on a hemispheric frame and connected to a spectrometer through fibre optics, have an 8° full cone of acceptance and a viewing footprint varying from 0.049m2 at nadir to 0.142m2 at viewing angles of 60°. These relatively small footprints allow for the characterization of small-scale heterogeneities in the HDRF of observed surfaces. HDRF measurements representative of the Dome C snow surfaces were made at eight different sites along a transect approximately 100 m long. All the sites exhibit similar HDRF distributions with inter-site differences explained by small-scale inhomogeneities of the surface. The measured HDRF display marked forward scattering with anisotropy increasing with wavelength in the 400–1600 nm spectral region. These data complement those from previous measurements performed in the same area with a different technique. Agreement between the two data sets is shown by differences generally lower than 4% between HDRF distributions derived from a previous study and the spatially averaged HDRF from the various sites along a transect presented in this work.JRC.H.1-Water Resource

Structural and photosynthetic dynamics mediate the response of SIF to water stress in a potato crop

Solar-induced Fluorescence (SIF) has an advantage over greenness-based Vegetation Indices in detecting drought. This advantage is the mechanistic coupling between SIF and Gross Primary Productivity (GPP). Under water stress, SIF tends to decrease with photosynthesis, due to an increase in non-photochemical quenching (NPQ), resulting in rapid and/or sustained reductions in the fluorescence quantum efficiency (phi F). Water stress also affects vegetation structure via highly dynamic changes in leaf angular distributions (LAD) or slower changes in leaf area index (LAI). Critically, these responses are entangled in space and time and their relative contribution to SIF, or to the coupling between SIF and GPP, is unclear. In this study, we quantify the relative effect of structural and photosynthetic dynamics on the diurnal and spatial variation of canopy SIF in a potato crop in response to a replicated paired-plot water stress experiment. We measured SIF using two platforms: a hydraulic lift and an Unmanned Aerial Vehicle (UAV) to capture temporal and spatial variation, respectively. LAD parameters were estimated from point clouds and photographic data and used to assess structural dynamics. Leaf phi F estimated from PAM fluorescence measurements were used to represent variations in photosynthetic regulation. We also measured foliar pigments, operating quantum yield of photosystem II (PSII), photosynthetic gas exchange, stomatal conductance and LAI. We used a radiative transfer model (SCOPE) to provide a means of decoupling structural and photosynthetic factors across the diurnal and spatial domains. The results demonstrate that diurnal variation in SIF is driven by photosynthetic and structural dynamics. The influence of phi F was prominent in the diurnal SIF response to water stress, with reduced fluorescence efficiencies in stressed plants. Structural factors dominated the spatial response of SIF to water stress over and above phi F. The results showed that the relationship between SIF and GPP is maintained in response to water stress where adjustments in NPQ and leaf angle co-operate to enhance the correlation between SIF and GPP. This study points to the complexity of interpreting and modelling the spatiotemporal connection between SIF and GPP which requires simultaneous knowledge of vegetation structural and photosynthetic dynamics.Peer reviewe

The value of Sentinel-2 spectral bands for the assessment of winter wheat growth and development

Leaf Area Index (LAI) and chlorophyll content are strongly related to plant development and productivity. Spatial and temporal estimates of these variables are essential for efficient and precise crop management. The availability of open-access data from the European Space Agency’s (ESA) Sentinel-2 satellite—delivering global coverage with an average 5-day revisit frequency at a spatial resolution of up to 10 metres—could provide estimates of these variables at unprecedented (i.e., sub-field) resolution. Using synthetic data, past research has demonstrated the potential of Sentinel-2 for estimating crop variables. Nonetheless, research involving a robust analysis of the Sentinel-2 bands for supporting agricultural applications is limited. We evaluated the potential of Sentinel-2 data for retrieving winter wheat LAI, leaf chlorophyll content (LCC) and canopy chlorophyll content (CCC). In coordination with destructive and non-destructive ground measurements, we acquired multispectral data from an Unmanned Aerial Vehicle (UAV)-mounted sensor measuring key Sentinel-2 spectral bands (443 to 865 nm). We applied Gaussian processes regression (GPR) machine learning to determine the most informative Sentinel-2 bands for retrieving each of the variables. We further evaluated the GPR model performance when propagating observation uncertainty. When applying the best-performing GPR models without propagating uncertainty, the retrievals had a high agreement with ground measurements—the mean R2 and normalised root-mean-square error (NRMSE) were 0.89 and 8.8%, respectively. When propagating uncertainty, the mean R2 and NRMSE were 0.82 and 11.9%, respectively. When accounting for measurement uncertainty in the estimation of LAI and CCC, the number of most informative Sentinel-2 bands was reduced from four to only two—the red-edge (705 nm) and near-infrared (865 nm) bands. This research demonstrates the value of the Sentinel-2 spectral characteristics for retrieving critical variables that can support more sustainable crop management practices