Assessing across-scale optical diversity and productivity relationships in grasslands of the Italian alps

The linearity and scale-dependency of ecosystem biodiversity and productivity relationships (BPRs) have been under intense debate. In a changing climate, monitoring BPRs within and across different ecosystem types is crucial, and novel remote sensing tools such as the Sentinel-2 (S2) may be adopted to retrieve ecosystem diversity information and to investigate optical diversity and productivity patterns. But are the S2 spectral and spatial resolutions suitable to detect relationships between optical diversity and productivity? In this study, we implemented an integrated analysis of spatial patterns of grassland productivity and optical diversity using optical remote sensing and Eddy Covariance data. Across-scale optical diversity and ecosystem productivity patterns were analyzed for different grassland associations with a wide range of productivity. Using airborne optical data to simulate S2, we provided empirical evidence that the best optical proxies of ecosystem productivity were linearly correlated with optical diversity. Correlation analysis at increasing pixel sizes proved an evident scale-dependency of the relationships between optical diversity and productivity. The results indicate the strong potential of S2 for future large-scale assessment of across-ecosystem dynamics at upper levels of observation

Remote sensing tools for monitoring grassland plant leaf traits and biodiversity

Rocchini, Duccio1This project has received funding from the European Union’s Horizon 2020 Research and Innovation Program under the Marie Skłodowska-Curie Grant No. 721995 (project Trustee).openGrasslands are one of the most important ecosystems on Earth, covering approximately onethird of the Earth’s surface. Grassland biodiversity is important as many services provided by such ecosystems are crucial for the human economy and well-being. Given the importance of grasslands ecosystems, in recent years research has been carried out on the potential to monitor them with novel remote sensing techniques. Improved detectors technology and novel sensors providing finescale hyperspectral imagery have been enabling new methods to monitor plant traits (PTs) and biodiversity. The aims of the work were to study different approaches to monitor key grassland PTs such as Leaf Area Index (LAI) and biodiversity-related traits. The thesis consists of 3 parts: 1) Evaluating the performance of remote sensing methods to estimate LAI in grassland ecosystems, 2) Estimating plant biodiversity by using the optical diversity approach in grassland ecosystems, and 3) Investigating the relationship between PTs variability with alpha and beta diversity for the applicability of the optical diversity approach in a subalpine grassland of the Italian Alps To evaluate the performance of remote sensing methods to estimate LAI, temporal and spatial observations of hyperspectral reflectance and LAI were analyzed at a grassland site in Monte Bondone, Italy (IT-MBo). In 2018, ground temporal observations of hyperspectral reflectance and LAI were carried out at a grassland site in Neustift, Austria (AT-NEU). To estimate biodiversity, in 2018 and 2019 a floristics survey was conducted to determine species composition and hyperspectral data were acquired at two grassland sites: IT-MBo and University of Padova’s Experimental Farm, Legnaro, Padua, Italy (IT-PD) respectively. Furthermore, in 2018, biochemistry analysis of the biomass samples collected from the grassland site IT-MBo was carried out to determine the foliar biochemical PTs variability. The results of the thesis demonstrated that the grassland spectral response across different spectral regions (Visible: VIS, red-edge: RE, Near-infrared: NIR) showed to be both site-specific and scale-dependent. In the first part of the thesis, the performance of spectral vegetation indices (SVIs) based on visible, red-edge (RE), and NIR bands alongside SVIs solely based or NIRshoulder bands (wavelengths 750 - 900 nm) was evaluated. A strong correlation (R2 > 0.8) was observed between grassland LAI and both RE and NIR-shoulder SVIs on a temporal basis, but not on a spatial basis. Using the PROSAIL Radiative Transfer Model (RTM), it was demonstrated that grassland structural heterogeneity strongly affects the ability to retrieve LAI, with high uncertainties due to structural and biochemical PTs co-variation. In the second part, the applicability of the spectral variability hypothesis (SVH) was questioned and highlighted the challenges to use high-resolution hyperspectral images to estimate biodiversity in complex grassland ecosystems. It was reported that the relationship between biodiversity (Shannon, Richness, Simpson, and Evenness) and optical diversity metrics (Coefficient of variation (CV) and Standard deviation (SD)) is not consistent across plant communities. The results of the second part suggested that biodiversity in terms of species richness could be estimated by optical diversity metrics with an R2 = 0.4 at the IT-PD site where the grassland plots were artificially established and are showing a lower structure and complexity from the natural grassland plant communities. On the other hand, in the natural ecosystems at IT-MBo, it was more difficult to estimate biodiversity indices, probably due to structural and biochemical PTs co-variation. The 18 effects of canopy non-vegetative elements (flowers and dead material), shadow pixels, and overexposed pixels on the relationship between optical diversity metrics and biodiversity indices were highlighted. In the third part, we examined the relationship between PTs variability (at both local and community scales, measured by standard deviation and by the Euclidean distances of the biochemical and biophysical PTs respectively) and taxonomic diversity (both α-diversity and βdiversity, measured by Shannon’s index and by Jaccard dissimilarity index of the species, families, and functional groups percent cover respectively) in Monte Bondone, Trentino province, Italy. The results of the study showed that the PTs variability metrics at alpha scale were not correlated with α-diversity. However, the results at the community scale (β-diversity) showed that some of the investigated biochemical and biophysical PTs variations metrics were associated with β-diversity. The SVH approach was also tested to estimate β-diversity and we found that spectral diversity calculated by spectral angular mapper (SAM) showed to be a better proxy of biodiversity in the same ecosystem where the spectral diversity failed to estimate alpha diversity, this leading to the conclusion that the link between functional and species diversity may be an indicator of the applicability of optical sampling methods to estimate biodiversity. The findings of the thesis highlighted that grassland structural heterogeneity strongly affects the ability to retrieve both LAI and biodiversity, with high uncertainties due to structural and biochemical PTs co-variation at complex grassland ecosystems. In this context, the uncertainties of satellite-based products (e.g., LAI) in monitoring grassland canopies characterized by either spatially or temporally varying structure need to be carefully taken into account. The results of the study highlighted that the poor performance of optical diversity proxies in estimating biodiversity in structurally heterogeneous grasslands might be due to the complex relationships between functional diversity and biodiversity, rather than the impossibility to detect functional diversity with spectral proxiesopenImran, H.A

Assessing plant trait diversity as an indicators of species α and β-diversity in a subalpine grassland of the Italian Alps

As the need for ecosystem biodiversity assessment increases within the climatecrisis framework, more and more studies using spectral variation hypothesis(SVH) are proposed to assess biodiversity at various scales. The SVH impliesoptical diversity (also called spectral diversity) is driven by light absorptiondynamics associated with plant traits (PTs) variability (which is an indicator offunctional diversity) which is, in turn, determined by biodiversity. In this study,we examined the relationship between PTs variability, optical diversity andα-andβ-diversity at different taxonomic ranks at the Monte Bondone grasslands,Trentino province, Italy. The results of the study showed that the PTs variabil-ity, at theαscale, was not correlated with biodiversity. On the other hand, theresults observed at the community scale (β-diversity) showed that the variationof some of the investigated biochemical and biophysical PTs was associatedwith theβ-diversity. We used the Mantel test to analyse the relationshipbetween the PTs variability and speciesβ-diversity. The results showed a corre-lation coefficient of up to 0.50 between PTs variability and speciesβ-diversity.For higher taxonomic ranks such as family and functional groups, a slightlyhigher Spearman’s correlation coefficient of up to 0.64 and 0.61 was observed,respectively. The SVH approach was also tested to estimateβ-diversity and wefound that spectral diversity calculated by Spectral Angle Mapper showed to bea better proxy of biodiversity in the same ecosystem where the spectral diversityapproach failed to estimateα-diversity. These findings suggest that optical andPTs diversity approaches can be used to predict species diversity in the grass-lands ecosystem where the species turnover is high

NDVI Analysis for Monitoring Land-Cover Evolution on Selected Deglaciated Areas in the Gran Paradiso Group (Italian Western Alps)

The ongoing climate warming is affecting high-elevation areas, reducing the extent and the duration of glacier and snow covers, driving a widespread greening effect on the Alpine region. The impact assessment requires therefore the integration of the geomorphological context with altitudinal and ecological features of the study areas. The proposed approach introduces chronologically-constrained zones as geomorphological evidence for selecting deglaciated areas in the alpine and non-alpine belts. In the present study, the protected and low-anthropic-impacted areas of the Gran Paradiso Group (Italian Western Alps) were analysed using Landsat NDVI time series (1984–2022 CE). The obtained results highlighted a progressive greening even at a higher altitude, albeit not ubiquitous. The detected NDVI trends showed, moreover, how the local factors trigger the greening in low-elevation areas. Spectral reflectance showed a general decrease over time, evidencing the progressive colonisation of recently deglaciated surfaces. The results improved the discrimination between different greening rates in the deglaciated areas of the Alpine regions. The geomorphological-driven approach showed significant potential to support the comprehension of these processes, especially for fast-changing areas such as the high mountain regions

Prediction of grassland biodiversity using measures of spectral variance: a meta-analytical review

Over the last 20 years, there has been a surge of interest in the use of reflectance data collected using satellites and aerial vehicles to monitor vegetation diversity. One methodological option to monitor these systems involves developing empirical relationships between spectral heterogeneity in space (spectral variation) and plant or habitat diversity. This approach is commonly termed the ‘Spectral Variation Hypothesis’. Although increasingly used, it is controversial and can be unreliable in some contexts. Here, we review the literature and apply three-level meta-analytical models to assess test results of the hypothesis across studies using several moderating variables, relating to the botanical and spectral sampling strategies, and the types of sites evaluated. We focus on the literature relating to grasslands, which are less well studied compared to forests and are likely to require separate treatment due to their dynamic phenology and the taxonomic complexity of their canopies over small scales. Across studies, results suggest an overall positive relationship between spectral variation and species diversity (mean correlation co-efficient = 0.36). However, high levels of both within study and between study heterogeneity was found. Whether data was collected at the leaf or canopy level had the most impact on the mean effect size, with leaf level studies displaying a stronger relationship compared to canopy level studies. We highlight the challenges facing synthesis of these kinds of experiments, the lack of studies carried out in arid or tropical systems and the need for scalable, multi-temporal assessments to resolve controversy in the field

Progressively excluding mammals of different body size affects community and trait structure of ground beetles

Mammalian grazing induces changes in vegetation properties in grasslands, which can affect a wide variety of other animals including many arthropods. However, the impacts may depend on the type and body size of these mammals. Furthermore, how mammals influence functional trait syndromes of arthropod communities is not well known. We progressively excluded large (e.g. red deer, chamois), medium (e.g. alpine marmot, mountain hare), and small (e.g. mice) mammals using size-selective fences in two vegetation types (short- and tall-grass vegetation) of subalpine grasslands. We then assessed how these exclusions affected the community composition and functional traits of ground beetles (Coleoptera, Carabidae), and which vegetation characteristic mediated the observed effects. Total carabid biomass, the activity densities of carabids with specific traits (i.e. small eyes, short wings), the richness of small-eyed species and the richness of herbivorous species were significantly higher when certain mammals were excluded compared to when all mammals had access, regardless of vegetation type. Excluding large and medium mammals increased the activity density of herbivorous carabid species, but only in short-grass vegetation. Similarly, excluding large mammals (ungulates) altered carabid species composition in the short-, but not in the tall-grass vegetation. All these responses were related to aboveground plant biomass, but not to plant Shannon diversity or vegetation structural heterogeneity. Our results indicate that changes in aboveground plant biomass are key drivers of mammalian grazers' influence on carabids, suggesting that bottom-up forces are important in subalpine grassland systems. The exclusion of ungulates provoked the strongest carabid response. Our results, however, also highlight the ecological significance of smaller herbivorous mammals. Our study furthermore shows that mammalian grazing not only altered carabid community composition, but also caused community-wide functional trait shifts, which could potentially have a wider impact on species interactions and ecosystem functioning

Synergy between habitat fragmentation and climate change: implications for biodiversity in Alpine ecosystems

An increase in global temperature accompanied by rapid fragmentation of habitats will lead to greater pressure on biodiversity, with more dramatic impacts expected on high mountain ranges. A new wave of extinction is likely to occur as the ability of species to migrate toward new cooler suitable areas will be hampered by altered landscapes, also the magnitude of species loss will in part depend on species traits, or phenotypic plasticity of individuals which will have to adapt to the changed environmental conditions. In this PhD thesis, I included different models employing altitudinal gradient as a surrogate, to understand how effects determined by climatic variation might or might not exacerbate the negative impact of landscape changes on carabid communities (eastern Italian Alps). Chapter I contains a brief overview of the current body of scientific literature on the main ecological impacts of habitat fragmentation and climate change, and the emerging research related to the response of organisms to the synergistic impacts of these two threats. The aim of Chapter II is to determine whether the effects of rising temperature might enhance the impact of habitat fragmentation on beetle diversity and community structure. Chapter III describes an attempt to assess the existence of simultaneous effects generated by habitat fragmentation and climate change on variation of morphological traits (fluctuating asymmetry and body length) in natural populations of forest-dwelling species Haptoderus unctulatus. Finally, Chapter IV explores if species’ sensitivity to landscape modification and altitude might be maximized or not by a combination of life history traits of ground beetles. In summary, data of carabid assemblages suggest that the impact of rising temperature acting in synergy with land use pressure will move up along the mountainside, inflicting more serious negative impact on species composition, and causing changes in morphological traits of beetle populations particularly accentuated at lowlands. Also, interaction between these two drivers of change will exert a selective pressure on species with certain functional traits, which will result in a greater impact on the beetle assemblages of Alpine ecosystems than either driver acting individually

Hundi (Canis lupus) populatsioonid Eestis ja Euroopas: geneetiline mitmekesisus, populatsiooni struktuur ja -protsessid ning hübridiseerimine koertega

Väitekirja elektrooniline versioon ei sisalda publikatsioone.Ajal, mil mitmete hundipopulatsioonide levila on Euroopas suurenemas, on teadmised hundi populatsioonigeneetikast vajalikud liigi jaoks oluliste kaitse- ja majandamisotsuste tegemiseks ja seda nii kohalike populatsioonide kui ka üleeuroopalisel tasandil. Käesoleva töö peamisteks eesmärkideks oli uurida Eesti ja Läti hundipopulatsioonide struktuuri ja –protsesse, hübridiseerumist koertega ning laiemalt kogu Euroopa huntide ruumilis-geneetilise mitmekesisuse mustreid ja trende. Kasutades nii emaliini, isaliini kui ka biparentaalseid geneetilisi markereid kombineerivat analüüsi, tuvastasime Eestis (esmakordselt) ja Lätis hundi ja koera hübriidid, sealjuures kaks hübriidi Lätist esindasid väga haruldast, Euroopas esmakordselt tuvastatud hübridiseerimisjuhtumit - emase koera ja isase hundi vahel. Eestit ja Lätit hõlmav hundipopulatsiooni geneetilisel analüüsil leiti neli geneetiliselt eristuvat rühma ning uudne DResD analüüs tuvastas populatsioonis migratsioonikoridori ning liikumisbarjääre ja kontakttsoone eri geneetiliste rühmade vahel. Suuremat osa Euroopa hundipopulatsioonidest hõlmav meta-analüüs tuvastas olulise ruumilise mitmekesisuse trendi – huntide madalaim geneetiline mitmekesisus esines Euroopa edelaosas ja kõrgeim kirdeosas. Tulemustes selgunud ruumilise autokorrelatsiooni vahemik 650-850 km näitab, et konkreetse hundipopulatsiooni geneetilist mitmekesisust võivad mõjutada hundipopulatsioonid, mis asuvad kuni 850 km kaugusel. Enamik Euroopa hundipopulatsioonidest on silmitsi sarnaste, inimese poolt otseselt või kaudselt seotud ohtudega: küttimine (sealhulgas salaküttimine), inimeste madal sallivus hundi suhtes, konfliktid kariloomade murdmise tõttu, elupaikade hävimine ning võimalik hübridiseerumine koertega. Selleks, et hunt säiliks Euroopas pikka aega ja soodsas seisundis, on vaja suurendada Euroopa hundipopulatsioonide üldist arvukust ja soodustada loomade levikut ja populatsioonide-siseseid ja -vahelisi seoseid. Hundi teaduspõhiseks kaitsmiseks ja majandamiseks nii piirkondlikel kui ka üleeuroopalisel skaalal, on hundipopulatsioone vaja hallata kui bioloogilisi üksusi, mis nõuab kõiki Euroopa hundipopulatsioone hõlmavaid täiendavaid geneetilisi analüüse, et teha kindlaks populatsioonide täpne arv, ruumiline jaotus, geenisiirde ulatused ning hübridiseerumise sageduse koertega.As many wolf populations in Europe are expanding their range, knowledge of population genetics are of great importance for effective conservation and management of the species at both local and over-European scales. The main goal of this thesis was to provide information on wolf population structure and processes in Europe with a particular emphasis on Estonia and Latvia, including the wolf-dog hybridization. Using a combined analysis of maternal, paternal and biparental genetic markers, hybridization between grey wolf and domestic dog was ascertained in Estonia (for the first time) and in Latvia. The two hybrids from Latvia represented a very rare case of hybridization – the first record from Europe – between a female dog and a male wolf. Population structure analysis demonstrated that wolf popu¬lation shared between Estonia and Latvia is represented by four genetic groups. The spatially explicit DResD analysis provided clear evidence of spatial variation of genetic divergence, revealing a migration corridor, barriers, and several contact zones between different genetic groups. In a meta-analysis covering most of the European wolf populations, significant spatial trend in heterozygosity across Europe from south-west (lowest genetic diversity) to north-east (highest) was found. The range of spatial autocorrelation of 650−850 km suggests, that the genetic diversity of a given wolf population can be influenced by populations up to 850 km away. Various human-related factors are undoubtedly the main source of threats to wolf populations in Europe: the majority of populations face similar common threats such as overharvesting (including poaching), low public acceptance, conflicts due to livestock depredation, habitat destruction, barriers to gene flow and interactions with dogs leading to possible hybridization. For the long-term survival and favourable conservation status of European wolves there is a need to increase the overall population size and favour wolf dispersal and connectivity among and within populations. For science-based wolf conservation and manage¬ment at regional and Europe-wide scales it was suggested to manage wolf populations according to biological units, which requires additional genetic analysis covering all wolf populations in Europe to define the exact number and spatial distribution of populations

Assessing responses of grasslands to grazing management using remote sensing approaches

Grazing caused grassland degradation has occurred worldwide in recent decades. In spite of numerous efforts that have been invested to explore the mechanism of grassland responses to grazing management, the major challenge remains monitoring the responses over large area. This research evaluates the synthetic use of remote sensing data and the Milchunas-Sala-Lauenroth (MSL) model for grazing impact assessment, aiming to explore the potential of remotely sensed data to investigate the responses of grasslands to various grazing intensities across different grassland types. By combining field collected biophysical parameters, ground hyperspectral data and satellite imagery with different resolutions, this research concluded that 1) sampling scale played an important role in vegetation condition assessment. Adjusted transformed soil-adjusted vegetation index (ATSAVI) derived from remote sensing imagery with 10m or 20m spatial resolution was suitable for measuring leaf area index (LAI) changes in post-grazing treatment in the grazing experimental site; 2) canopy height and the ratio of photosynthetically to non-photosynthetically active vegetation cover were identified as the most sensitive biophysical parameters to reflect vegetation changes in mixed grasslands under light to moderate grazing intensities; 3) OSAVI (Optimised soil adjusted vegetation index) derived from Landsat Thematic Mapper (TM) image can be used for grassland production estimation under various grazing intensities in three types of grasslands in Inner Mongolia, China, with an accuracy of 76%; and 4) Grassland production predicted by NCI (Normalized canopy index) showed significant differences between grazed and ungrazed sites in years with above average and average growing season precipitation, but not in dry years, and 75% of the variation in production was explained by growing season precipitation (April-August) for both grazed and ungrazed sites