Warming-Induced Shrub Expansion and Lichen Decline in the Western Canadian Arctic

Strong evidence for a pan-Arctic expansion of upright shrubs comes from analysis of satellite imagery, historical photographs, vegetation plots, and growth rings. However, there are still uncertainties related to local-scale patterns of shrub growth, resulting interactions among vegetation functional groups, and the relative roles of disturbance and climate as drivers of observed change. Here, we present evidence that widespread and rapid shrub expansion and lichen declines over a 15,000 km² area of the western Canadian Arctic have been driven by regional increases in temperature. Using 30 m resolution Landsat satellite imagery and high resolution repeat color-infrared aerial photographs, we show that 85% of the land surface has a positive 1985–2011 trend (P < 0.05) in NDVI, making this one of the most intensely greening regions in the Arctic. Strong positive trends (>0.03 NDVI/decade) occurred consistently across all landscape positions and most vegetation types. Comparison of 208, 1:2,000 scale vertical air photo pairs from 1980 and 2013 clearly shows that this greening was driven by increased canopy cover of erect dwarf and tall shrubs, with declines in terricolous lichen cover. Disturbances caused by wildfires, exploratory gas wells, and drained lakes all produced strong, yet localized increases in NDVI due to shrub growth. Our analysis also shows that a 4°C winter temperature increase over the past 30 years, leading to warmer soils and enhanced nutrient mineralization provides the best explanation for observed vegetation change. These observations thus provide early corroboration for modeling studies predicting large-scale vegetation shifts in low-Arctic ecosystems from climate change.     

Satellite microwave detection of boreal forest recovery from the extreme 2004 wildfires in Alaska and Canada

The rate of vegetation recovery from boreal wildfire influences terrestrial carbon cycle processes and climate feedbacks by affecting the surface energy budget and land‐atmosphere carbon exchange. Previous forest recovery assessments using satellite optical‐infrared normalized difference vegetation index (NDVI) and tower CO₂ eddy covariance techniques indicate rapid vegetation recovery within 5–10 years, but these techniques are not directly sensitive to changes in vegetation biomass. Alternatively, the vegetation optical depth (VOD) parameter from satellite passive microwave remote sensing can detect changes in canopy biomass structure and may provide a useful metric of post‐fire vegetation response to inform regional recovery assessments. We analyzed a multi‐year (2003–2010) satellite VOD record from the NASA AMSR‐E (Advanced Microwave Scanning Radiometer for EOS) sensor to estimate forest recovery trajectories for 14 large boreal fires from 2004 in Alaska and Canada. The VOD record indicated initial post‐fire canopy biomass recovery within 3–7 years, lagging NDVI recovery by 1–5 years. The VOD lag was attributed to slower non‐photosynthetic (woody) and photosynthetic (foliar) canopy biomass recovery, relative to the faster canopy greenness response indicated from the NDVI. The duration of VOD recovery to pre‐burn conditions was also directly proportional (P < 0.01) to satellite (moderate resolution imaging spectroradiometer) estimated tree cover loss used as a metric of fire severity. Our results indicate that vegetation biomass recovery from boreal fire disturbance is generally slower than reported from previous assessments based solely on satellite optical‐infrared remote sensing, while the VOD parameter enables more comprehensive assessments of boreal forest recovery.     

Remotely sensed vegetation phenology and productivity along a climatic gradient: on the value of incorporating the dimension of woody plant cover

Aim Woody plants affect vegetation–environment interactions by modifying microclimate, soil moisture dynamics and carbon cycling. In examining broad‐scale patterns in terrestrial vegetation dynamics, explicit consideration of variation in the amount of woody plant cover could provide additional explanatory power that might not be available when only considering landscape‐scale climate patterns or specific vegetation assemblages. Here we evaluate the interactive influence of woody plant cover on remotely sensed vegetation dynamics across a climatic gradient along a sky island. Location The Santa Rita Mountains, Arizona, USA. Methods Using a satellite‐measured normalized difference vegetation index (NDVI) from 2000 to 2008, we conducted time‐series and regression analyses to explain the variation in functional attributes of vegetation (productivity, seasonality and phenology) related to: (1) vegetation community, (2) elevation as a proxy for climate, and (3) woody plant cover, given the effects of the other environmental variables, as an additional ecological dimension that reflects potential vegetation–environment feedbacks at the local scale. Results NDVI metrics were well explained by interactions among elevation, vegetation community and woody plant cover. After accounting for elevation and vegetation community, woody plant cover explained up to 67% of variation in NDVI metrics and, notably, clarified elevation‐ and community‐specific patterns of vegetation dynamics across the gradient. Main conclusions In addition to the environmental factors usually considered – climate, reflecting resources and constraints, and vegetation community, reflecting species composition and relative dominance – woody plant cover, a broad‐scale proxy of many vegetation–environment interactions, represents an ecological dimension that provides additional process‐related understanding of landscape‐scale patterns of vegetation function.     

The greening and browning of Alaska based on 1982–2003 satellite data

Aim To examine the trends of 1982–2003 satellite‐derived normalized difference vegetation index (NDVI) values at several spatial scales within tundra and boreal forest areas of Alaska. Location Arctic and subarctic Alaska. Methods Annual maximum NDVI data from the twice monthly Global Inventory Modelling and Mapping Studies (GIMMS) NDVI 1982–2003 data set with 64‐km² pixels were extracted from a spatial hierarchy including three large regions: ecoregion polygons within regions, ecozone polygons within boreal ecoregions and 100‐km climate station buffers. The 1982–2003 trends of mean annual maximum NDVI values within each area, and within individual pixels, were computed using simple linear regression. The relationship between NDVI and temperature and precipitation was investigated within climate station buffers. Results At the largest spatial scale of polar, boreal and maritime regions, the strongest trend was a negative trend in NDVI within the boreal region. At a finer scale of ecoregion polygons, there was a strong positive NDVI trend in cold arctic tundra areas, and a strong negative trend in interior boreal forest areas. Within boreal ecozone polygons, the weakest negative trends were from areas with a maritime climate or colder mountainous ecozones, while the strongest negative trends were from warmer basin ecozones. The trends from climate station buffers were similar to ecoregion trends, with no significant trends from Bering tundra buffers, significant increasing trends among arctic tundra buffers and significant decreasing trends among interior boreal forest buffers. The interannual variability of NDVI among the arctic tundra buffers was related to the previous summer warmth index. The spatial pattern of increasing tundra NDVI at the pixel level was related to the west‐to‐east spatial pattern in changing climate across arctic Alaska. There was no significant relationship between interannual NDVI and precipitation or temperature among the boreal forest buffers. The decreasing NDVI trend in interior boreal forests may be due to several factors including increased insect/disease infestations, reduced photosynthesis and a change in root/leaf carbon allocation in response to warmer and drier growing season climate. Main conclusions There was a contrast in trends of 1982–2003 annual maximum NDVI, with cold arctic tundra significantly increasing in NDVI and relatively warm and dry interior boreal forest areas consistently decreasing in NDVI. The annual maximum NDVI from arctic tundra areas was strongly related to a summer warmth index, while there were no significant relationships in boreal areas between annual maximum NDVI and precipitation or temperature. Annual maximum NDVI was not related to spring NDVI in either arctic tundra or boreal buffers.     

Predicting growth of mat‐forming lichens on a landscape scale – comparing models with different complexities

During the 20th century, forestry practices has adversely affected lichen‐rich habitats. Mat‐forming lichens are important components of the vegetation of boreal and arctic ecosystems and are the main reindeer forage during the winter. To support the long‐term management of lichens in such habitats we developed models for predicting the growth of two common species. The lichens were transplanted across northern Scandinavia along a west‐east gradient varying in precipitation, temperature and irradiance. Growth was recorded seasonally over 16 months and ranged from ?4.8 to 34.6% and ?12.7 to 34.7% dry weight change for Cetraria stellaris and Cladina islandica, respectively. Growth was light limited below canopies with more than ca 60% cover and highest at the more humid sites when light levels were optimal. The models were based on various meteorological parameters, irradiance, physiological data and lichen hydration status; the latter was derived from a recently developed lichen hydration model. Our models' abilities to predict growth, both annually and seasonally (i.e. in summer), were evaluated in relation to their complexity and their potential usefulness from a management perspective. One parameter related to irradiance (the logarithm of site openness) was valuable in the prediction of annual growth for both species and could, in combination with precipitation, explain 52% of the variation in annual growth for C. stellaris and, in combination with total wet time and the irradiance received while wet, explain 66% of the variation in annual growth for C. islandica. The best simplified model explained 43% of the variation in annual growth for C. stellaris, using stem basal area and the annual normal temperature, and 24% for C. islandica using basal area alone. It is concluded that ensuring sufficient irradiance below the forest canopy is of crucial importance in the long‐term management of mat‐forming lichens and that simplified models can be used to identify appropriate habitats.     

Spatial heterogeneity of tundra vegetation response to recent temperature changes

The spatial heterogeneity of recent decadal dynamics in vegetation greenness and biomass in response to changes in summer warmth index (SWI) was investigated along spatial gradients on the Arctic Slope of Alaska. Image spatial analysis was used to examine the spatial pattern of greenness dynamics from 1991 to 2000 as indicated by variations of the maximum normalized difference vegetation index (Peak NDVI) and time‐integrated NDVI (TI‐NDVI) along latitudinal gradients. Spatial gradients for both the means and temporal variances of the NDVI indices for 0.1° latitude intervals crossing three bioclimate subzones were analyzed along two north–south Arctic transects. NDVI indices were generally highly variable over the decade, with great heterogeneity across the transects. The greatest variance in TI‐NDVI was found in low shrub vegetation to the south (68.7–68.8°N) and corresponded to high fractional cover of shrub tundra and moist acidic tundra (MAT), while the greatest variance in Peak‐NDVI predominately occurred in areas dominated by wet tundra (WT) and moist nonacidic tundra (MNT). Relatively high NDVI temporal variances were also related to specific transitional areas between dominant vegetation types. The regional temporal variances of NDVI from 1991 to 2000 were largely driven by meso‐scale climate dynamics. The spatial heterogeneity of the NDVI variance was mostly explained by the fractional land cover composition, different responses of each vegetation type to climate change, and patterned ground features. Aboveground plant biomass exhibited similar spatial heterogeneity as TI‐NDVI; however, spatial patterns are slightly different from NDVI because of their nonlinear relationship.     

Vegetation recovery following extreme winter warming events in the sub-Arctic estimated using NDVI from remote sensing and handheld passive proximal sensors

Extreme winter warming events in the sub-Arctic have caused considerable vegetation damage due to rapid changes in temperature and loss of snow cover. The frequency of extreme weather is expected to increase due to climate change thereby increasing the potential for recurring vegetation damage in Arctic regions. Here we present data on vegetation recovery from one such natural event and multiple experimental simulations in the sub-Arctic using remote sensing, handheld passive proximal sensors and ground surveys.Normalized difference vegetation index (NDVI) recovered fast (2 years), from the 26% decline following one natural extreme winter warming event. Recovery was associated with declines in dead Empetrum nigrum (dominant dwarf shrub) from ground surveys. However, E. nigrum healthy leaf NDVI was also reduced (16%) following this winter warming event in experimental plots (both control and treatments), suggesting that non-obvious plant damage (i.e., physiological stress) had occurred in addition to the dead E. nigrum shoots that was considered responsible for the regional 26% NDVI decline. Plot and leaf level NDVI provided useful additional information that could not be obtained from vegetation surveys and regional remote sensing (MODIS) alone.The major damage of an extreme winter warming event appears to be relatively transitory. However, potential knock-on effects on higher trophic levels (e.g., rodents, reindeer, and bear) could be unpredictable and large. Repeated warming events year after year, which can be expected under winter climate warming, could result in damage that may take much longer to recover.     

Assessment of vegetation cover by lichen-indication methods (by the example of the north of Central Siberia)

The vegetation cover in the north of Central Siberia has been assessed from lichenological data. The approaches and methods of lichen-based indication of the state of vegetation cover have been developed with the application of the data on diversity of lichens and lichen synusias, their projective cover and morphological deviations. The species of lichens and synusias that can be used for indication purposes have been defined. The changes in the characteristics of the lichen component in vegetation cover under the increasing chemical air pollution caused by industrial plants have been examined. The early deviations are indicated by morphological changes of lichen thalli, species depletion, and diversity of lichen synusias. Practical recommendations on lichen indication of the vegetation cover in the north of Siberia have been given.     

Wildlife species benefitting from a greener Arctic are most sensitive to shrub cover at leading range edges

Widespread expansion of shrubs is occurring across the Arctic. Shrub expansion will substantially alter arctic wildlife habitats. Identifying which wildlife species are most affected by shrubification is central to predicting future arctic community composition. Through meta‐analysis, we synthesized the published evidence for effects of canopy‐forming shrubs on birds and mammals in the Arctic and Subarctic. We examined variation in species behaviour, distribution and population dynamics in birds and mammals in response to shrub cover (including shrub cover indicators such as shrub occurrence, extent, density and height). We also assessed the degree of heterogeneity in wildlife responses to shrub cover and synthesized the remaining literature that did not fit the criteria for our quantitative meta‐analyses. Species from higher green vegetation biomass habitats (high Normalized Difference Vegetation Index, NDVI, across their distribution) were more likely to respond positively to shrub cover, demonstrating the potential for species to expand from boreal to arctic habitats under shrubification. Wildlife populations located in the lowest vegetation biomass (low NDVI) areas of their species’ range had the greatest proportion of positive responses to shrub cover, highlighting how increases in performance at leading edges of invaders distributions may be particularly rapid. This demonstrates the need to study species at these leading edges to accurately predict expansion potential. Arctic specialists were poorly represented across studies (limited to 5 bird and 0 mammal species), this knowledge gap potentially explains the few reported negative effects of shrub cover (3 of 29 species). Species responses to shrub cover showed substantial heterogeneity and varied among sites and years in all studies with sufficient replication to detect such variation. Our study highlights the importance of responses at species range edges in determining outcomes of shrubification for arctic birds and mammals and the need for greater examination of potential wildlife losers under shrubification.     

Analysing forest recovery after wildfire disturbance in boreal Siberia using remotely sensed vegetation indices

Wildfires have major effects on forest dynamics, succession and the carbon cycle in the boreal biome. They are a significant source of carbon emissions, and current observed changes in wildfire regimes due to changes in climate could affect the balance of the boreal carbon pool. A better understanding of postwildfire vegetation dynamics in boreal forests will help predict the future role of boreal forests as a carbon sink or source. Time series of Normalized Difference Vegetation Index (NDVI) and Normalized Difference Shortwave Infrared Index (NDSWIR) derived from Moderate Resolution Imaging Spectroradiometer (MODIS) aboard the Terra satellite were used to investigate whether characteristic temporal patterns exist for stands of different ages in the Siberian boreal forests and whether their postwildfire dynamics are influenced by variables such as prewildfire vegetation cover. Two types of forests, evergreen needle‐leaf (ENF) and deciduous needle‐leaf (DNF), were studied by analysing a sample of 78 burned forest areas. In order to study a longer time frame, a chronosequence of burned areas of different ages was built by coupling information on location and age provided by a forest burned area database (from 1992 to 2003) to MODIS NDVI and NDSWIR time series acquired from 2001 to 2005. For each of the burned areas, an adjacent unburned control plot representing the same forest type was selected, with the aim of separating the interannual variations caused by climate from changes in NDVI and NDSWIR behaviour due to a wildfire. The results suggest that it takes more than 13 years for the temporal NDVI and NDSWIR signal to recover fully after wildfire. NDSWIR, which is associated to canopy moisture, needs a longer recovery period than NDVI, which is associated to vegetation greenness. The results also suggest that variability observed in postwildfire NDVI and NDSWIR can be explained partially by the dominant forest type: while 13 years after a fire NDVI and NDSWIR are similar for ENF and DNF, the initial impact appears to be greater on the NDVI and NDSWIR of ENF, suggesting a faster recovery by ENF.     

Permafrost thaw induces short-term increase in vegetation productivity in northwestern Canada

Over the past several decades, various trends in vegetation productivity, from increases to decreases, have been observed throughout Arctic–Boreal ecosystems. While some of this variation can be explained by recent climate warming and increased disturbance, very little is known about the impacts of permafrost thaw on productivity across diverse vegetation communities. Active layer thickness data from 135 permafrost monitoring sites along a 10° latitudinal transect of the Northwest Territories, Canada, paired with a Landsat time series of normalized difference vegetation index from 1984 to 2019, were used to quantify the impacts of changing permafrost conditions on vegetation productivity. We found that active layer thickness contributed to the observed variation in vegetation productivity in recent decades in the northwestern Arctic–Boreal, with the highest rates of greening occurring at sites where the near-surface permafrost recently had thawed. However, the greening associated with permafrost thaw was not sustained after prolonged periods of thaw and appeared to diminish after the thaw front extended outside the plants' rooting zone. Highest rates of greening were found at the mid-transect sites, between 62.4° N and 65.2° N, suggesting that more southernly sites may have already surpassed the period of beneficial permafrost thaw, while more northern sites may have yet to reach a level of thaw that supports enhanced vegetation productivity. These results indicate that the response of vegetation productivity to permafrost thaw is highly dependent on the extent of active layer thickening and that increases in productivity may not continue in the coming decades.     

Rich and cold: diversity,distribution and drivers of fungal communities in patterned‐ground ecosystems of the North American Arctic

Fungi are abundant and functionally important in the Arctic, yet comprehensive studies of their diversity in relation to geography and environment are not available. We sampled soils in paired plots along the North American Arctic Transect (NAAT), which spans all five bioclimatic subzones of the Arctic. Each pair of plots contrasted relatively bare, cryoturbated patterned‐ground features (PGFs) and adjacent vegetated between patterned‐ground features (bPGFs). Fungal communities were analysed via sequencing of 7834 ITS‐LSU clones. We recorded 1834 OTUs – nearly half the fungal richness previously reported for the entire Arctic. These OTUs spanned eight phyla, 24 classes, 75 orders and 120 families, but were dominated by Ascomycota, with one‐fifth belonging to lichens. Species richness did not decline with increasing latitude, although there was a decline in mycorrhizal taxa that was offset by an increase in lichen taxa. The dominant OTUs were widespread even beyond the Arctic, demonstrating no dispersal limitation. Yet fungal communities were distinct in each subzone and were correlated with soil pH, climate and vegetation. Communities in subzone E were distinct from the other subzones, but similar to those of the boreal forest. Fungal communities on disturbed PGFs differed significantly from those of paired stable areas in bPGFs. Indicator species for PGFs included lichens and saprotrophic fungi, while bPGFs were characterized by ectomycorrhizal and pathogenic fungi. Our results suggest that the Arctic does not host a unique mycoflora, while Arctic fungi are highly sensitive to climate and vegetation, with potential to migrate rapidly as global change unfolds.     

Confounding effects of snow cover on remotely sensed vegetation indices of evergreen and deciduous trees: An experimental study

Located at northern latitudes and subject to large seasonal temperature fluctuations, boreal forests are sensitive to the changing climate, with evidence for both increasing and decreasing productivity, depending upon conditions. Optical remote sensing of vegetation indices based on spectral reflectance offers a means of monitoring vegetation photosynthetic activity and provides a powerful tool for observing how boreal forests respond to changing environmental conditions. Reflectance-based remotely sensed optical signals at northern latitude or high-altitude regions are readily confounded by snow coverage, hampering applications of satellite-based vegetation indices in tracking vegetation productivity at large scales. Unraveling the effects of snow can be challenging from satellite data, particularly when validation data are lacking. In this study, we established an experimental system in Alberta, Canada including six boreal tree species, both evergreen and deciduous, to evaluate the confounding effects of snow on three vegetation indices: the normalized difference vegetation index (NDVI), the photochemical reflectance index (PRI), and the chlorophyll/carotenoid index (CCI), all used in tracking vegetation productivity for boreal forests. Our results revealed substantial impacts of snow on canopy reflectance and vegetation indices, expressed as increased albedo, decreased NDVI values and increased PRI and CCI values. These effects varied among species and functional groups (evergreen and deciduous) and different vegetation indices were affected differently, indicating contradictory, confounding effects of snow on these indices. In addition to snow effects, we evaluated the contribution of deciduous trees to vegetation indices in mixed stands of evergreen and deciduous species, which contribute to the observed relationship between greenness-based indices and ecosystem productivity of many evergreen-dominated forests that contain a deciduous component. Our results demonstrate confounding and interacting effects of snow and vegetation type on vegetation indices and illustrate the importance of explicitly considering snow effects in any global-scale photosynthesis monitoring efforts using remotely sensed vegetation indices.     

Epigeic lichen communities of taiga and tundra regions

The major physiognomic and ecological categories of the lichen-rich, epigeic communities in the boreal (taiga) and arctic (tundra) zones are defined and their syntaxonomy and ecology in Europe, Asia and North America is reviewed. In the boreal and hemiarctic areas open, dry, acidophytic lichen woodlands are widespread, especially on sandy habitats. Their epigeic lichen synusiae are usually dominated by four fruticoseCladina species, being extremely homogeneous in species composition and structure throughout the boreal zone, while the dominant trees and the other vascular plant flora of the woodlands are geographically more variable. No phytosociological classification system exists that would cover most of these communities over the circumpolar regions. Very similar communities, though much more poorly known, are found on thin soils over Precambrian rock outcrops. Other sites to produce epigeic lichen communities include open sand dunes, treeless heathlands, drier bogs and many seral stages, like those on road banks. Boreal lichen-rich communities on eutrophic soils may be developed in semiarid regions, in particular. In the Arctic, lichens are common in most communities, and the driest ones are regularly lichen-dominated, whether acidophytic or eutrophytic, chionophytic or achionophytic. Detailed syntaxonomic systems for their classification have been developed, especially in Greenland and Scandinavian mountains (in oroarctic zones in the latter regions). The richest fruticose lichen areas are in continental, hemiarctic timberline regions in northern Siberia and Canada. The southern and middle arctic subzones are also characterized by many macrolichens, such asCetraria cucullata, C. nivalis, Alectoria ochroleuca, andThamnolia vermicularis, but everywhere also small, crustose lichens are common on soil, such asRinodina turfacea andLopadium pezizoideum, which are often overlooked in vegetation analyses. The presence of microlichens and the formation of mosaic micropatterns of soil lichen communities is particularly typical of the northern arctic subzone. The conservation problems of the boreal and arctic lichen communities include overgrazing by reindeer or caribou, which has caused delichenization in some regions, extensive forest and tundra fires, use of heavy transport vehicles in forestry and tundra operations, and, locally, heavy industrial air pollution.     

Measuring phenological variability from satellite imagery

Abstract. Vegetation phenological phenomena are closely related to seasonal dynamics of the lower atmosphere and are therefore important elements in global models and vegetation monitoring. Normalized difference vegetation index (NDVI) data derived from the National Oceanic and Atmospheric Administration's Advanced Very High Resolution Radiometer (AVHRR) satellite sensor offer a means of efficiently and objectively evaluating phenological characteristics over large areas. Twelve metrics linked to key phenological events were computed based on time-series NDVI data collected from 1989 to 1992 over the conterminous United States. These measures include the onset of greenness, time of peak NDVI, maximum NDVI, rate of greenup, rate of senescence, and integrated NDVI. Measures of central tendency and variability of the measures were computed and analyzed for various land cover types. Results from the analysis showed strong coincidence between the satellite-derived metrics and predicted phenological characteristics. In particular, the metrics identified interannual variability of spring wheat in North Dakota, characterized the phenology of four types of grasslands, and established the phenological consistency of deciduous and coniferous forests. These results have implications for large-area land cover mapping and monitoring. The utility of remotely sensed data as input to vegetation mapping is demonstrated by showing the distinct phenology of several land cover types. More stable information contained in ancillary data should be incorporated into the mapping process, particularly in areas with high phenological variability. In a regional or global monitoring system, an increase in variability in a region may serve as a signal to perform more detailed land cover analysis with higher resolution imagery.     

Productivity–diversity patterns in arctic tundra vegetation

Productivity has long been argued to be a major driver of species richness patterns. In the present study we test alternative productivity–diversity hypotheses using vegetation data from the vast Eurasian tundra. The productivity–species pool hypothesis predicts positive relationships at both fine and coarse grain sizes, whereas the productivity–interaction hypothesis predicts unimodal patterns at fine grain size, and monotonic positive patterns at coarse grain size. We furthermore expect to find flatter positive (productivity–species pool hypothesis) or more strongly negative (productivity–interaction hypothesis) relationships for lichens and bryophytes than for vascular plants, because as a group, lichens and bryophytes are better adapted to extreme arctic conditions and more vulnerable to competition for light than the taller‐growing vascular plants. The normalised difference vegetation index (NDVI) was used as a proxy of productivity. The generally unimodal productivity–diversity patterns were most consistent with the productivity–interaction hypothesis. There was a general trend of decreasing species richness from moderately to maximally productive tundra, in agreement with an increasing importance of competitive interactions. High richness of vascular plants and lichens occurred in moderately low productive tundra areas, whereas that of bryophytes occurred in the least productive tundra habitats covered by this study. The fine and coarse grain richness trends were surprisingly uniform and no variation in beta diversity along the productivity gradient was seen for vascular plants or bryophytes. However, lichen beta diversity varied along the productivity gradient, probably reflecting their sensitivity to habitat conditions and biotic interactions. Overall, the results show evidence that productivity–diversity gradients exist in tundra and that these appear to be largely driven by competitive interactions. Our results also imply that climate warming‐driven increases in productivity will strongly affect arctic plant diversity patterns.     

Pheno-climatic profiles of vegetation based on multitemporal analysis of satellite data

Satellite Remote Sensing offers numerous advantages: study of large areas in a short time, study of areas with not easy accessibility, synoptic observation of territory, multitemporal observations of the same area, monitoring land modifications and change detection studies. The effectiveness of using satellite images for studying and mapping vegetation and land use has been stressed since the early 1980s. The photosynthetically active vegetation presents a very characteristic spectral response. In fact, leaves absorb red radiation (RED) in order to do photosynthetic process and reflect almost completely near infrared (NIR) wavelengths. The most diffused index for quantifying photosynthetically active biomass is the NDVI (Normalized Difference Vegetation Index): NDVI = (NIR-RED)/(NIR+RED). The NDVI is calculated, for each pixel of the images analysed, through an appropriate software. Low values of NDVI correspond to scarcely vegetated areas, while high values indicate densely vegetated ones. In order to distinguish among vegetation typologies we need some images of the same territory, well distributed during the year, showing seasonal variations of vegetation photosynthetic activity. Then it will be e.g. very easy distinguish between evergreen species (with NDVI almost steady during the year) and deciduous ones. Several types of sensors aboard some satellites allow different investigations to be done. AVHRR sensor on NOAA and TM sensor on Landsat are among the best known sensors available. They have different characteristics as for spectral resolution (number of spectral bands), spatial resolution (size of each elementary cell) and temporal resolution (the period of the satellite passes on the same territory). Vegetation phenology (including biomass and photosynthetic activity) heavily depends on climatic factors. The most important are: solar radiance, with an annual cycle and maximum at summer solstice; air temperature, (depending on solar radiance) with an annual cycle and maximum more than one month later; water availability, which is strongly dependent on rainfalls; in the Mediterranean area they can have an annual cycle (maximum during winter) or a six-monthly one (maxima near the equinoxes). Having a set of multitemporal satellite data (e.g. 12 monthly NOAA-AVHRR images) we can use a mathematical model able to discriminate annual and six-monthly cycles. Through Fourier analysis, the mathematical model calculate, for each pixel of the image, the parameters of the annual NDVI profile and create a synthetic image (pheno-climatic map), in which the values of the three RGB components (Red, Green, Blue ) are proportional to the integral of the NDVI profile for the following three periods: B=Nov-Feb G=Mar-Jun R=Jul-Oct. A similarly analysis is possible with Landsat satellite data, which have a higher spatial resolution, given that some shrewdness are taken. In fact, it is necessary to select satellite images according to the presence of cloud cover, which is--over the Italian peninsula--quite common during the March-April and October-November intervals. The purpose of carrying out pheno-climatic maps can be accomplished using 6 Landsat-TM images well-distributed during a year, every two months, even if the images have been taken during different years.     

Growth and nitrogen relations in the mat-forming lichens Stereocaulon paschale and Cladonia stellaris

BACKGROUND AND AIMS: Mat-forming lichens in the genera Stereocaulon and Cladonia have ecosystem-level effects in northern boreal forests. Yet the factors affecting the productivity of mat-forming lichens are not known. The aim of the presented work was to investigate whether mat-forming lichens adapted to low N availability employ N-conserving mechanisms similar to those of vascular plants in nutrient-poor ecosystems. Specifically, the following questions were asked: (a) Do lichens translocate N from basal areas to apical growth areas? (b) Are the quantities of N translocated of ecological significance. (c) Is lichen growth dependent on tissue N concentration [N]. METHODS: Two different, but complementary, field experiments were conducted using the mat-forming N2-fixing Stereocaulon paschale and non-fixing Cladonia stellaris as model species. First, N translocation was investigated by feeding lichens with Na(15)NO3 either directly to the apex (theoretical sink) or to the basal part (theoretical source) and observing the redistribution of (15)N after a growth period. Secondly, growth and variation in [N] in thalli of different lengths was measured after a growth period. KEY RESULTS: (15)N fed to lower parts of lichen was translocated towards the growing top, but not vice versa, indicating physiologically dependent translocation that follows a sink-source relationship. In the growth experiment where thalli were cut to different lengths, the significant decrease in [N] in apices of short vs. longer thalli after a growth period is consistent with internal relocation as an ecologically important source of N. CONCLUSIONS: The presented results demonstrate that internal recycling of N occurs in both species investigated and may be ecologically important in these mat-forming lichens under field conditions. The higher nitrogen use efficiency and relative growth rate in C. stellaris in comparison with S. paschale probably enable C. stellaris to dominate the ground cover vegetation in dry boreal coniferous forests under undisturbed conditions.     

Estimating plant abundance using inflated beta distributions: Applied learnings from a lichen–caribou ecosystem

Quantifying abundance and distribution of plant species can be difficult because data are often inflated with zero values due to rarity or absence from many ecosystems. Terrestrial fruticose lichens (Cladonia and Cetraria spp.) occupy a narrow ecological niche and have been linked to the diets of declining caribou and reindeer populations (Rangifer tarandus) across their global distribution, and conditions related to their abundance and distribution are not well understood. We attempted to measure effects related to the occupancy and abundance of terrestrial fruticose lichens by sampling and simultaneously modeling two discrete conditions: absence and abundance. We sampled the proportion cover of terrestrial lichens at 438 vegetation plots, including 98 plots having zero lichens. A zero‐inflated beta regression model was employed to simultaneously estimate both the absence and the proportion cover of terrestrial fruticose lichens using fine resolution satellite imagery and light detection and ranging (LiDAR) derived covariates. The probability of lichen absence significantly increased with shallower groundwater, taller vegetation, and increased Sphagnum moss cover. Vegetation productivity, Sphagnum moss cover, and seasonal changes in photosynthetic capacity were negatively related to the abundances of terrestrial lichens. Inflated beta regression reliably estimated the abundance of terrestrial lichens (R² = .74) which was interpolated on a map at fine resolution across a caribou range to support ecological conservation and reclamation. Results demonstrate that sampling for and simultaneously estimating both occupancy and abundance offer a powerful approach to improve statistical estimation and expand ecological inference in an applied setting. Learnings are broadly applicable to studying species that are rare, occupy narrow niches, or where the response variable is a proportion value containing zero or one, which is typical of vegetation cover data.     

Comparison of five physiological parameters to assess the vitality of the lichen Ramalina lacera exposed to air pollution

To determine the environmental impact of industrial activity, we examined and compared the following parameters of physiological integrity in the epiphytic fruticose lichen Ramalina lacera. (1) Potential quantum yield of PSII expressed as the chlorophyll fluorescence ratio F_v/F_m. (2) Spectral reflectance expressed as values of normalized difference vegetation index (NDVI). (3) Production of ethylene. (4) Electrolyte leakage brought about by degrading cell membranes in terms of electric conductivity. (5) The ratio A_435nm/A_415nm indicating the disintegration of chlorophyll. The amounts of Ba, Cu, K, Ni, S, V and Zn contained in the lichen thallus were measured to quantify the degree of pollution. Some of the lichen‐carrying twigs collected at a relatively unpolluted control site were resuspended on the original trees as controls. Other lichens were transplanted to 19 biomonitoring sites. Transplanted lichens in polluted sites contained higher amounts of Ba, Ni, S, V and Zn than lichens in the control site and in most of the rural sites upon an exposure period of 8 months. Statistical analysis revealed negative correlations between F_v/F_m ratios and Ba contents of transplants. High Ba, Cu, Ni and Zn contents correlated negatively with NDVI values. NDVI values correlated with A_435nm/A_415nm, F_v/F_m and K. The ratio A_435nm/A_415nm correlated positively with K and negatively with Ba, Cu and Zn. The production of ethylene correlated positively with Cu and Ba and negatively with A_435nm/A_415nm, F_v/F_m and NDVI. Electric conductivity values correlated positively with Ba, Cu, Na, S, V and Zn and negatively with NDVI. Both elemental content and physiological alterations in transplants of R. lacera point to a high degree of contamination in the Haifa Bay region, which is polluted by fuel‐oil combustion apart from other industrial activities. The present work suggests that in our specific study area, the most sensitive parameter to assess the vitality of the lichen thallus is electric conductivity whereas ethylene production is less sensitive.