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The Arctic is currently undergoing intense changes in climate; vegetation composition and productivity are expected to respond to such changes. To understand the impacts of climate change on the function of Arctic tundra ecosystems within the global carbon cycle, it is crucial to improve the understanding of vegetation distribution and heterogeneity at multiple scales. Information detailing the fine-scale spatial distribution of tundra communities provided by high resolution vegetation mapping, is needed to understand the relative contributions of and relationships between single vegetation community measurements of greenhouse gas fluxes (e.g., ∼1 m chamber flux) and those encompassing multiple vegetation communities (e.g., ∼300 m eddy covariance measurements). The objectives of this study were: (1) to determine whether dominant Arctic tundra vegetation communities found in different locations are spectrally distinct and distinguishable using field spectroscopy methods; and (2) to test which combination of raw reflectance and vegetation indices retrieved from field and satellite data resulted in accurate vegetation maps and whether these were transferable across locations to develop a systematic method to map dominant vegetation communities within larger eddy covariance tower footprints distributed along a 300 km transect in northern Alaska. We showed vegetation community separability primarily in the 450-510 nm, 630-690 nm and 705-745 nm regions of the spectrum with the field spectroscopy data. This is line with the different traits of these arctic tundra communities, with the drier, often non-vascular plant dominated communities having much higher reflectance in the 450-510 nm and 630-690 nm regions due to the lack of photosynthetic material, whereas the low reflectance values of the vascular plant dominated communities highlight the strong light absorption found here. High classification accuracies of 92% to 96% were achieved using linear discriminant analysis with raw and rescaled spectroscopy reflectance data and derived vegetation indices. However, lower classification accuracies (∼70%) resulted when using the coarser 2.0 m WorldView-2 data inputs. The results from this study suggest that tundra vegetation communities are separable using plot-level spectroscopy with hand-held sensors. These results also show that tundra vegetation mapping can be scaled from the plot level (<1 m) to patch level (<500 m) using spectroscopy data rescaled to match the wavebands of the multispectral satellite remote sensing. We find that developing a consistent method for classification of vegetation communities across the flux tower sites is a challenging process, given the spatial variability in vegetation communities and the need for detailed vegetation survey data for training and validating classification algorithms. This study highlights the benefits of using fine-scale field spectroscopy measurements to obtain tundra vegetation classifications for landscape analyses and use in carbon flux scaling studies. Improved understanding of tundra vegetation distributions will also provide necessary insight into the ecological processes driving plant community assemblages in Arctic environments. [ABSTRACT FROM AUTHOR]

In mountain ecosystems, species can be said to respond synchronously to environmental change when the elevation ranges of vegetation types and their associated vertebrates expand or contract in the same direction. Conversely, the response is asynchronous when the elevation ranges of vegetation types and associated vertebrates change in different directions. The capacity of vertebrate species to respond synchronously with change in the elevation ranges of the vegetation that comprises their habitat is likely a function of their ecological traits. Here we combine measures of elevation range shifts in 23 vertebrate species with those of their associated vegetation types across 80 yr, on a large elevation transect in California's Sierra Nevada mountains that encompasses Yosemite National Park. Half the species' shifts were synchronous with vegetation shifts, ¼ of the species were asynchronous, and the others showed no relationship. Most species that responded synchronously to changes in vegetation elevation ranges expanded their elevation range, and are inhabitants of low and intermediate elevations. In contrast, those species whose range shifts were asynchronous to associated vegetation shifts inhabit high elevations. These species experienced contraction in elevation range even while their associated vegetation types expanded. However, these species were responding synchronously to a subset of their associated vegetation types. Considering trait-based predictors, omnivores were more synchronous than herbivores. Our results on synchronous and asynchronous elevation shifts with vegetation may permit more accurate modeling of future ranges for vertebrates in California's Sierra Nevada. The approach also offers a new method for use in assessment of vertebrate vulnerability in other mountain regions, and can be an important component of assessing their vulnerability to climate change. [ABSTRACT FROM AUTHOR]

Protected Areas (PAs) are important wildlife refuges and act as climate change buffers, but they may impact human livelihoods, particularly engendering a high risk of negative human-wildlife interactions (HWI). Understanding synergies and tradeoffs among the drivers of overall human vulnerability within PAs is needed to ensure good outcomes for conservation and human wellbeing. We examined how climate variability, HWI, and socio-demographics affect livelihood vulnerability across three PAs in Mozambique, Southeast Africa. We used structured questionnaires to obtain information on livelihood vulnerability and socialecological context-specific variables. We applied principal component analysis to understand synergies and trade-offs between the dimensions of vulnerability and linear models to test the effect of social-ecological drivers on vulnerability. We show that households are mostly vulnerable within PAs due to exposure to climate variability and to HWI, and their low capacity to employ livelihood strategies or to have a strong social network. Furthermore, we show that vulnerability to HWI and climate variability increases with distance to strict protection areas within the PAs and distance to rivers, which implies that proximity to strict protection areas and rivers within PAs still promotes better livelihood conditions than elsewhere. On the other hand, we also found that lower access to infrastructure and other livelihood assets enhances vulnerability, which reflects a trade-off within PAs that potentially limits the benefits of socially inclusive conservation. Our results show that the impacts of PAs, HWI, and climate on community vulnerability should not be viewed in isolation, but instead, conservation and livelihood improvement strategies should reflect their interconnectedness. Although livelihood vulnerability appears to be shaped by these general effects of PAs, it is important also to consider the local PA context when addressing or mitigating livelihood vulnerability in and around them [ABSTRACT FROM AUTHOR]

Earth's arid and semiarid ecosystems are subject to novel combinations of disruptive factors and unprecedented rates of change. Biotic soil crust is believed to be sensitive to impacts caused by land use and climate changes. This study examined the potential for spectral detection of different biological soil crusts (BSC: cyanobacteria, moss and lichen) and bare soil components at a long-term manipulative experiment at the Mojave Global Change Facility (MGCF) in southwestern Nevada. We evaluated the potential for spectral detection of experimental treatments using laboratory and field measured reflectance spectra in the second and third year of the experiment, and airborne hyperspectral data obtained in the third year of the manipulations for soil disturbance, increased summer rainfall, and dry nitrogen deposition. Laboratory spectra of individual components of biological soil crust and bare soil measured under controlled laboratory conditions were spectrally different over much of the spectrum and exhibited features at 0.42, 0.50, and 0.68 μm, which could differentiate these materials. Field measured spectra were more similar in overall shape in each of the MGCF treatments and individual BSC could not be distinguished. The field spectra most closely resemble cyanobacteria from laboratory measurements, which are known to cover up to 60% of the inter-shrub spaces. There were significant treatment differences between control, soil disturbance, and irrigation treatments in field spectral measurements and a spectral feature in the 2.00–2.08 μm region could distinguish these treatments. The treatments were also apparent in high spatial resolution (~4 m ground IFOV) airborne hyperspectral imagery using a minimum noise fraction (MNF) analysis, although treatments were not distinct in terms of laboratory or field-based specific features. Disturbance treatments were easily apparent in color-infrared imagery although other treatments were not... [Copyright &y& Elsevier]