Bunting, E., Southworth, J., Herrero, H., Ryan, S., & Waylen, P. (2018). Understanding Long-Term Savanna Vegetation Persistence across Three Drainage Basins in Southern Africa. Remote Sensing, 10(7), 1013.
Abstract: Across savanna landscapes of southern Africa, people are strongly tied to the environment, meaning alterations to the landscape would impact livelihoods and socioecological development. Given the human-environment connection, it is essential to further our understanding of the drivers of savanna vegetation dynamics, and under increasing climate variability, to better understand the vegetation-climate relationship. Monthly time series of Advanced Very High-Resolution Radiometer (AVHRR)- and Moderate Resolution Imaging Spectroradiometer (MODIS) derived vegetation indices, available from as early as the 1980s, holds promise for the large-scale quantification of complex vegetation�climate dynamics and regional analyses of landscape change as related to global environmental changes. In this work, we employ time series based analyses to examine landscape-level vegetation greening patterns over time and across a significant precipitation gradient. In this study, we show that climate induced reductions in Normalized Difference Vegetation Index (NDVI; i.e., degradation or biomass decline) have had large spatial and temporal impacts across the Kwando, Okavango, and Zambezi catchments of southern Africa. We conclude that over time there have been alterations in the available soil moisture resulting from increases in temperature in every season. Such changes in the ecosystem dynamics of all three basins has led to system-wide changes in landscape greening patterns.
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Cacciapaglia, C., & van Woesik, R. (2015). Reef-coral refugia in a rapidly changing ocean. Glob Change Biol, .
Abstract: This study sought to identify climate-change thermal-stress refugia for reef corals in the Indian and Pacific Oceans. A species distribution modeling approach was used to identify refugia for 12 coral species that differed considerably in their local response to thermal stress. We hypothesized that the local response of coral species to thermal stress might be similarly reflected as a regional response to climate change. We assessed the contemporary geographic range of each species and determined their temperature and irradiance preferences using a k-fold algorithm to randomly select training and evaluation sites. That information was applied to downscaled outputs of global climate models to predict where each species is likely to exist by the year 2100. Our model was run with and without a 1 °C capacity to adapt to the rising ocean temperature. The results show a positive exponential relationship between the current area of habitat that coral species occupy and the predicted area of habitat that they will occupy by 2100. There was considerable decoupling between scales of response, however, and with further ocean warming some ‘winners’ at local scales will likely become ‘losers’ at regional scales. We predicted that nine of the 12 species examined will lose 24–50% of their current habitat. Most reductions are predicted to occur between the latitudes 5–15°, in both hemispheres. Yet when we modeled a 1 °C capacity to adapt, two ubiquitous species, Acropora hyacinthus and Acropora digitifera, were predicted to retain much of their current habitat. By contrast, the thermally tolerant Porites lobata is expected to increase its current distribution by 14%, particularly southward along the east and west coasts of Australia. Five areas were identified as Indian Ocean refugia, and seven areas were identified as Pacific Ocean refugia for reef corals under climate change. All 12 of these reef-coral refugia deserve high-conservation status.
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Tsai, H., Southworth, J., & Waylen, P. (2014). Spatial persistence and temporal patterns in vegetation cover across Florida, 1982-2006. Physical Geography, 35(2), 151–180.
Abstract: The study analyzes the spatial persistence and temporal patterns in vegetation cover across Florida by utilizing the Normalized Difference Vegetation Index (NDVI) time-series data derived from the Advanced Very High Resolution Radiometer from 1982 to 2006. Specifically, mean-variance analysis and persistence metrics are used to discern the significance of vegetation patterns, the significance of land cover and land-use change, and the relevance of climate variability across time and space. Results demonstrate a consistent, increasing pattern in the mean NDVI and its variance, especially during the late fall and winter season. A possible explanation of this increasing pattern is based on the Atlantic Multidecadal Oscillation, which switched from cold to warm phase after 1995 and is associated with increased winter precipitation. Additionally, the impacts of the El Niño Southern Oscillation can be detected through the decreased spatial variances of NDVI in warm-phase events, compared to cold-phase events, and the more pronounced nature of the pattern in fall/winter. This study proposes a novel set of techniques applied to satellite-derived vegetation data, which effectively discerns fine, statewide vegetation dynamics at appropriate spatial and temporal scales.
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Zhang, W., & Kirtman, B. (2019). Estimates of Decadal Climate Predictability From an Interactive Ensemble Model. Geophys. Res. Lett., 46(6), 3387–3397.
Abstract: Decadal climate predictability has received considerable scientific interest in recent years, yet the limits and mechanisms for decadal predictability are currently not well known. It is widely accepted that noise due to internal atmospheric dynamics at the air-sea interface influences predictability. The purpose of this paper is to use the interactive ensemble (IE) coupling strategy to quantify how internal atmospheric noise at the air-sea interface impacts decadal predictability. The IE technique can significantly reduce internal atmospheric noise and has proven useful in assessing seasonal-to-interannual variability and predictability. Here we focus on decadal timescales and apply the nonlinear local Lyapunov exponent method to the Community Climate System Model comparing control simulations with IE simulations. This is the first time the nonlinear local Lyapunov exponent has been applied to the state-of-the-art coupled models. The global patterns of decadal predictability are discussed from the perspective of internal atmospheric noise and ocean dynamics.
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