Mirela Tulbure
I am an Australian Research Council DECRA fellow and a senior lecturer (assistant professor w/ tenure U.S. equivalent) in the School of Biological, Earth and Environmental Science at the University of New South Wales (UNSW). Since joining UNSW in 2012, I have built the Geospatial Analysis for Environmental Change Lab (www.mirela-tulbure.com).
My work focuses on the integration of ecological research with the application of remote sensing, Geographic Information Systems (GIS), and spatial statistics across various spatial (landscape to continental) and temporal scales. Reaching across disciplines, I conduct quantitative research using terabytes of satellite data and high performance computing. Results can underpin water policy and management in areas with competing water demands.
Address: Sydney, Australia
My work focuses on the integration of ecological research with the application of remote sensing, Geographic Information Systems (GIS), and spatial statistics across various spatial (landscape to continental) and temporal scales. Reaching across disciplines, I conduct quantitative research using terabytes of satellite data and high performance computing. Results can underpin water policy and management in areas with competing water demands.
Address: Sydney, Australia
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Papers by Mirela Tulbure
greening and browning are influenced by variability in climatic
forcing. Quantitative spatial information on phenological
cycles and their variability is important for agricultural
applications, wildfire fuel accumulation, land management,
land surface modeling, and climate change studies.
Most phenology studies have focused on temperature-driven
Northern Hemisphere systems, where phenology shows annually
recurring patterns. However, precipitation-driven nonannual
phenology of arid and semi-arid systems (i.e., drylands)
received much less attention, despite the fact that they
cover more than 30% of the global land surface. Here, we
focused on Australia, a continent with one of the most variable
rainfall climates in the world and vast areas of dryland
systems, where a detailed phenological investigation and a
characterization of the relationship between phenology and
climate variability are missing.
To fill this knowledge gap, we developed an algorithm to
characterize phenological cycles, and analyzed geographic
and climate-driven variability in phenology from 2000 to
2013, which included extreme drought and wet years. We
linked derived phenological metrics to rainfall and the Southern
Oscillation Index (SOI). We conducted a continentwide
investigation and a more detailed investigation over the
Murray–Darling Basin (MDB), the primary agricultural area
and largest river catchment of Australia.
Results showed high inter- and intra-annual variability in
phenological cycles across Australia. The peak of phenological
cycles occurred not only during the austral summer,
but also at any time of the year, and their timing varied
by more than a month in the interior of the continent. The
magnitude of the phenological cycle peak and the integrated
greenness were most significantly correlated with monthly
SOI within the preceding 12 months. Correlation patterns
occurred primarily over northeastern Australia and within
the MDB, predominantly over natural land cover and particularly
in floodplain and wetland areas. Integrated greenness
of the phenological cycles (surrogate of vegetation productivity)
showed positive anomalies of more than 2 standard
deviations over most of eastern Australia in 2009–2010,
which coincided with the transition from the El Niño-induced
decadal droughts to flooding caused by La Niña.
Objective: To evaluate how surface water network structure, landscape resistance to movement, and flooding affect the connectivity of amphibian habitats within the Murray–Darling Basin (MDB), a highly modified but ecologically significant region of south-eastern Australia.
Methods: We evaluated potential connectivity network graphs based on circuit theory, Euclidean and least-cost path distances for two amphibian species with different dispersal abilities, and used graph theory metrics to compare regional- and patch-scale connectivity across a range of flooding scenarios.
Results: Circuit theory graphs were more connected than Euclidean and least-cost equivalents in floodplain environments, and less connected in highly modified or semi-arid regions. Habitat networks were highly fragmented for both species, with flooding playing a crucial role in facilitating landscape-scale connectivity. Both formally and informally protected habitats were more likely to form important connectivity “hubs” or “stepping stones” compared to non-protected habitats, and increased in importance with flooding.
Conclusions: Surface water network structure and the quality of the intervening landscape matrix combine to affect the connectivity of MDB amphibian habitats in ways which vary spatially and in response to flooding. Our findings highlight the importance of utilising organism-relevant connectivity models which incorporate landscape resistance to movement, and accounting for dynamic landscape-scale processes such as flooding when quantifying connectivity to inform the conservation of dynamic and highly modified environments.
Results did not predict an increase in maximum switchgrass yield but showed an overall shift in areas of high switchgrass productivity for both cytotypes. For upland cytotypes, the shift in high yields was concentrated in northern and north-eastern areas where there were increases in average growing season temperature, whereas for lowland cultivars the areas where yields were projected to increase were associated with increases in average early growing season precipitation.
These results highlight the fact that the influences of climate change on switchgrass yield are spatially heterogeneous and vary depending on cytotype. Knowledge of spatial distribution of suitable areas for switchgrass production under climate change should be incorporated into planning of current and future biofuel production. Understanding how switchgrass yields will be affected by future changes in climate is important for achieving a sustainable biofuels economy.
Lakes have reached extreme lows and are expected to decline with future climate change.
"
less-dynamic vegetation for prairie wetland complexes. The WLS model portrays the future PPR as a much less resilient ecosystem: The western PPR will be too dry and the eastern PPR will have too few functional wetlands and nesting habitat to support historic levels of waterfowl and other wetland-dependent species. Maintaining ecosystem goods and services at current levels in a warmer climate will be a major challenge for the conservation community."
greening and browning are influenced by variability in climatic
forcing. Quantitative spatial information on phenological
cycles and their variability is important for agricultural
applications, wildfire fuel accumulation, land management,
land surface modeling, and climate change studies.
Most phenology studies have focused on temperature-driven
Northern Hemisphere systems, where phenology shows annually
recurring patterns. However, precipitation-driven nonannual
phenology of arid and semi-arid systems (i.e., drylands)
received much less attention, despite the fact that they
cover more than 30% of the global land surface. Here, we
focused on Australia, a continent with one of the most variable
rainfall climates in the world and vast areas of dryland
systems, where a detailed phenological investigation and a
characterization of the relationship between phenology and
climate variability are missing.
To fill this knowledge gap, we developed an algorithm to
characterize phenological cycles, and analyzed geographic
and climate-driven variability in phenology from 2000 to
2013, which included extreme drought and wet years. We
linked derived phenological metrics to rainfall and the Southern
Oscillation Index (SOI). We conducted a continentwide
investigation and a more detailed investigation over the
Murray–Darling Basin (MDB), the primary agricultural area
and largest river catchment of Australia.
Results showed high inter- and intra-annual variability in
phenological cycles across Australia. The peak of phenological
cycles occurred not only during the austral summer,
but also at any time of the year, and their timing varied
by more than a month in the interior of the continent. The
magnitude of the phenological cycle peak and the integrated
greenness were most significantly correlated with monthly
SOI within the preceding 12 months. Correlation patterns
occurred primarily over northeastern Australia and within
the MDB, predominantly over natural land cover and particularly
in floodplain and wetland areas. Integrated greenness
of the phenological cycles (surrogate of vegetation productivity)
showed positive anomalies of more than 2 standard
deviations over most of eastern Australia in 2009–2010,
which coincided with the transition from the El Niño-induced
decadal droughts to flooding caused by La Niña.
Objective: To evaluate how surface water network structure, landscape resistance to movement, and flooding affect the connectivity of amphibian habitats within the Murray–Darling Basin (MDB), a highly modified but ecologically significant region of south-eastern Australia.
Methods: We evaluated potential connectivity network graphs based on circuit theory, Euclidean and least-cost path distances for two amphibian species with different dispersal abilities, and used graph theory metrics to compare regional- and patch-scale connectivity across a range of flooding scenarios.
Results: Circuit theory graphs were more connected than Euclidean and least-cost equivalents in floodplain environments, and less connected in highly modified or semi-arid regions. Habitat networks were highly fragmented for both species, with flooding playing a crucial role in facilitating landscape-scale connectivity. Both formally and informally protected habitats were more likely to form important connectivity “hubs” or “stepping stones” compared to non-protected habitats, and increased in importance with flooding.
Conclusions: Surface water network structure and the quality of the intervening landscape matrix combine to affect the connectivity of MDB amphibian habitats in ways which vary spatially and in response to flooding. Our findings highlight the importance of utilising organism-relevant connectivity models which incorporate landscape resistance to movement, and accounting for dynamic landscape-scale processes such as flooding when quantifying connectivity to inform the conservation of dynamic and highly modified environments.
Results did not predict an increase in maximum switchgrass yield but showed an overall shift in areas of high switchgrass productivity for both cytotypes. For upland cytotypes, the shift in high yields was concentrated in northern and north-eastern areas where there were increases in average growing season temperature, whereas for lowland cultivars the areas where yields were projected to increase were associated with increases in average early growing season precipitation.
These results highlight the fact that the influences of climate change on switchgrass yield are spatially heterogeneous and vary depending on cytotype. Knowledge of spatial distribution of suitable areas for switchgrass production under climate change should be incorporated into planning of current and future biofuel production. Understanding how switchgrass yields will be affected by future changes in climate is important for achieving a sustainable biofuels economy.
Lakes have reached extreme lows and are expected to decline with future climate change.
"
less-dynamic vegetation for prairie wetland complexes. The WLS model portrays the future PPR as a much less resilient ecosystem: The western PPR will be too dry and the eastern PPR will have too few functional wetlands and nesting habitat to support historic levels of waterfowl and other wetland-dependent species. Maintaining ecosystem goods and services at current levels in a warmer climate will be a major challenge for the conservation community."