ALBERT

Description: A century of hydrologic modification has altered the physical and biological drivers of landscape processes in the Everglades (southern Florida, USA). Restoring the ridge-slough patterned landscape, a dominant feature of the historical system, is a priority, but requires an understanding of pattern genesis mechanisms. Physical experiments to evaluate alternative pattern formation mechanisms are limited by the time scales of peat accumulation and loss, necessitating model-based comparisons, where support for a particular mechanism is based on model replication of extant patterning and trajectories of degradation. However, multiple mechanisms yield a central feature of ridge-slough patterning (patch elongation in the direction of historical flow), limiting the utility of that characteristic for discriminating among alternatives. Using data from vegetation maps we investigated the statistical features of ridge-slough spatial patterning (ridge density, patch perimeter, elongation, patch-area scaling, and spatial periodicity) to establish rigorous criteria for evaluating model performance, and to inform controls on pattern variation across the contemporary system. Mean water depth explained significant variation in ridge density, total perimeter, and length : width ratios, illustrating significant pattern response to existing hydrologic gradients. Two independent analyses (2-D periodograms and patch size distributions) provide strong evidence against regular patterning, with the landscape exhibiting neither a characteristic wavelength nor a characteristic patch size, both of which are expected under conditions that produce regular patterns. Rather, landscape properties suggest robust scale-free patterning, indicating genesis from the coupled effects of local facilitation and a global negative feedback operating uniformly at the landscape-scale. Critically, this challenges widespread invocation of meso-scale negative feedbacks for explaining ridge-slough pattern origins. These results help discern among genesis mechanisms and provide an improved statistical template against which to compare model outputs, as well as landscape trajectories with future restoration.

Description: Self-organized landscape patterning can arise in response to multiple processes. Discriminating among alternative patterning mechanisms, particularly where experimental manipulations are untenable, requires process-based models. Previous modeling studies have attributed patterning in the Everglades (Florida, USA) to sediment redistribution and anisotropic soil hydraulic properties. In this work, we tested an alternate theory, the self-organizing canal (SOC) hypothesis, by developing a cellular automata model that simulates pattern evolution via local positive feedbacks (i.e., facilitation) coupled with a global negative feedback based on hydrology. The model is forced by global hydroperiod that drives stochastic transitions between two patch types: ridge (higher elevation) and slough (lower elevation). We evaluated model performance using multiple criteria based on six statistical and geostatistical properties observed in reference portions of the Everglades landscape: patch density, patch anisotropy, semivariogram ranges, power-law scaling of ridge areas, perimeter area fractal dimension, and characteristic pattern wavelength. Model results showed strong statistical agreement with reference landscapes, but only when anisotropically acting local facilitation was coupled with hydrologic global feedback, for which several plausible mechanisms exist. Critically, the model correctly generated fractal landscapes that had no characteristic pattern wavelength, supporting the invocation of global rather than scale-specific negative feedbacks.

Description: Self-organized landscape patterning can arise in response to multiple processes. Discriminating among alternative patterning mechanisms, particularly where experimental manipulations are untenable, requires process-based models. Previous modeling studies have attributed patterning in the Everglades (Florida, USA) to sediment redistribution and anisotropic soil hydraulic properties. In this work, we tested an alternate theory, the self-organizing-canal (SOC) hypothesis, by developing a cellular automata model that simulates pattern evolution via local positive feedbacks (i.e., facilitation) coupled with a global negative feedback based on hydrology. The model is forced by global hydroperiod that drives stochastic transitions between two patch types: ridge (higher elevation) and slough (lower elevation). We evaluated model performance using multiple criteria based on six statistical and geostatistical properties observed in reference portions of the Everglades landscape: patch density, patch anisotropy, semivariogram ranges, power-law scaling of ridge areas, perimeter area fractal dimension, and characteristic pattern wavelength. Model results showed strong statistical agreement with reference landscapes, but only when anisotropically acting local facilitation was coupled with hydrologic global feedback, for which several plausible mechanisms exist. Critically, the model correctly generated fractal landscapes that had no characteristic pattern wavelength, supporting the invocation of global rather than scale-specific negative feedbacks.

Description: The Indian Ocean Dipole (IOD) and the El Niño-Southern Oscillation (ENSO) frequently co-occur, driving significant interannual changes within the Indian Ocean. We use a four-decade hindcast from a coupled bio-physical ocean general circulation model, to disentangle patterns of chlorophyll anomalies driven by these two climate modes. Comparisons with remotely-sensed records show that the simulation competently reproduces the chlorophyll seasonal cycle, as well as open-ocean anomalies during the 1997–1998 ENSO and IOD event. Results show that anomalous surface and euphotic-layer chlorophyll blooms in the eastern equatorial Indian Ocean in fall, and southern Bay of Bengal in winter, are primarily related to IOD forcing. IOD depresses integrated chlorophyll in the 5° S–10° S thermocline ridge region, even though the signal is negligible in surface chlorophyll. A previously-unreported negative influence of IOD on chlorophyll concentrations is also shown in a region around the southern tip of India. The only investigated region where ENSO has a greater influence on chlorophyll than does IOD, is in the Somalia upwelling region, where it causes a decrease in fall and winter chlorophyll by reducing local upwelling winds. Lastly, we show that the chlorophyll impact of climate indices is frequently asymmetric, with a general tendency for larger positive than negative chlorophyll anomalies. ENSO and IOD cause significant and predictable regional re-organisation of phytoplankton productivity via their influence on near-surface oceanography. Resolving the details of these effects should improve our understanding, and eventually gain predictability, of interannual changes in Indian Ocean productivity, fisheries, ecosystems and carbon budgets.

Description: The Indian Ocean Dipole (IOD) and the El Niño/Southern Oscillation (ENSO) are independent climate modes, which frequently co-occur, driving significant interannual changes within the Indian Ocean. We use a four-decade hindcast from a coupled biophysical ocean general circulation model, to disentangle patterns of chlorophyll anomalies driven by these two climate modes. Comparisons with remotely sensed records show that the simulation competently reproduces the chlorophyll seasonal cycle, as well as open-ocean anomalies during the 1997/1998 ENSO and IOD event. Results suggest that anomalous surface and euphotic-layer chlorophyll blooms in the eastern equatorial Indian Ocean in fall, and southern Bay of Bengal in winter, are primarily related to IOD forcing. A negative influence of IOD on chlorophyll concentrations is shown in a region around the southern tip of India in fall. IOD also depresses depth-integrated chlorophyll in the 5–10° S thermocline ridge region, yet the signal is negligible in surface chlorophyll. The only investigated region where ENSO has a greater influence on chlorophyll than does IOD, is in the Somalia upwelling region, where it causes a decrease in fall and winter chlorophyll by reducing local upwelling winds. Yet unlike most other regions examined, the combined explanatory power of IOD and ENSO in predicting depth-integrated chlorophyll anomalies is relatively low in this region, suggestive that other drivers are important there. We show that the chlorophyll impact of climate indices is frequently asymmetric, with a general tendency for larger positive than negative chlorophyll anomalies. Our results suggest that ENSO and IOD cause significant and predictable regional re-organisation of chlorophyll via their influence on near-surface oceanography. Resolving the details of these effects should improve our understanding, and eventually gain predictability, of interannual changes in Indian Ocean productivity, fisheries, ecosystems and carbon budgets.