ORCID Profile
0000-0003-2096-2242
Current Organisation
Brandenburgische Technische Universität Cottbus-Senftenberg
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Publications
Theory and empirical evidence for the irregularity of self-organized vegetation patterns
Publisher: Copernicus GmbH
Date: 28-03-2022
DOI: 10.5194/EGUSPHERE-EGU22-11905
Abstract: & & In arid environments, vegetation tends to self-organize into patches separated by bare soil. This is necessitated by the lack of water for sustaining a continuous vegetation cover and facilitated by the attraction of water from barren interpatch areas by the vegetation. This process is a positive feedback which introduces spatially heterogeneity into otherwise homogeneous environments, characterised by regular patterns. These patterns are typically considered to be periodic and distinguished on hand of their wavelength. Such patterns have so far been studied with numerical models which generate periodic patterns in homogeneous environments. However, environments are rarely homogeneous, as topography and soil-hydraulic properties vary in space. This raises the questions to which degree heterogeneity of vegetation is self-organized or imposed by the environment, and how environmental heterogeneity interacts with the self-organization process. In contrast to the persisting conceptual model of periodic patterns, natural vegetation exhibit a high degree of irregularity. Several studies have linked this irregularity to heterogeneity in the environment, but a comprehensive theory for analysing the irregularity has not yet been established. Furthermore remains the extend of irregularity unexplored on a global scale. To fill this gap, we, demonstrate empirically the global prevalence of irregularity in vegetation patterns and find that natural vegetation patterns are stochastic, rather than periodic. We then propose a stochastic framework to conceptually describe and measure the regularity, based on the spectral density of the patterns. In addition to the dominant wavelength, measuring the spatial scale, it reveals a novel parameter, measuring the regularity. The parameter is determined by the correlation structure and discriminates gradually between the limit cases of periodicity and white noise. Applied to natural and computer-generated patterns, we find that the former are highly irregular, while the latter are close to periodic. We reproduce the stochasticity of patterns with numerical models by introducing spatial heterogeneity of the model coefficients. We provide a fresh look at the nature of vegetations patterns and present a comprehensive theory for a more holistic understanding of self-organized systems.& & & & & img src=& quot ileStorageProxy.php?f=gnp.b390733f41e167285512461/sdaolpUECMynit/22UGE& app=m& a=0& c=abd147c2aca67c19a20b0a025d582dd3& ct=x& n=gnp.elif& d=1& quot alt=& quot & quot width=& quot & quot height=& quot & quot & & &
Hydrology of inland tropical lowlands: the Kapuas and Mahakam wetlands
Publisher: Copernicus GmbH
Date: 24-05-2017
DOI: 10.5194/HESS-21-2579-2017
Abstract: Abstract. Wetlands are important reservoirs of water, carbon and bio ersity. They are typical landscapes of lowland regions that have high potential for water retention. However, the hydrology of these wetlands in tropical regions is often studied in isolation from the processes taking place at the catchment scale. Our main objective is to study the hydrological dynamics of one of the largest tropical rainforest regions on an island using a combination of satellite remote sensing and novel observations from dedicated field c aigns. This contribution offers a comprehensive analysis of the hydrological dynamics of two neighbouring poorly gauged tropical basins the Kapuas basin (98 700 km2) in West Kalimantan and the Mahakam basin (77 100 km2) in East Kalimantan, Indonesia. Both basins are characterised by vast areas of inland lowlands. Hereby, we put specific emphasis on key hydrological variables and indicators such as discharge and flood extent. The hydroclimatological data described herein were obtained during fieldwork c aigns carried out in the Kapuas over the period 2013–2015 and in the Mahakam over the period 2008–2010. Additionally, we used the Tropical Rainfall Measuring Mission (TRMM) rainfall estimates over the period 1998–2015 to analyse the distribution of rainfall and the influence of El-Niño – Southern Oscillation. Flood occurrence maps were obtained from the analysis of the Phase Array type L-band Synthetic Aperture Radar (PALSAR) images from 2007 to 2010. Drought events were derived from time series of simulated groundwater recharge using time series of TRMM rainfall estimates, potential evapotranspiration estimates and the threshold level approach. The Kapuas and the Mahakam lake regions are vast reservoirs of water of about 1000 and 1500 km2 that can store as much as 3 and 6.5 billion m3 of water, respectively. These storage capacity values can be doubled considering the area of flooding under vegetation cover. Discharge time series show that backwater effects are highly influential in the wetland regions, which can be partly explained by inundation dynamics shown by flood occurrence maps obtained from PALSAR images. In contrast to their nature as wetlands, both lowland areas have frequent periods with low soil moisture conditions and low groundwater recharge. The Mahakam wetland area regularly exhibits low groundwater recharge, which may lead to prolonged drought events that can last up to 13 months. It appears that the Mahakam lowland is more vulnerable to hydrological drought, leading to more frequent fire occurrences than in the Kapuas basin.
A metaanalysis of the regularity of environmental spatialpatterns and a theory relating them to stochastic processes
Publisher: Copernicus GmbH
Date: 15-05-2023
DOI: 10.5194/EGUSPHERE-EGU23-5817
Abstract: Fascinating spatial patterns are found in many ecosystems. For ex le, patterns in Dryland ecosystems often consist of vegetation patches which alternate with bare soil. The patterns appear strikingly regular, when their formation is driven by scale-dependent feedbacks. Because of their regularity, such patterns are conceptually understood to be periodic. The formation of periodic patterns has been reproduced with idealized numerical models and the vulnerability of pattern forming ecosystems to environmental pressure has been preferentially studied with such models. However, natural patterns appear far from periodic. So does the distance between and the size of the patches vary systematically and the fringes of the patches are ragged. Previously, we revisited tests for periodicity and demonstrated that the large majority of regular patterns found in nature are not periodic. We also introduced a method to quantify the regularity of patterns, and found that natural patterns are of intermediate regularity, in-between uncorrelated noise and periodic functions, which can best be described by stochastic processes, where the irregularity is intrinsic to the pattern and not due to added noise. Here, we corroborate our previous results with a comprehensive metastudy, where we analyze natural and computer-generated patterns found in the leading literature. Furthermore, we extend our theory for the formation of stochastic patterns with arbitrary regularity to two dimensions. We find that our theory captures well the spectral properties of both isotropic, i.e. spotted, labyrinthic and gapped, as well as of anisotropic, i.e. banded patterns. Figure 1: a) Normalized spectral density averaged over the natural and model generated patterns found in the literature. The density of the natural patterns consists of a wide and low lobe, while the density of the model generated patterns consists of a narrow and high peak. b) Median regularity and interquartile range for the natural and model generated patterns. The modelled patterns are 3-5 times as regular as the natural patterns. Number of s les indicated next to the median.
Related Organisations
Brandenburgische Technische Universität Cottbus-Senftenberg
Location: Germany
Related Funding Activities
No related grants have been discovered for Karl Kästner.