A macrophyte submodel for aquatic ecosystems

Collins, Carol D.; Wlosinski, Joseph H.

doi:10.1016/0304-3770(89)90037-5

Cited by 37 publications

(15 citation statements)

References 47 publications

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“…On the other hand, biomass models, including growth simulation and holistic empirical ones, are developed for quantitative purpose. Simulation models are advantageous to predict daily growth or seasonal trends of macrophyte biomass (Best et al, 2001;Collins and Wlosinski, 1989;Scheffer et al, 1993;Van Nes et al, 2002, 2003, but their generation requires a large number of detailed physiological and daily environmental data. Comparatively, holistic empirical models enable us to pay less attention to growing details and use fewer independent variables.…”

Section: Background and Purposementioning

confidence: 99%

Empirical modelling of submersed macrophytes in Yangtze lakes

Wang

Liang

et al. 2005

Ecological Modelling

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Section: Background and Purposementioning

confidence: 99%

Empirical modelling of submersed macrophytes in Yangtze lakes

Wang

Liang

et al. 2005

Ecological Modelling

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“…Each ramet has an exact x and y coordinate and Table 1 An overview of the main differences between non-clonal macrophyte models (e.g. Collins and Wlosinski, 1989;Scheffer et al, 1993;Hootsmans, 1994;Chen and Coughenour, 1996;Muhammetoglu and Soyupak, 2000;Van Nes et al, 2003) is associated with one grid cell. A clone can expand over more than one grid cell.…”

Section: Overviewmentioning

confidence: 99%

“…These models can be (a) non-spatial (Collins and Wlosinski, 1989;Scheffer et al, 1993;van Dijk and Janse, 1993;Davis and McDonnell, 1997;Hootsmans, 1999;Asaeda and Karunaratne, 2000;Calado and Duarte, 2000;Best et al, 2001) or (b) spatial (Wortmann et al, 1997;Van Nes et al, 2003).…”

Section: Comparison With Other Modelsmentioning

confidence: 99%

“…Although there are many detailed dynamical models of macrophytes (Collins and Wlosinski, 1989;Scheffer et al, 1993;Hootsmans, 1994;Chen and Coughenour, 1996;Muhammetoglu and Soyupak, 2000;Van Nes et al, 2003), the clonal growth of submerged macrophytes has, to our knowledge, never been modelled in detail, including architectural, spatial, environmental, temporal and demographic components. For terrestrial plants, only a few of such detailed models exists (Herben and Suzuki, 2002;Oborny and Kun, 2002).…”

Section: Introductionmentioning

confidence: 99%

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Modelling the clonal growth of the rhizomatous macrophyte Potamogeton perfoliatus

Wolfer

Nes

Straile

2006

Ecological Modelling

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Macrophytes play a crucial role in the functioning of lake ecosystems. Until now most macrophyte models neglected the fact that the majority of macrophyte species expand clonally during the growing season. Inclusion of a detailed description of clonal growth in models can facilitate our understanding of space occupation and patch expansion and predict future macrophyte development. "CLOMO" is an individual-based model which includes a detailed, spatially explicit description of rhizome formation and clone expansion as well as a realistic description of photosynthesis including light limitation and temperature. The model also accounts for transfers of energy or resources between different parts of the clone ("clonal integration").Although the clonal growth of macrophytes is complex and poorly known, the first model results for the macrophyte species Potamogeton perfoliatus were promising and compared well with the field data. The model can produce growth networks very similar to those found in the field. A Monte Carlo sensitivity analysis showed systematically which parameters have the largest effect on the architecture and expansion of the clones.The application of the model provided new insights into growth dynamics and patch development: (1) the model showed that a lack of branching will lead to the extinction of the clone after a certain number of years. This is due to the fact that the reproductive organs (turions) are formed at the end of a branch and even a small turion mortality will cause a reduction in surviving plant numbers; (2) the growth of rhizome axes relative to those in the previous year determines the patch density and patch expansion rate. Reversing rhizomes lead to compact patch growth whereas continuing rhizomes lead to loose aggregates.

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“…Although the number of simulation models for growth of monotypic, submersed macrophyte communities is increasing (e.g., Titus et al 1975;Best 1981;Collins and Wlosinski 1985;Best and Jacobs 1990;Hootsmans 1991;Scheffer et al 1993;Best and Boyd 1996, 1999, 2001, it is still relatively low compared to that for terrestrial vegetation. The current model has been developed because none of the existing models was suitable to simulate the behavior of a monotypic sago pondweed community under various environmental and climatological conditions over a period ranging from one season to several years.…”

Section: Introductionmentioning

confidence: 99%

A Simulation Model for Growth of the Submersed Aquatic Macrophyte Sago Pondweed (Potamogeton pectinatus L.)

Best¹,

Boyd²

2003

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A simulation model for biomass dynamics of the submersed macrophyte Potamogeton pectinatus L. is presented. The model (POTAM) is based on carbon flow through the vegetation in meter-squared (m^) water columns. It includes descriptions of several factors that affect biomass dynamics, such as site characteristic changes in climate, temperature, water transparency, water level, pH, and oxygen effects on CO2 assimilation rate at light saturation, wintering strategies, mechanical control (removal of shoot biomass), and grazing. The characteristics of community and site can be easily modified by the user.POTAM incorporates insight into the processes affecting the dynamics of a sago pondweed community in relatively shallow, hard water (0.1-to 6-m depth; dissolved inorganic carbon concentration > 0.8 mmol and pH > 6), under ample supply of nitrogen and phosphorus in a pest-, disease-, and competitor-free environment under the prevailing weather conditions. It has been calibrated on data pertaining to a sago pondweed community in the Western Canal near Zandvoort, The Netherlands. At this site, growth starts from the subterranean tubers alone. Plant biomass usually peaks once a year, in July, and intensive downward transport of soluble carbohydrates occurs after anthesis, used for the formation of tubers that grow into the sediment.POTAM simulated the dynamics of plant and tuber biomass and tuber numbers in the Western Canal near Zandvoort, The Netherlands, well over a period of 1 to 5 years. Starting from measured instead of nominal tuber size increased the similarity between simulated and measured plant data. The importance of several plant speciescharacteristic properties was explored, namely, of leaf surface:dry weight ratio, tuber bank density, anchorage depth, and presence/absence of wintering shoots.The model has been used to calculate plant and tuber biomass and tuber numbers for other sites as well. In Lake Veluwe, The Netherlands, a site with a temperate climate, simulated plant biomass and newly produced tuber densities were similar to measured ones in two consecutive years, but timing in the simulated plants was delayed the second year. In the Byrnes Canal, California, with a far warmer temperate climate, simulated plant biomass and tuber bank density were similar to measured values when a lower self-shading coefficient than the nominal one and the same tuber size/tuber number per plant as measured were used. However, plant biomass and tuber bank density were lower with the nominal self-shading coefficient. In the tropical Lake Ramgarh, India, a simulated peak plant biomass similar to measured was found using the same lower self-shading coefficient as run for the California site, and almost no tubers were formed. Verification of simulated with measured tuber numbers was not possible, since tubers had not been measured.Several case studies are presented in which POTAM generated insight useful for management aimed at conserving or controlling sago pondweed populations. The model was used to calculate t...

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A macrophyte submodel for aquatic ecosystems

Cited by 37 publications

References 47 publications

Empirical modelling of submersed macrophytes in Yangtze lakes

Empirical modelling of submersed macrophytes in Yangtze lakes

Modelling the clonal growth of the rhizomatous macrophyte Potamogeton perfoliatus

A Simulation Model for Growth of the Submersed Aquatic Macrophyte Sago Pondweed (Potamogeton pectinatus L.)

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