Spatial modeling of rangeland potential vegetation environments

Jensen, M. E.; Dibenedetto, J. P.; Barber, J. A.

doi:10.2458/azu_jrm_v54i5_jensen

Cited by 4 publications

(4 citation statements)

References 7 publications

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“…In rangelands, potential natural vegetation is mapped via land unit classifications such as habitat types (Jensen et al 2001), range units and range sites (Kunst et al 2006), and ecological sites (Bestelmeyer et al 2003). More recently, attention has focused on the delineation of the current states of a set of land units based on its STM (Steele et al 2012).…”

Section: Mapping State-and-transition Model Informationmentioning

confidence: 99%

State and Transition Models: Theory, Applications, and Challenges

Bestelmeyer

Ash

Brown

et al. 2017

Springer Series on Environmental Management

105

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State and transition models (STMs) are used to organize and communicate information regarding ecosystem change, especially the implications for management. The fundamental premise that rangelands can exhibit multiple states is now widely accepted and has deeply pervaded management thinking, even in the absence of formal STM development. The current application of STMs for management, however, has been limited by both the science and the ability of institutions to develop and use STMs. In this chapter, we provide a comprehensive and contemporary overview of STM concepts and applications at a global level. We first review the ecological concepts underlying STMs with the goal of bridging STMs to recent theoretical developments in ecology. We then provide a synthesis of the history of

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Section: Mapping State-and-transition Model Informationmentioning

confidence: 99%

State and Transition Models: Theory, Applications, and Challenges

Bestelmeyer

Ash

Brown

et al. 2017

Springer Series on Environmental Management

105

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“…De acordo com JENSEN et al (2001), o uso eficiente de estudo da vegetação potencial em escalas regional e sub-regional foi limitado até o início dos anos de 1990 devido à falta de dados, tornando difícil a localização precisa e o arranjo espacial do ambiente de vegetação potencial. Entretanto, os avanços recentes em sensoriamento remoto, sistema de informação geográfica, modelos terrestres e interpolação climática facilitaram o mapeamento da vegetação potencial, como foi mostrado por JENSEN et al (2001). SUD et al (1996) descrevem que a vantagem dos Modelos de Circulação Geral (MCG) é que podem ser usados para fazer avaliação com base nos efeitos climáticos de possíveis alterações antropogênicas da biosfera.…”

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Modelo de vegetação potencial para a Região Nordeste decorrente da precipitação pluvial

Nascimento

Brito

2007

Bragantia

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O presente trabalho aplica o modelo de Rey para calcular a vegetação potencial da Região Nordeste do Brasil e, assim, verificar se esse modelo identifica os principais tipos de vegetação dessa região. O método utilizado para calcular a taxa de Evapotanspiração (ET) é embasado na equação de Penman-Monteith. O modelo também inclui parâmetros fixados e as variáveis altura da vegetação e índice de área foliar (IAF). De modo geral, o modelo conseguiu reproduzir bem os biomas da região Nordeste do Brasil, principalmente a Caatinga, o Cerrado e a Mata Atlântica.

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“…Topography has been used previously as an indicator of plant community composition (Bork et al 1997;Brown 1994;Jensen et al 2001;Vivian-Smith 1997). Even minor changes in topography are associated with changes in species composition for Argentinean grasslands (Perelman et al 2001).…”

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confidence: 99%

Predicting the likelihood of yellow starthistle (Centaurea solstitialis) occurrence using landscape characteristics

Shafii¹,

Price

Prather

et al. 2003

Weed Science

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Yellow starthistle is an invasive plant species common in the semiarid climate of central Idaho and other western states. Early detection of yellow starthistle and estimation of its infestation potential in semiarid grasslands have important scientific and managerial implications. Weed detection and delineation of infestations are often carried out by using ground survey techniques. However, such methods can be inefficient and expensive in detecting sparse infestations. The distribution of yellow starthistle over a large region may be affected by various landscape variables such as elevation, slope, and aspect. These exogenous variables may be used to develop prediction models to estimate the potential for yellow starthistle invasion into new areas. A nonlinear prediction model has been developed using a polar coordinate transformation of landscape characteristics to predict the likelihood of yellow starthistle occurrence in north-central Idaho. The study region included the lower Snake River and parts of the Salmon and Clearwater basins encompassing various land-use (range, pasture, and forest) categories. The model provided accurate estimates of yellow starthistle incidence within each specified land-use category and performed well in subsequent statistical validations. This prediction model can assist land managers in focusing their efforts by identifying specific areas for survey.

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Spatial modeling of rangeland potential vegetation environments

Cited by 4 publications

References 7 publications

State and Transition Models: Theory, Applications, and Challenges

State and Transition Models: Theory, Applications, and Challenges

Modelo de vegetação potencial para a Região Nordeste decorrente da precipitação pluvial

Predicting the likelihood of yellow starthistle (Centaurea solstitialis) occurrence using landscape characteristics

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