Comparing models for predicting species' potential distributions : a case study using correlative and mechanistic predictive modelling techniques
- Robertson, Mark P, Peter, Craig I, Villet, Martin H, Ripley, Bradford S
- Authors: Robertson, Mark P , Peter, Craig I , Villet, Martin H , Ripley, Bradford S
- Date: 2003
- Language: English
- Type: Article
- Identifier: vital:6539 , http://hdl.handle.net/10962/d1005980 , http://dx.doi.org/10.1016/S0304-3800(03)00028-0
- Description: Models used to predict species’ potential distributions have been described as either correlative or mechanistic. We attempted to determine whether correlative models could perform as well as mechanistic models for predicting species potential distributions, using a case study. We compared potential distribution predictions made for a coastal dune plant (Scaevola plumieri) along the coast of South Africa, using a mechanistic model based on summer water balance (SWB), and two correlative models (a profile and a group discrimination technique). The profile technique was based on principal components analysis (PCA) and the group-discrimination technique was based on multiple logistic regression (LR). Kappa (κ) statistics were used to objectively assess model performance and model agreement. Model performance was calculated by measuring the levels of agreement (using κ) between a set of testing localities (distribution records not used for model building) and each of the model predictions. Using published interpretive guidelines for the kappa statistic, model performance was “excellent” for the SWB model (κ=0.852), perfect for the LR model (κ=1.000), and “very good” for the PCA model (κ=0.721). Model agreement was calculated by measuring the level of agreement between the mechanistic model and the two correlative models. There was “good” model agreement between the SWB and PCA models (κ=0.679) and “very good” agreement between the SWB and LR models (κ=0.786). The results suggest that correlative models can perform as well as or better than simple mechanistic models. The predictions generated from these three modelling designs are likely to generate different insights into the potential distribution and biology of the target organism and may be appropriate in different situations. The choice of model is likely to be influenced by the aims of the study, the biology of the target organism, the level of knowledge the target organism’s biology, and data quality.
- Full Text:
- Authors: Robertson, Mark P , Peter, Craig I , Villet, Martin H , Ripley, Bradford S
- Date: 2003
- Language: English
- Type: Article
- Identifier: vital:6539 , http://hdl.handle.net/10962/d1005980 , http://dx.doi.org/10.1016/S0304-3800(03)00028-0
- Description: Models used to predict species’ potential distributions have been described as either correlative or mechanistic. We attempted to determine whether correlative models could perform as well as mechanistic models for predicting species potential distributions, using a case study. We compared potential distribution predictions made for a coastal dune plant (Scaevola plumieri) along the coast of South Africa, using a mechanistic model based on summer water balance (SWB), and two correlative models (a profile and a group discrimination technique). The profile technique was based on principal components analysis (PCA) and the group-discrimination technique was based on multiple logistic regression (LR). Kappa (κ) statistics were used to objectively assess model performance and model agreement. Model performance was calculated by measuring the levels of agreement (using κ) between a set of testing localities (distribution records not used for model building) and each of the model predictions. Using published interpretive guidelines for the kappa statistic, model performance was “excellent” for the SWB model (κ=0.852), perfect for the LR model (κ=1.000), and “very good” for the PCA model (κ=0.721). Model agreement was calculated by measuring the level of agreement between the mechanistic model and the two correlative models. There was “good” model agreement between the SWB and PCA models (κ=0.679) and “very good” agreement between the SWB and LR models (κ=0.786). The results suggest that correlative models can perform as well as or better than simple mechanistic models. The predictions generated from these three modelling designs are likely to generate different insights into the potential distribution and biology of the target organism and may be appropriate in different situations. The choice of model is likely to be influenced by the aims of the study, the biology of the target organism, the level of knowledge the target organism’s biology, and data quality.
- Full Text:
Environmental limits to the distribution of Scaevola plumieri along the South African coast
- Peter, Craig I, Ripley, Bradford S, Robertson, Mark P
- Authors: Peter, Craig I , Ripley, Bradford S , Robertson, Mark P
- Date: 2003
- Language: English
- Type: Article
- Identifier: vital:6872 , http://hdl.handle.net/10962/d1011617
- Description: Scaevola plumieri is an important pioneer on many tropical and subtropical sand dunes, forming a large perennial subterranean plant with only the tips of the branches emerging above accreting sand. In South Africa it is the dominant pioneer on sandy beaches along the east coast, less abundant on the south coast and absent from the southwest and west coasts. Transpiration rates (E) of S. plumieri are predictably related to atmospheric vapour pressure deficit under a wide range of conditions and can therefore be predicted from measurement of ambient temperature and relative humidity. Scaling measurements of E at the leaf level to the canopy level has been demonstrated previously. Using a geographic information system, digital maps of regional climatic variables were used to calculate digital maps of potential transpiration from mean monthly temperature and relative humidity values, effectively scaling canopy level transpiration rates to a regional level. Monthly potential transpiration was subtracted from the monthly median rainfall to produce a map of mean monthly water balance. Seasonal growth was correlated with seasonal water balance. Localities along the coast with water deficits in summer corresponded with the recorded absence of S. plumieri, which grows and reproduces most actively in the summer months. This suggests that reduced water availability during the summer growth period limits the distribution of S. plumieri along the southwest coast, where water deficits develop in summer. Temperature is also important in limiting the distribution of S. plumieri on the southwest coast of South Africa through its effects on the growth and phenology of the plant.
- Full Text:
- Authors: Peter, Craig I , Ripley, Bradford S , Robertson, Mark P
- Date: 2003
- Language: English
- Type: Article
- Identifier: vital:6872 , http://hdl.handle.net/10962/d1011617
- Description: Scaevola plumieri is an important pioneer on many tropical and subtropical sand dunes, forming a large perennial subterranean plant with only the tips of the branches emerging above accreting sand. In South Africa it is the dominant pioneer on sandy beaches along the east coast, less abundant on the south coast and absent from the southwest and west coasts. Transpiration rates (E) of S. plumieri are predictably related to atmospheric vapour pressure deficit under a wide range of conditions and can therefore be predicted from measurement of ambient temperature and relative humidity. Scaling measurements of E at the leaf level to the canopy level has been demonstrated previously. Using a geographic information system, digital maps of regional climatic variables were used to calculate digital maps of potential transpiration from mean monthly temperature and relative humidity values, effectively scaling canopy level transpiration rates to a regional level. Monthly potential transpiration was subtracted from the monthly median rainfall to produce a map of mean monthly water balance. Seasonal growth was correlated with seasonal water balance. Localities along the coast with water deficits in summer corresponded with the recorded absence of S. plumieri, which grows and reproduces most actively in the summer months. This suggests that reduced water availability during the summer growth period limits the distribution of S. plumieri along the southwest coast, where water deficits develop in summer. Temperature is also important in limiting the distribution of S. plumieri on the southwest coast of South Africa through its effects on the growth and phenology of the plant.
- Full Text:
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