CABALA: a linked carbon, water and nitrogen model of forest growth for silvicultural decision support

Battaglia, Michael; Sands, Peter; White, D. A.; Mummery, DC

doi:10.1016/j.foreco.2004.01.033

Cited by 190 publications

(98 citation statements)

References 74 publications

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“…Climate information has been used extensively to define and map vegetation types and ecological zones and for modelling habitat distributions of vertebrates and invertebrates (Daubenmire 1978;Pojar et al 1987;Thackway and Cresswell 1992), for species and provenance selection (Booth et al 1988;Booth 1990) and seed zone identification (Johnson et al 2004), for forest fire weather risk assessment and fire behaviour modelling (Carvalho et al 2008), for modelling forest productivity (Battaglia et al 2004) and analysing the dynamics of a range of ecological processes (Anderson 1991;Breymeyer and Melillo 1991). Predicting species responses to future climate change presents a different set of challenges, involving consideration of predictions of future climate that are often outside the historical range of variability of many species.…”

Section: Predicting Species and Ecosystem Responses To Future Climatementioning

confidence: 99%

Climate change impacts and adaptation in forest management: a review

Keenan

2015

Annals of Forest Science

464

303

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Abstract& Key message Adaptation of forest management to climate change requires an understanding of the effects of climate on forests, industries and communities; prediction of how these effects might change over time; and incorporation of this knowledge into management decisions. This requires multiple forms of knowledge and new approaches to forest management decisions. Partnerships that integrate researchers from multiple disciplines with forest managers and local actors can build a shared understanding of future challenges and facilitate improved decision making in the face of climate change.

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Section: Predicting Species and Ecosystem Responses To Future Climatementioning

confidence: 99%

Climate change impacts and adaptation in forest management: a review

Keenan

2015

Annals of Forest Science

464

303

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“…Well-known forest growth models are often based on very large (e.g., Buckman et al, 2006;Vanclay, 1994a) or sophisticated databases (e.g., Landsberg et al, 2003;Battaglia et al, 2004), but there remains strong demand for forest growth forecasts in situations where efforts to calibrate and initialize models are hampered by a lack of data. This paper examines some robust principles that may underpin simple models based on minimal data for forest plantation forest forecasting.…”

Section: Introductionmentioning

confidence: 99%

Robust relationships for simple plantation growth models based on sparse data

Vanclay

2010

Forest Ecology and Management

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“…A potentially useful, yet unexplored application of the SNAP model is its use in plant production models that rely on the prediction of NNM and nitrification (Keating et al, 2003;Jones et al, 2003;Battaglia et al, 2004;van Noordwijk et al, 2011). Such models already use daily climate data, which would additionally require aerobic incubation and a few other inputs.…”

Section: Discussionmentioning

confidence: 99%

Appraisal of the Snap Model for Predicting Nitrogen Mineralization in Tropical Soils Under Eucalyptus

Smethurst

Gonçalves

Pulito

et al. 2015

Rev. Bras. Ciênc. Solo

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the soil Nitrogen Availability predictor (sNAp) model predicts daily and annual rates of net N mineralization (NNm) based on daily weather measurements, daily predictions of soil water and soil temperature, and on temperature and moisture modifiers obtained during aerobic incubation (basal rate). the model was based on in situ measurements of NNm in Australian soils under temperate climate. the purpose of this study was to assess this model for use in tropical soils under eucalyptus plantations in São Paulo State, Brazil. Based on field incubations for one month in three, NNm rates were measured at 11 sites (0-20 cm layer) for 21 months. the basal rate was determined in in situ incubations during moist and warm periods (January to march). Annual rates of 150-350 kg ha -1 yr -1 NNm predicted by the sNAp model were reasonably accurate (r 2 = 0.84). in other periods, at lower moisture and temperature, NNm rates were overestimated. therefore, if used carefully, the model can provide adequate predictions of annual NNm and may be useful in practical applications. for NNm predictions for shorter periods than a year or under suboptimal incubation conditions, the temperature and moisture modifiers need to be recalibrated for tropical conditions.

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CABALA: a linked carbon, water and nitrogen model of forest growth for silvicultural decision support

Cited by 190 publications

References 74 publications

Climate change impacts and adaptation in forest management: a review

Climate change impacts and adaptation in forest management: a review

Robust relationships for simple plantation growth models based on sparse data

Appraisal of the Snap Model for Predicting Nitrogen Mineralization in Tropical Soils Under Eucalyptus

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