Use policyThe full-text may be used and/or reproduced, and given to third parties in any format or medium, without prior permission or charge, for personal research or study, educational, or not-for-prot purposes provided that:• a full bibliographic reference is made to the original source • a link is made to the metadata record in DRO • the full-text is not changed in any way The full-text must not be sold in any format or medium without the formal permission of the copyright holders.Please consult the full DRO policy for further details. Abstract: Planted forests are increasingly recognised for the provision of habitats for species threatened with extinction. Despite this development, a limited number of empirical studies have been undertaken to estimate the economic value of this ecosystem service. New Zealand's planted forests provide habitat to at least 118 threatened species. These forests can be managed to increase the abundance of many of these species. We present findings from survey data obtained in a discrete choice experiment designed to estimate the non-market values for a proposed biodiversity enhancement programme in New Zealand's planted forests. We used a two-stage modelling process. First we estimated the individual specific willingness to pay values and then we explored their socioeconomic and spatial determinants. The first stage modeling process, which used a random parameters logit model with error components, suggested that willingness to pay was higher for increasing the abundance of native bird than for non-bird species. The second stage model used a least squares panel random-effects regression. Results from this method suggested that socioeconomic characteristics, such as attitudes toward the programme and distance from large planted forests, influenced willingness to pay for biodiversity enhancement.We would like to thank Reviewers 2 and 3 for their additional comments that helped 1 improved the quality of this manuscript. Our responses to their comments are in italics 2 below. 3 4Reviewers' comments: 5 6Reviewer #2: Based on the second revision I would now suggest the manuscript for 7 publication; I have just two minor points: 8 1) You may check whether all references you make are really essential; e.g., concerning 9 the experimental design you have in line 232 in total 7 references. Given the length of the 10 manuscript and as design criteria are not really your topic please consider to reduce the 11 references to those that are really essential for your work 12 13Thank you for this comment. References now reduced to 2. 14 152) Again, I would not insist on dropping the RPL model without error component ( In the set of keywords, we changed "random parameters logit with error components" to 49 "random parameters logit model" 50 51 2. Similarly, the manuscript could be easily shortened by just including Model C. There 52 is nothing to be learned from Model A and B when C is included. The authors want to 53 focus on spatial attributes (see title) so that the inclusion of models A and B ...

We employ an integrated spatial economic model to assess the net private and public benefits of converting marginal agricultural land into forest plantations (afforestation) in New Zealand. For numerous locations, we conduct policy analysis considering the magnitudes of net private and public benefits of land-use changes to determine whether a policy response is justified and, if so, to identify the appropriate policy instruments to encourage adoption of afforestation. Net private benefit is commonly negative, so much so, that in most cases no policy response is justified. However, in certain cases, net private benefits are slightly negative and public benefits are significantly positive justifying the use of positive incentives as the most appropriate policy instrument to encourage afforestation in New Zealand. The most commonly used policy instruments for afforestation in New Zealand, extension and awareness training, are found to be appropriate in only a minority of situations.

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Background: Two indices, the 300 Index and Site Index, are commonly used to quantify productivity of Pinus radiata D.Don within New Zealand. Although maps of these indices exist, availability of new data and modifications to underlying models makes a refit of these prediction surfaces desirable. Prediction errors of such surfaces have only been reported at a plot-level scale, but their application is invariably at a larger scale where prediction accuracy should be better. The objectives of this study were to: (i) develop updated predictive surfaces for the 300 Index and Site Index; and (ii) characterise the relationship between prediction error and spatial scale for both surfaces. Methods: Models were developed using a dataset of 4108 permanent sample plots from throughout New Zealand. Productivity indices were estimated from plot measurements and environmental variables extracted for each plot. Data were randomly split into fitting and validation datasets and surfaces developed from the fitting dataset for the 300 Index and Site Index using partial least squares regression, ordinary kriging and regression kriging. Prediction accuracy across a range of scales from 0.2 to 200 km was evaluated using the validation dataset. Results: Regression kriging was found to be the most accurate method for describing spatial variation in the 300 Index and Site Index across New Zealand. Examination of changes in prediction error with spatial scale demonstrated a gradual decline in error from the plot level with increasing scale. Conclusions: This study provides accurate maps of both the 300 Index and Site Index across New Zealand. Analysis of the effects of scale on prediction accuracy indicates that 95% confidence intervals of predictions for the 300 Index based on these maps averaged over an area of about 700 ha are half those of plot-level predictions and halve again at a scale of about 20,000 ha. For the Site Index, the improvement in precision with increasing scale is more gradual with 95% confidence intervals halving at a scale of about 20,000 ha and halving again at a scale of about 250,000 ha.

The study evaluates a proposed programme that would sustain and enhance the provision of ecosystem services in planted forests. We focused on the evaluation of the benefits and costs of the conservation of the brown kiwi (an iconic yet threatened New Zealand bird species) that inhabits planted forests. Yao et al. (2014) found that a sample of 209 New Zealand (NZ) households would, on average, financially support a programme for conserving the brown kiwi in NZ planted forests. We extend that study using a proof of concept that integrates economic, ecological and spatial approaches. We undertake this in five steps: 1) supplementing a previous choice experiment survey by interviewing more than 900 additional georeferenced households; 2) estimating household-specific means of marginal willingness-to-pay (WTP) values; 3) using spatial econometrics to explore WTP determinants; 4) identifying 12 ecologically and economically feasible ecosystem-service sites (ranging from 5,000 to 11,500 hectares) and calculate the average annual costs of a conservation programme at each site; and finally 5) aggregating the public benefits of biodiversity at the regional and national levels and calculate the benefit cost ratio. We found that the value of the proposed biodiversity conservation initiative at the national level can be more than 100 times higher than the overall cost of the programme. To prioritise intervention of this initiative, we also identify the New Zealand region with planted forest sites that would produce the highest net economic benefit from the enhanced provision of ecosystem services.

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Surfaces that describe spatial variation in optimal stand density following final thining (Sopt) are likely to be of considerable use to forest managers. Using a comprehensive series of growth model simulations, the aim of this research was to (i) develop a model of Sopt that maximises volume of large-diameter, small-branched sawlogs (S27) for unpruned New Zealand radiata pine (Pinus radiata D. Don) stands, (ii) use this model to examine how site productivity and tree morphology influence Sopt, and (iii) generate a map of Sopt for New Zealand. A model predicting Sopt from clearfell age and two productivity indices, Site Index (SI) and 300 Index (I300), was found to predict optimal stand density with a high degree of accuracy. Optimal stand density was found to increase with I300 and clearfell age but decrease with SI. Within New Zealand plantations, the mean predicted Sopt for clearfell age 28 years was 614 stems·ha−1. The proportion of plantations predicted to have Sopt greater than 400, 500, and 600 stems·ha−1 was 0.99, 0.88, and 0.61, respectively. The predicted Sopt was found to exceed the actual mean final crop stand density in stands managed under unpruned sawlog regimes of ca. 500 stems·ha−1 within most plantation areas in New Zealand. This disparity highlights the potential of this approach for increasing crop value in New Zealand P. radiata plantations.