A soil-landscape model for southern Mahurangi Forest, Northland

Exotic plantation forestry has a productive area of about 75 000 ha in Northland (L. Cannon, personal communication). Forestry is thus an important land use of both economic and environmental significance in Northland as well as elsewhere in New Zealand. Therefore, it is of considerable importance that forestlands be managed sustainably by employing approaches such as site-specific management. The establishment of site-specific forest management practices requires information regarding the distribution of key soil properties (Turvey and Poutsma, 1980). Quantitative modelling to predict key soil properties of sustainable forestry from observable landscape features may be a cost-effective approach to mapping forestlands. We are investigating the efficacy of such an approach within Mahurangi Forest, Northland

Mapping and explaining the productivity of Pinus radiata in New Zealand

Mapping Pinus radiata productivity for New Zealand not only provides useful information for forest owners, industry stakeholders and policy managers, but also enables current and future plantations to be visualised, quantified, and planned. Using an extensive set of permanent sample plots, split into fitting (n = 1,146) and validation (n = 618) datasets, models of P. radiata 300 Index (an index of volume mean annual increment) and Site Index (an index of height growth) were developed using a regression kriging technique. Spatial predictions were accurate and accounted for 61% and 70% of the variance for 300 Index and Site Index, respectively. Productivity predicted from these surfaces for the entire plantation estate averaged 27.4 m³ ha⁻¹ yr⁻¹ for the 300 Index and 30.4 m for Site Index. Surfaces showed wide regional variation in this productivity, which was attributable mainly to variation in air temperature and root-zone water storage from site to site

A soil-landscape model for Mahurangi Forest, Northland, New Zealand

Exotic plantation forestry is an important land use of both economic and environmental significance in Northland and elsewhere in New Zealand. It is therefore of considerable importance that forestlands be managed sustainably by employing approaches such as site-specific management. The establishment of site-specific forest management practices requires information regarding the distribution of key soil properties (Turvey and Poutsma, 1980). Quantitative modelling to predict key soil properties from landscape features may be an effective approach to mapping forestlands. A study investigating the efficacy of such an approach is being conducted within Mahurangi Forest, Northland, New Zealand. As a pilot to the study, a detailed qualitative soil-landscape model was developed in order to gain a greater understanding of the soil-landscape relationships and soil pattern of the area. The qualitative soil-landscape model developed in the pilot study is presented here

Mapping the productivity of radiata pine

Forest owners, investors and policy makers all want to know the spread and productivity of New Zealand’s current and future radiata plantation. David Palmer, a geo-spatial analyst at Scion, has combined advanced statistical techniques with mapping technology to predict radiata 300 Index and Site Index for any location in New Zealand. The 300 Index is an index of volume mean annual increment, and the Site Index is for height and growth. The map of Site Index and 300 Index was built using growth measurement data from trees in 1,146 radiata pine permanent sample plots, planted between 1975 and 2003. The data was combined with a number of climate, land use, terrain and environmental variables to predict forest productivity under a range of conditions

Soil and foliar phosphorus as indicators of sustainability for Pinus radiata plantation forestry in New Zealand

We investigated how multiple-crop forestry has influenced the magnitude and variability of soil and plant phosphorus (P) fertility and site disturbance. Kinleith Forest, on Mamaku Plateau, covers >100,000 ha and comprises mainly plantation Pinus radiata. Three study areas in the forest were chosen to represent natural state (native forest), first crop of P. radiata (24 years growth), and second crop of P. radiata (4 years growth of second crop). The adjacent areas have similar relief and climate, and the soils are all the same age, being predominantly Andic Haplohumods developed in 1770 calendar-year-old non-welded tephra (Taupo Ignimbrite, ca. 0.5–0.8 m in thickness) and overlying a buried paleosol on earlier tephric material. Soil properties were compared using a random geometric sampling scheme stratified in a 40-m grid. Soil samples (0–20 cm) were taken at 1.5, 4.5 and 13 m spatial intervals in random directions away from each primary node, providing 192 sample sites for each study area. Additionally at selected sites, samples of the current year's foliage from the upper crowns were collected, the thickness of Taupo Ignimbrite (i.e. depth to buried paleosol) was recorded by augering, and site disturbance was assessed using a new six-point scale based on change relative to a modal soil profile. Geostatistics and geographical information systems (GIS) were used to assess variability and effects of forest management on the measured properties. Soil Bray-2 P concentrations were below guidelines for satisfactory growth (12 mg kg⁻¹) at all sites, and no differences were recorded between the different management areas. However, the amount of within-site variability in Bray-2 P increased with the number of crops. Foliar P concentrations were only marginally deficient in both the first and second crops, indicating that P is currently not significantly limiting growth. The lack of difference in foliar P between first and second crops indicates no crop-to-crop decline in foliar P status and suggests that no site P fertility decline has occurred. The soils have an unusual ability to continue releasing P through successive sequential extractions in the Bray-2 P test, indicating a strong buffering capacity, and this may explain the apparent lack of deficiency even with Bray-2 P values of <12 mg kg⁻¹. The site disturbance index increased and the spatial distribution of P data became increasingly variable with crop rotation. GIS, inverse-distance weighting and kriging proved useful in illustrating the trends between crops. The spatial variability of results indicated that there was no obvious pattern to the variability and that more site-specific forest management in the region would be difficult. However, there was some evidence that less disturbance during harvesting may minimise variability of soil P supply

Comparison of spatial prediction techniques for developing Pinus radiata productivity surfaces across New Zealand

Spatial interpolation is frequently used to predict values across a landscape enabling the spatial variation and patterns of a property to be quantified. Inverse distance weighting (IDW), ordinary kriging (OK), regression kriging (RK), and partial least squares (PLS) regression are interpolation techniques typically used where the region of interest's spatial extent is relatively small and observations are numerous and regularly spaced. In the current era of data ‘mining’ and utilisation of sparse data, the above criteria are not always fully met, increasing model uncertainties. Furthermore, regression modelling and kriging techniques require good judgement, experience, and expertise by the practitioner compared with IDW with its more rudimentary approach. In this study we compared spatial predictions derived from IDW, PLS, RK, and OK for Pinus radiata volume mean annual increment (referred to as 300 Index) and mean top height at age twenty (referred to as Site Index) across New Zealand using cross-validation techniques. Validation statistics (RMSE, ME, and R2) show that RK, OK, and IDW provided predictions that were less biased and of greater accuracy than PLS predictions. Standard deviation of rank (SDR) and mean rank (MR) validation statistics showed similar results with OK the most consistent (SDR) predictor, whereas RK had the lowest mean rank (MR), closely followed by IDW. However, the mean performance rankings for validation observations classified according to their distance to the nearest model data point indicate that although PLS provided the poorest predictions at relatively close separation distances (<2 km), in the medium range ( 4–8 km) performance was of similar ranking to that of the other techniques, and at greater separation distances PLS outperformed the other techniques. Maps illustrating the spatial variation of P. radiata forest productivity are provided

Development of models to predict Pinus radiata productivity throughout New Zealand

Development of spatial surfaces describing variation in productivity across broad landscapes at a fine resolution would be of considerable use to forest managers as decision support tools to optimize productivity. In New Zealand, the two most widely used indices to quantify productivity of Pinus radiata D. Don are Site Index and 300 Index. Using an extensive national data set comprising a comprehensive set of national extent maps, multiple regression models and spatial surfaces of these indices for P. radiata were constructed. The final models accounted for 64% and 53%, respectively, of the variance in Site Index and 300 Index. For Site Index, variables included in the final model in order of importance were mean annual air temperature, fractional mean annual available root-zone water storage, mean annual windspeed, length and slope factor, categories describing Land Environments of New Zealand (LENZ), and major soil parent material. The variables included in the final model of 300 Index in order of importance included the degree of ground frost during autumn, fractional mean annual available root-zone water storage, categories describing LENZ, vegetation classification, foliar nitrogen, taxonomic soil order, and major soil parent material. These results highlight the utility of thematic spatial layers as driving variables in the development of productivity models