Species-specific basic stem-wood densities for twelve indigenous forest and shrubland species of known age, New Zealand Michael Marden1,*, Suzanne Lambie2 and Larry Burrows3 1 31 Haronga Road, Gisborne 4010, New Zealand 2 Manaaki Whenua – Landcare Research, Private Bag 3127, Hamilton 3240, New Zealand 3 Manaaki Whenua – Landcare Research, PO Box 69041, Lincoln 7640, New Zealand *Corresponding author: mardenm@landcareresearch.co.nz (Received for publication 19 July 2019; accepted in revised form 26 January 2021) Abstract Background: Tree carbon estimates for New Zealand indigenous tree and shrub species are largely based on mean basic stem-wood densities derived from a limited number of trees, often of unspecified age and from a limited number of sites throughout New Zealand. Yet stem-wood density values feed directly into New Zealand’s international and national greenhouse gas accounting. We augment existing published basic stem-wood density data with new age- specific values for 12 indigenous forest and shrubland species, including rarely obtained values for trees <6-years old, across 21 widely-distributed sites between latitudes 35° and 46° S, and explore relationships commonly used to estimate carbon stocks. Methods: The volume of 478 whole stem-wood discs collected at breast height (BH) was determined by water displacement, oven dried, and weighed. Regression analyses were used to determine possible relationships between basic stem-wood density, and tree height, root collar diameter (RCD), and diameter at breast height (DBH). Unbalanced ANOVA was used to determine inter-species differences in basic stem-wood density in 5-yearly age groups (i.e. 0–5 years, 6–10 years etc.) (P<0.05). As specific taxa of Kunzea ericoides (Myrtaceae) has only been identified at some study sites we combine the data from each site, and use the term Kunzea spp. We compare our age- and species-specific results with existing published data where age is specified versus non-age-specific values. Results: Kunzea spp. and Leptospermum scoparium exhibited positive correlations between basic stem-wood density and tree height, RCD, and DBH. No relationships were established for Melicytus ramiflorus, Coprosma grandiflora, Weinmannia racemosa ≥6-years old, or for Podocarpus totara, Agathis australis, Vitex lucens, and Alectryon excelsus <6-years old. Dacrydium cupressinum and Prumnopitys ferruginea <6-years old exhibited a significant positive relationship with DBH only, while for Dacrycarpus dacrydioides, each correlation was negative. Irrespective of age, basic stem-wood density is not different between the hardwood species L. scoparium and Kunzea spp. but is significantly greater (P=0.001) than that of the remaining, and predominantly softwood species of equivalent age. For Kunzea spp., L. scoparium, Coprosma grandiflora, Weinmannia racemosa, and Melicytus ramiflorus ≥6-years old there was no evidence that basic stem-wood density increased with tree age, and values were within the range of published and unpublished data. For naturally reverting stands of Kunzea spp. located between latitudes 35° to 46° S, basic stem-wood density values tended to increase with decreased elevation and increased temperature. Conclusions: Increasing basic wood density values in Kunzea spp. with decreased elevation and increased temperature suggest that where local data are available its use would improve the accuracy of biomass estimates both locally and nationally. Furthermore, refining biomass estimates for existing communities of mixed softwood species, stands of regenerating shrubland, and new plantings of indigenous species will require additional basic stem-wood density values for scaling from stem wood volume to total stand biomass. New Zealand Journal of Forestry Science Marden et al. New Zealand Journal of Forestry Science (2021) 51:1 https://doi.org/10.33494/nzjfs512021x121x E-ISSN: 1179-5395 published on-line: 15/02/2021 © The Author(s). 2021 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. Research Article Open Access Keywords: basic stem-wood density, allometric relations, 12 indigenous forest and shrubland species, New Zealand. http://creativecommons.org/licenses/by/4.0/), Marden et al. New Zealand Journal of Forestry Science (2021) 51:1 Page 2 Introduction The variability in basic stem-wood density and age are critical factors influencing estimates of wood biomass and carbon storage capability (Chave et al. 2004, Dale 2013). Stem-wood density values feed directly into New Zealand’s international greenhouse gas accounting of forest carbon stocks, and for internal schemes such as the Emissions Trading Scheme (ETS) (Ministry for Primary Industries 2017), and the 1 Billion Trees Programme (1BT) (Ministry for Primary Industries 2018). Previously, New Zealand studies have estimated the biomass of indigenous forest stands for tree carbon stocks and sequestration using diameters and height measurements of individual trees in forest inventory plots (Carswell et al. 2012, Scott et al. 2000, Trotter et al. 2005, Beets et al. 2014, Schwendenmann & Mitchell 2014, Dale 2013, Holdaway et al. 2014). When basic wood density values are available for only a limited number of species and locations, wood volume is converted to carbon stocks using generic (as opposed to species- specific) functions based on the basic density of stem- wood (oven-dry mass/ ‘green’ volume). Where species- specific and/or regional basic stem-wood density values are unavailable, congeneric values are used instead, or in their absence, the mean of all published values e.g. Beets et al. (2012 and unpublished data1). While most early studies in New Zealand collected basic stem-wood density data from sites of well- established indigenous shrubs and trees, age-specific and species-specific stem-wood density data for the early growth period of many species remain elusive. The absence of taxon-specific stem-wood density and age-class distribution data of a wide variety of species over a range of geographic sites introduces uncertainty in the accuracy of New Zealand’s national carbon budget calculations (Scott et al. 2000, Chave et al. 2004, Holdaway 2014). The use of taxon-specific stem-wood density to scale tree volume, as yield or growth, to stem biomass, and from stem biomass to total biomass will improve the accuracy of species-specific allometric equations for estimating tree carbon storage, and avoid potential bias to national carbon budgets. Furthermore, basic stem-wood density values for a few widespread indigenous species (Entrican et al. 1951, Hall et al. unpublished data2), and for specific species with a more restricted geographic range (Wardle 1991), can vary depending on geographic location, though no relationships have been verified with respect to climate or site factors (Hall et al. unpublished data2). Clifton (1990) suggests that basic stem-wood density varies according to the age of the tree, the location of the wood within a tree (outer-wood/inner-wood, base or top of a tree), and while densities have been determined for some of New Zealand’s historically important merchantable wood species (Hinds & Reid 1957, Beets et al. 2012), the age of the trees and variations in basic stem-wood density were not determined, the sample size was generally small, the methods uncertain, and the location vague. Stand basic stem-wood densities will also change with time, influenced by climatic variability and site-specific physical factors, including soil type, slope, aspect, elevation and rainfall regime, all of which can affect growth rates, plant survival, and carbon sequestration rates. Furthermore, as the area of indigenous species plantings and their diversity increases with age, age-specific and species- specific stem-wood density data, will be relevant for Afforestation/Reforestation reporting, for updating the national carbon inventory system (Land Use and Carbon Accounting System – LUCAS), and policy, to reduce net greenhouse gas emissions as required under the Kyoto Protocol (Ministry of the Environment 2010), and for comparison with pre-calculated forest carbon stocks (includes stem, bark, branch, leaves, litter, woody debris, stumps and roots expressed in units of tonnes of CO2 ha-1), by age, for given forest types in the Emissions Trading Scheme (Ministry for Primary Industries 2017). We augment existing published basic stem-wood density data with new age-specific values for 12 of New Zealand’s indigenous forest and shrubland species from 21 widely distributed sites located between latitudes 35° to 46° S. We explore relationships between basic stem-wood density and tree parameters commonly used to estimate stem carbon stocks, and applicable to future efforts to reduce the uncertainty of carbon stock estimates for forest and shrubland communities where basic stem-wood density values for different age classes of many species is currently missing. Methods Study sites Basic wood density data was collected from 14 sites located in the North Island and from 7 sites in the South Island of New Zealand with a latitudinal range between 35° and 46° S (Fig. 1). Details of species, elevation, and substrate characteristics are summarised in Table 1, and presented in more detail in Appendix Table A1. Species nomenclature Since this study began, there has been a taxonomic revision of the New Zealand Kunzea ericoides (Myrtaceae) complex in New Zealand (de Lange 2014). Ten Kunzea species endemic to New Zealand are now recognised, seven of which are new. Where we have some confidence in the identification of new taxa these are presented in Table 1 and Appendix Table A1. As specific taxa have not been identified for all sites we have not attempted to analyse for possible inter-specific variations in basic stem-wood density for this genus but 1 Beets, P.N., Oliver, G.R, Kimberley., M.O, Pearce, S.H. (2008). Allometric functions for estimating above ground carbon in native forest trees, shrubs and ferns. Scion Report 12679 prepared for the Ministry for the Environment 63 p. 2 Hall, G., Wiser, S., Allen, R., Moore, T., Beets, P., Goulding, C. (1998). Estimate of the carbon stored in New Zealand’s indigenous forest and scrub vegetation for 1990. Landcare Research Contract JNT9798/147 Prepared for Ministry for the Environment, Wellington, New Zealand. 36 p. instead we combine data for all sites where present and use the generic term Kunzea spp. Wood sampling and density There are many methods of sampling wood and determining wood density (Chave 2005, Williamson & Wiemann 2010). In this study, wood density is defined as the ratio of the oven-dry mass of a stem-wood disc sampled at a standard height divided by the mass of water displaced by its green volume to give wood specific gravity (WSG). WSG is described as basic wood density or stem-wood density throughout the text. Discs cut from the stem account for the change in density from pith to bark (Williamson & Wiemann 2010, Beets et al. 2012). Basic stem density measurements of discs were sourced from trees located in areas of naturally regenerating Kunzea spp. (sites 2–7, 9, 12– 21), regenerating Leptospermum scoparium (sites 1, 2, 9, 14, 16, and 21), a lowland shrub community (site 11), a species growth trial of indigenous softwood and hardwood species (site 8), and from an area of low-density plantings of L. scoparium (site 10). As the purpose of the research undertaken at each site differed, 256 of the basic stem-wood density measurements were of discs with the bark intact (Cornelissen et al. 2003) (e.g. sites 2, 4-11 & 21) and 222 measurements were of discs with the bark removed (e.g. sites 1, 3, 12- 20). All discs were sampled at breast height (BH) (1.4 m above ground-level). The fresh volume of each wood disc was determined by water displacement, then oven dried at 105°C (Cornelissen et al. 2003) and weighed. For multiple-stemmed trees, a disc was cut from each stem, and the density averaged for the tree. Tree age in naturally regenerating stands was based on ring counts of the single oldest stem. The age of the species established in the plant growth trial (site 8) was based on the known date that seedlings were ‘pricked-out’ into seed trays in the nursery. For the site established in L. scoparium for honey production (site 10), the year in which 1-year-old, nursery-raised seedlings were planted was known. For Melicytus ramiflorus and Coprosma grandiflora (site 11), discs were collected in the field at BH and transported in a sealed container to avoid moisture loss. In the laboratory, discs were soaked before the volume was determined by water displacement. Discs were dried at 80°C until dry and weighed (Cornelissen et al. 2003). Tree height was based on the tallest single stem. Tree age was based on ring counts of a disc cut from a representative stem of the tree. For Kunzea spp. and L. scoparium collected from sites 2, 9, and 21, discs were collected at BH and frozen at –20°C. The discs were thawed at room temperature and soaked in water for 2 days before their volume was assessed. As L. scoparium and Kunzea spp. tend to split during drying making ring counting and measuring difficult, the discs were partially dried at 35°C, the rings counted, and then dried at 80°C and weighed. For Kunzea spp., and L. scoparium, tree parameters were predominantly measured in regenerating shrubland >6-years old. Other regenerating shrubland species including Melicytus ramiflorus, Coprosma grandiflora, and Weinmannia racemosa include measurements for a wide range of ages both < and >6-years old while regressions for plot-based Alectron excelsus, Podocarpus totara, Agathis australis, Dacrydium cupressinum, Prumnopitus ferruginea, Dacrycarpus dacrydioides and Vitex lucens include only data for trees <6-years old. Statistical analyses Linear regression analysis best fitted the data and was used within each tree species to determine the possible relationship between basic stem-wood density and tree height, root collar diameter (RCD), diameter at breast height (DBH), and tree age. Unbalanced ANOVA with least significant differences (LSD) was used to determine differences in basic stem- wood density between species and for Kunzea spp. to assess if densities differed between 17 sites located throughout New Zealand. Density values were grouped into 5-yearly age classes (e.g. 0–5-years, 6–10 years etc.). Only data sets within a species, and within an age class with three or more replicates (irrespective of the geographical position) were used in the analysis. The average basic stem-wood densities for younger (<6-years old) and older (≥6-years old) trees are compared with published values. For the Marden et al. New Zealand Journal of Forestry Science (2021) 51:1 Page 3 FIGURE 1: Location of 21 New Zealand indigenous forest, shrubland, and experimental trial sites where discs were collected for analysis of basic stem-wood density. Marden et al. New Zealand Journal of Forestry Science (2021) 51:1 Page 4 FIGURE 2: TA B LE 1 : Lo ca ti on s, tr ee s pe ci es p re se nt , e le va ti on a bo ve s ea le ve l ( as l) , a nd s ub st ra te c ha ra ct er is ti cs fo r 21 s tu dy s it es s am pl ed fo r ba si c w oo d de ns it y. M ap c o- or di na te s ar e N ew Z ea la nd M ap G ri d (N ZM G ) Si te n um be r an d na m e G ri d re fe re nc e Sp ec ie s El ev at io n as l ( m ) Su bs tr at e 1: T au to ro 17 3° 5 0´ 1 3 15 E , 3 5° 2 8´ 5 2 00 S Le pt os pe rm um s co pa ri um 10 0– 14 0 gr ey w ac ke a rg ill it es a nd s an ds to ne s 2: W ai ta ke re R an ge 17 4° 3 5´ 1 4 42 E , 3 7° 0 0´ 1 0 17 S Ku nz ea s pp . a nd L . s co pa ri um 40 vo lc an ic a nd es it ic la va , c on gl om er at es , a nd b re cc ia 3: N ik au V al le y 17 6° 5 8´ 2 3 85 E , 3 8° 0 1´ 2 5 27 S Ku nz ea r ob us ta 40 –1 00 un di ffe re nt ia te d gr ey w ac ke 4- 6: T ol ag a B ay 17 8˚ 1 2΄ 1 9 29 E , 3 8˚ 2 0΄ 42 5 8 S Ku nz ea r ob us ta 64 ca lc ar eo us s an dy s ilt st on es w it h ba nd ed s an ds to ne s 7: W ai m at a Va lle y 17 8° 0 3΄ 1 3 66 E , 3 8˚ 2 8΄ 3 3 84 S Ku nz ea r ob us ta 20 7 ca lc ar eo us s an dy s ilt st on es w it h ba nd ed s an ds to ne s 8: G is bo rn e 17 8° 0 0´ 1 6 02 E , 3 8° 3 8´ 4 4 82 S Ag at hi s au st ra lis , P ru m no pi ty s fe rr ug in ea , P od oc ar pu s to ta ra , D ac ry ca rp us d ac ry di oi de s, D ac ry di um cu pr es si nu m , A le ct ry on e xc el su s, an d Vi te x lu ce ns . 5 al lu vi al g ra ve ls a nd s ilt . 9: T ur an gi 17 5° 4 7´ 1 1 53 E , 3 9° 0 9´ 1 9 20 S L. s co pa ri um a nd K un ze a sp p. 80 0 rh yo lit ic a nd a nd es it ic v ol ca ni cs 10 : L ak e Tu ti ra 17 6° 5 4´ 1 0 44 E , 3 9° 1 4´ 0 0 44 S L. s co pa ri um 20 0– 37 5 m ud st on e, s an ds to ne , a nd li m es to ne 11 : W ai nu io m at a & Ca nn on s Cr ee k 17 4° 5 7´ 1 9 75 E , 4 1° 1 7´ 4 5 29 S Co pr os m a gr an di flo ra , W ei nm an ni a ra ce m os a, a nd M el ic yt us r am ifl or us 11 7 al te rn at in g da rk g re y ar gi lli te a nd g re yw ac ke s an ds to ne 12 : L on g G ul ly 17 4° 4 0´ 5 5 30 E , 4 1° 1 8´ 3 4 82 S Ku nz ea a m at hi co la 30 0– 40 0 ar gi lli te a nd g re yw ac ke s an ds to ne w it h ra re li m es to ne an d vo lc an ic s 13 : R iv er sd al e 17 5° 2 5´ 5 3 49 E , 4 1° 3 0´ 5 7 74 S Ku nz ea r ob us ta 60 –2 00 gr ey w ac ke -l ik e da rk g re y m ud dy s ilt st on e w it h m in or co ng lo m er at es a nd s pi lit ic la va 14 : C oa tb ri dg e 17 3° 3 9´ 2 3 16 E , 41 ° 2 9´ 0 8 99 S L. s co pa ri um a nd K un ze a sp p. 20 0– 30 0 m et am or ph os ed s ed im en ta ry li th ol og ie s an d vo lc an ic s 15 : L on g Sp ur 17 5° 3 2´ 0 9 01 E , 4 1° 2 7´ 2 2 12 S Ku nz ea r ob us ta 40 –2 00 sa nd st on e an d m ud st on e, m in or c on gl om er at es a nd vo lc an ic s 16 : P eg gi oh 17 4° 0 1´ 1 3 67 E , 4 1° 5 1´ 3 1 57 S L. s co pa ri um a nd K un ze a ro bu st a 20 0– 30 0 gr ey w ac ke a nd a rg ill it e w it h m in or v ol ca ni cs , co ng lo m er at es , a nd r ar e lim es to ne 17 : S he na nd oa h 17 2° 1 5´ 0 5 30 E , 4 1° 5 3´ 3 6 00 S Ku nz ea e ri co id es 20 0– 30 0 lim es to ne a nd c al ca re ou s si lt st on e, lo ca l s an ds to ne a nd co al m ea su re s 18 : A vo ca S ta ti on 17 1° 5 3´ 2 3 31 E , 43 ° 1 1´ 4 9 51 S Ku nz ea s er ot in a 42 0– 54 0 gr ey w ac ke a nd a rg ill it e w it h m in or v ol ca ni cs , co ng lo m er at es , a nd r ar e lim es to ne 19 : E yr ew el l. 17 2° 1 1´ 4 1 76 E , 4 3° 2 2´ 5 9 35 S Ku nz ea s er ot in a 20 0 po st -g la ci al a llu vi um a nd g la ci al o ut w as h gr av el s 20 : H in ew ai . 17 3° 0 2´ 1 8 74 E , 4 3° 4 9´ 0 2 85 S Ku nz ea r ob us ta 20 –4 50 ba sa lt tu ff , a nd a ss oc ia te d in tr us iv e ro ck s 21 : D un ed in 17 0° 3 6´ 3 7 14 E , 4 5° 4 5´ 1 1 19 S L. s co pa ri um a nd K un ze a ro bu st a 20 0– 30 0 lo es s, b as al t a nd p ho no lit e earliest of the published data (Kirk 1889, but mostly by Entrican et al. 1951, and republished by Hinds & Reid 1957, Harris 1986, and Clifton 1990), tree age is rarely specified, and variations in basic stem-wood density values derived from merchantable-sized trees after removal of the bark is not given. For comparative purposes we use these few available published values (Appendix Table A2) together with a larger data set of mean age-specific/non-age-specific wood density values (bark removed) collected from Carbon Monitoring System (LUCAS) plots (20m x 20 m) across a wide range of well-established and pre-defined natural forest and shrubland types (Table A2) indicative of advanced succession toward indigenous forest (Hall et al. unpublished data2, Peltzer & Payton unpublished data3, Beets et al. 2012 and unpublished data1). We did not attempt to analyse for the influence of bark thickness on basic stem wood density values (i.e. inclusive versus exclusive of bark), as for the age-range (3- to 105-years old) of the shrubland species presented in this paper, all values were expected to fall well within the range of the published data. In the absence of reliable basic stem-wood density values for individual stems, often determined for only a small sample size of trees with widely varying, or of unknown age, and variability in basic stem-wood density values, the values in this paper are presented as means (Appendix Tables A3–A5). All statistical analyses were undertaken using Genstat (VSN International, Hemel Hempstead, UK) and were considered significant if P<0.05. Results Basic stem-wood density-allometric relationships For >6-year-old regenerating Kunzea spp. basic stem- wood density was significantly, positively correlated with tree height, as was also the case for L. scoparium (Table 2). Of the plot-based species <6-years old, the correlation for basic stem-wood density with tree height was strongest (and positive) for Prumnopitys ferruginea (Table 2) but was only just statistically significant, probably due to the small sample size (n=7). Interestingly, Dacrycarpus dacrydioides exhibited a significant negative correlation with about 30% of the variation in basic stem-wood density explained by tree height. There were no other significant relationships between basic stem-wood density and tree height for the remaining plot-based or regenerating shrubland species. Basic stem-wood density and RCD were positively correlated for regenerating L. scoparium and Kunzea spp. >6-years old (Table 2). Root collar diameter and density values were negatively correlated for plot- based Dacrycarpus dacrydioides (Table 2). There were no significant correlations between basic stem-wood density and RCD for the remaining plot-based and regenerating shrubland species <6-years old. Basic stem-wood density and DBH were positively correlated for regenerating L. scoparium, Kunzea spp., plot-based Dacrydium cupressinum and Prumnopitys ferruginea (Table 2) with DBH explaining 17–73% of the variation in density. Basic stem-wood and DBH were negatively correlated for Dacrycarpus dacrydioides (Table 2). There were no significant correlations between basic stem-wood density and DBH for the remaining plot-based and regenerating species. Basic stem-wood density was not correlated with tree age for low-density plantings of L. scoparium (site 10) between ages 4- and 6-years and increased with increasing tree age (data not shown). Conversely, for naturally reverting stands of L. scoparium, Kunzea spp., Coprosma grandiflora, Melicytus ramiflorus and Weinmannia racemosa, basic stem-wood density values of ≥6-years-old trees were not significant. Comparisons of mean basic wood densities by age- class Basic stem-wood density of L. scoparium was greater than for the remainder of the plot-based species trialled for trees <6-years of age (Fig. 2a). Basic stem-wood density was as follows for the various species in this age group: L. scoparium > Alectryon excelsus > Dacrycarpus dacrydioides = Podocarpus totara = Prumnopitys ferruginea = Dacrydium cupressinum > Agathis australis = Vitex lucens. For naturally regenerating stands between 6–10 and 11–15 years old, Kunzea spp. had greater basic stem- wood density than Melicytus ramiflorus (Fig. 2b). Basic stem-wood density of Kunzea spp. was also greater than Coprosma grandiflora and Melicytus ramiflorus in the 16– 20 (Fig. 2b) and 21–25-year-old age class (Fig. 2c). There was no difference in basic stem-wood density between Coprosma grandiflora and Melicytus ramiflorus between 16–20 (Fig 2b) and 21–25-year-old age classes (Fig 2c). In the age classes 26–30, 31–35, 36–40 (Fig. 2c), and 46-50, 51–70 years (Fig. 2d) there were no differences in basic stem-wood density between Kunzea spp. and L. scoparium. However, for the oldest of the age classes their respective densities were significantly greater (P<0.05) than for Weinmannia racemosa of the same age (Fig. 2d). Irrespective of age, the basic stem-wood density values for both Kunzea spp. and L. scoparium were not significantly different from each other but were significantly greater than that for all other species for which age-specific data was available. Comparisons of basic stem-wood density values with published data Basic stem-wood densities for ≥6-year-old specimen trees of L. scoparium, Kunzea spp., Melicytus ramiflorus, Coprosma grandiflora, and Weinmannia racemosa derived from natural stands indicative of advanced succession toward indigenous forest, fall within the range of these published values (Fig. 3a). Conversely, the mean basic stem-wood density values for trees <6-years old were either bordered on the lower limit of published means of older trees or significantly lower than published values (Fig. 3b). Marden et al. New Zealand Journal of Forestry Science (2021) 51:1 Page 5 3Peltzer, D.A., & Payton, I.J. (2006). Analysis of carbon monitoring system data for indigenous forests and shrublands collected in 2002/03. Landcare Research Contract Report LC0506/099. 55 p. Marden et al. New Zealand Journal of Forestry Science (2021) 51:1 Page 6 Sp ec ie s Lo ca ti on N o. tr ee s Si te ty pe * H ei gh t R CD D B H A ge r² P r² P r² P r² P Ku nz ea s pp . Tu ra ng i 22 R S 0. 12 0 <0 .0 01 0. 20 1 <0 .0 01 0. 06 7 0. 00 1 0. 00 4 0. 39 2 W ai m at a 32 R S To la ga B ay 13 R S D un ed in 11 R S W ai ta ke re 6 R S Co at br id ge 3 R S Lo ng G ul ly 5 R S R iv er sd al e 21 R S Ey re w el l 2 R S N ik au V al le y 56 R S Le pt os pe rm um s co pa ri um Tu ra ng i 24 R S 0. 20 9 0. 00 3 0. 17 9 0. 00 6 0. 16 6 0. 01 0 0. 13 4 0. 00 2 D un ed in 2 R S Al ec tr yo n ex ce ls us G is bo rn e 13 PB 0. 08 1 0. 34 5 0. 24 7 0. 08 4 0. 21 6 0. 10 9 D ac ry ca rp us d ac ry di oi de s G is bo rn e 30 PB 0. 29 5 0. 00 2 0. 43 3 <0 .0 01 0. 40 2 <0 .0 01 Po do ca rp us to ta ra G is bo rn e 9 PB 0. 02 6 0. 67 6 0. 37 9 0. 07 7 0. 3 0. 12 7 Ag at hi s au st ra lis G is bo rn e 8 PB 0. 14 5 0. 35 2 0. 08 1 0. 49 5 0. 02 3 0. 72 1 D ac ry di um c up re ss in um G is bo rn e 14 PB 0. 00 6 0. 8 0. 10 9 0. 24 9 0. 42 6 0. 01 1 Pr um no pi ty s fe rr ug in ea G is bo rn e 7 PB 0. 57 9 0. 04 7 0. 27 1 0. 23 1 0. 73 2 0. 01 4 Vi te x lu ce ns G is bo rn e 8 PB 0. 44 6 0. 07 1 0. 30 1 0. 15 9 0. 27 8 0. 17 9 Co pr os m a gr an di flo ra W el lin gt on 10 R F 0. 07 1 0. 48 7 0. 00 8 0. 80 6 0. 01 2 0. 75 9 0. 15 8 0. 25 8 M el ic yt us r am ifl or us W el lin gt on 30 R F 0. 00 6 0. 68 8 0. 00 9 0. 61 5 0 0. 96 1 0. 03 0 0. 09 7 W ei nm an ni a ra ce m os a W el lin gt on 10 R F 0. 18 3 0. 21 8 0. 12 7 0. 31 1 0. 17 6 0. 22 7 0. 00 2 0. 91 2 TA B LE 2 : Li ne ar r eg re ss io ns b et w ee n st em -w oo d de ns it y an d tr ee h ei gh t ( m ), ro ot c ol la r di am et er (R CD ; m m ), di am et er a t b re as t h ei gh t ( D B H ; m m ) a nd a ge ( ye ar s) fo r 12 o f N ew Z ea la nd ’s in di ge no us s pe ci es . R eg re ss io ns fo r bo th K un ze a sp p. a nd L . s co pa ri um in cl ud ed d at a fr om c ol le ct iv e si te s. V al ue s in b ol d w er e st at is ti ca lly s ig ni fic an t (P <0 .0 5) . *R S = re ge ne ra ti ng s hr ub la nd , P B = p lo t- ba se d gr ow th tr ia l, R F = re ge ne ra ti ng fo re st Marden et al. New Zealand Journal of Forestry Science (2021) 51:1 Page 7 FIGURE 2: Stem-wood density values for: a) species <6-years old from plot-based growth trials; b) 6–10-year-old Kunzea spp. and Leptospermum scoparium, for 11–15-year-old Kunzea spp. and Melicytus ramiflorus, and for 16–20-year-old Kunzea spp., Melicytus ramiflorus, and Coprosma grandiflora older than 6-years collected from regenerating shrubland or forest; c) 21–25-year-old Melicytus ramiflorus and Coprosma grandiflora, and for 26–30-year-old, 31–35-year-old, and 36–40-year-old Kunzea spp. and L. scoparium collected from regenerating shrubland or forest ≥6-years old; and d) 46–50 and 51–70-year-old Kunzea spp., L. scoparium and Weinmannia racemosa collected from ≥6-years-old regenerating shrubland or forest. Error bars represent the standard error of the mean. Sample numbers shown at base of each grey bar. Bars with different letters were significantly different (P<0.05). FIGURE 3: Comparison of: a) age-specific mean basic stem-wood density values for Kunzea spp. and Leptospermum scoparium ≥6-years old with densities sourced from published and unpublished literature. Density data for trees of known age was analysed separate to that for trees where age was not specified (see Table A2); and b) comparison of mean basic wood densities for trees <6-years old (grey bars) with mean densities of ≥6-year- old trees (dots) as sourced from published and unpublished literature (see Table A2). For Melicytus ramiflorus, Coprosma grandiflora, and Weinmannia racemosa, age-specific mean basic stem-wood density values (white bars in Fig. 3a) are compared with mean densities (dots) sourced from published and unpublished literature where age was not specified. Sample numbers shown at base of each bar. Error bars represent the standard error of the mean. Geographic distribution in Kunzea spp. and L. scoparium basic stem-wood density While there is considerable variation in mean basic stem-wood values within naturally regenerating stands of Kunzea spp. and L. scoparium, there is no supporting evidence that their density is significantly different between locations within either the North or South Island of New Zealand, between these islands, or between latitudes 35° to 46°S (Fig. 4). For all remaining species there was insufficient basic stem-wood density data to support a similar statistical analysis. Discussion Basic wood density is one of the largest sources of variation in estimates of biomass and in the calculation of carbon sequestration (Holdaway et al. 2014), yet these estimates are essential for New Zealand’s international and national reporting of GHG budgets. To date, allometric functions have largely been based on limited stem-wood density data, and where species-specific and/or regional basic stem-wood density values are TABLE 2: Confusion matrix unavailable, congeneric values have been used instead, or, in their absence, the mean of all published values have been used (Peltzer & Payton unpublished data3, Beets et al. unpublished data1). However, given that the earliest of the published values of basic stem wood density for merchantable timber trees were likely determined following the removal of the bark, a comparison with the means of all age-specific stem-wood densities, whether determined with the bark intact or after the removal of bark, might be considered invalid. Nonetheless, as has been shown in this paper, the basic stem-wood densities of ≥6-year-old trees comprising natural stands indicative of advanced succession toward indigenous forest fall well-within the range of the earlier published values. Furthermore, given the dearth of available data for many of the dominant and larger tree components of New Zealand’s indigenous forests, the diversity of species, and the difficulty of accessing them in remote locations, where species-specific wood density values obtained for indigenous species harvested for timber exist, they serve as valuable reference points. Marden et al. New Zealand Journal of Forestry Science (2021) 51:1 Page 8 FIGURE 4: Mean basic stem-wood density values for Kunzea spp. (17 locations) and Leptospermum scoparium (4 locations) trees from naturally regenerating stands distributed throughout the North and South Islands between latitudes 35° and 46°S. Site locations are shown in Figure 1. Annotated site details are tabulated in Table 1 and presented in greater detail in Table A1. Error bars represent the standard error of the mean. Bars with different letters were significantly different (P<0.05). At the younger end of the age spectrum, for species typically associated with the early phase of shrubland regeneration, tall statured shrubland classes, and mixed species forests, insufficient basic wood density data together with simple field measurements are a limitation to the development of appropriate allometric functions for improving estimates of biomass and carbon stocks. Furthermore, the use of different methods in the measurement of basic stem wood density (over bark versus under bark) has necessitated the development of equations that account for related variations in basic wood density in the calculation of tree biomass and changes in carbon stocks over time (Hall et al. unpublished data2). However, until additional basic stem-wood density data can be collected for a sufficiently diverse range of specimen trees comprising a wide range of indigenous shrubland, forest types, and ages, the continued use of the mean of all available basic stem-wood density values will likely give the best estimate of stem carbon stocks. Although the basic stem-wood densities of Kunzea spp. and L. scoparium (both widely distributed shrubland species and a dominant component of regenerating forest on extensive areas of marginal hill country), are not significantly different from each other, they are both significantly higher than those of most of New Zealand’s oldest indigenous forest and other shrubland species typically falling between 400 and 600 kg m3 (Allen et al. 1992). Therefore, using functions based on the stem- wood density of either Kunzea spp. or L. scoparium to scale tree volume, as yield or growth, to stem biomass, and from stem biomass to total biomass for different mixed-species indigenous forest communities is likely to overestimate total biomass. For Kunzea spp., while there is variation in intra- specific mean basic stem-wood density values at different sites, there is no evidence from our data that stem-wood density is significantly different between the 17 locations where this species occurs as naturally regenerating shrubland. Trends of increasing wood density values with decreased elevation (Lassen & Okkonen 1969) and increased temperature (Filipescu et al. 2014) have been reported for New Zealand-grown Douglas-fir (Kimberley et al. 2017), and for P. radiata basic wood density values show a gradual decrease from sea level to higher elevations, and from north to south (Clifton 1990, Palmer et al. 2013). For Kunzea spp., however, while the results support a correlation between decreasing basic wood densities from sea level to higher elevations, there remains little evidence in support of wood densities decreasing north to south. Other environmental influences, including intolerance to salt (Esler & Astridge 1974), soil fertility (Cown & McConchie 1981), soil moisture retention and stress (Smale 1994), variations in genetics (de Lange 2014) and rainfall distribution, are also likely to affect growth strategies (Wardle 1969), tree form, and ultimately basic stem-wood density of many of New Zealand’s indigenous shrubland and forest species. A site-by-site analysis of these factors was considered beyond the scope of this paper. Mean basic stem-wood densities of trees <6-years old were either significantly lower, or at the lower end of published values (Fig. 3b), but that within ca. ≥6 years after establishment, basic stem-wood density values approach that of older trees, and differs little thereafter (Fig. 3a). We therefore concur with Beets et al. (unpublished data1) on the strength of this relationship. Differences in basic stem-wood density values between trees <6-years old and older are therefore likely to be primarily a function of their age. Deng et al. (2014) found that stem-wood density of Pinus massoniana stems was significantly influenced by tree age, relative heights, and social class, while Beets et al. (2012) confirmed that stem-wood density at each relative height in older trees (age unspecified) was significantly higher than that of younger trees. Iida (2012) found that low stem-wood density was linked to the propensity of some species to select for vertical growth (tall and thin stemmed with narrow and shallow canopies) and may therefore underlie the interspecific trade-off between effective height gain and a persistent life in the understorey (Kohyama 1987, 1993; Kohyama & Hotta 1990). Furthermore, relationships between stem-wood density and tree height may be related to differences in stand density. For example, L. scoparium <6-years old in densely-stocked, naturally reverting stands are tall and thin-stemmed and contrast markedly with the shorter and thicker-stemmed trees that develop when planted at low densities (Marden et al. 2020). Perhaps, as has been shown in studies across a range of conifer species (Watt et al. 2011), the basic stem-wood density of L. scoparium would be expected to be lower in wider-spaced (planted) stands than in fully stocked stands that have reverted naturally. Unfortunately, insufficient wood density data for L. scoparium <6-years old from naturally reverting stands precluded such an analysis. To reduce net greenhouse gas emissions, as required under the Kyoto Protocol (Ministry of the Environment 2010), a number of government-funded schemes (e.g. Afforestation Grant Schemes (Ministry for Primary Industries 2015a) and the Permanent Forest Sink Initiative (Ministry for Primary Industries 2015b) have been introduced to facilitate natural regeneration of shrubland, and the planting of new areas of forest (exotic and indigenous). Together with the recently announced government goal to plant one billion trees over the next 10 years (1 BT Programme) (Ministry for Primary Industries 2018), ca 1.45 million ha of steep, erosion- prone pastoral hill country considered marginal for long-term agriculture will be targeted for transitioning to a permanent indigenous shrubland or forest (Trotter et al. 2005). In such high-risk areas woody indigenous shrubland largely comprising Kunzea spp. and L. scoparium has in the past played a significant role in mitigating erosion (Marden & Rowan 1993; Ministry for Primary Industries 2015a, 2015b, 2016). Together with increasing interest in high UMF (unique mānuka factor) values associated with honey produced by L. scoparium, the establishment of low-density plantings averaging ca 825 to 1100 stems ha–1 (McPherson & Newstrom- Marden et al. New Zealand Journal of Forestry Science (2021) 51:1 Page 9 Lloyd 2018) is seen as an alternative and viable land management option for erosion prone steeplands (Ministry for Primary Industries 2015c). Using linear regression analyses based on mean wood density values measured for Leptospermum scoparium <6-years old, new plantings at the recommended planting density, would by year 5 amass a forest carbon stock of 6.1 t CO2 ha−1 (excluding coarse woody debris and fine litter on the forest floor) (Marden & Lambie 2016). Alternatively, a mixed planting of successional broadleaved and conifer species would within the same time frame potentially amass a carbon stock of ~3.8 t CO2 ha -1 (Marden et al. 2018), while plantings consisting of a mix of early colonising seral species would amass a forest carbon stock of 8.8 t CO2 ha -1 (unpublished). Thus, the establishment of early colonising seral species on marginal land would amass an additional ~1 t CO2 ha−1 over and above the 7.8 t CO2 ha −1 estimated for the 5-year period from the date of planting (Ministry for Primary Industries 2017). Conversely, the planting of mixed indigenous broadleaved and coniferous species at the same density would amass ~4 t CO2 ha -1 less, and plantings of Leptospermum scoparium ~1.7 t CO2 ha −1 less. By implication, to achieve a similar level of carbon stock for new plantings of broadleaved and conifer species within this time frame would require an increase in planting density to ~2000 stems ha-1 and for areas planted and managed for mānuka honey production, a planting density of 1200–1300 stems ha-1 would be required. These estimates of carbon stocks are however based on only a few studies of indigenous species that comprise the many shrubland and forest communities present within New Zealand. With the pending conversion of extensive areas of former pastoral land to indigenous shrubland and forest through passive reversion, and by planting, therein lies an opportunity to validate and/or improve the accuracy of current estimates of biomass and carbon stocks during their early growth period, and for a wider range of species, by developing further allometric functions based on species-specific, basic stem-wood density values. Conclusions This study presents an analysis of a significant database of previously unpublished basic wood-density values collected for a range of New Zealand’s indigenous shrubland and forest species of varying age, and from sites located throughout both North and South Islands. The findings indicate that for the most geographically widespread shrubland species, Kunzea spp., differences in local site factors may affect tree parameters including basic wood density to a greater extent than wide differences in latitude within the normal growing range of the species. The data do however support trends showing that basic wood density values increase with decreased elevation, and increased temperature and where local data are available its use would improve the accuracy of biomass estimates both locally and nationally. Insufficient site-specific information precludes further comment on other factors (e.g. soil fertility, plant spacing) that likely contribute to variability in basic stem-wood density values. For each of the species <6-years old for which basic stem-wood densities were collected, their mean values were significantly lower, or at the lower end of published values for trees ≥6-years old after which basic stem- wood density values remain unchanged. Age-specific basic stem-wood density data is scarce for shrubland communities dominated by mixed softwood species that comprise 90% of the national live tree biomass stock. Furthermore, as their stem-wood density is considerably lower than for hardwood species, additional stem-wood density data are needed for use in combination with species-abundance information from LUCAS plots to update allometric functions applicable to areas of naturally reverting shrubland and to areas of former pastoral land pending their conversion to indigenous shrubland. As shown for the few indigenous species for which biomass and/or wood density data has been collected, at a planting density of 1000 stems ha-1, early colonising seral species would within 5-years amass a higher carbon stock of 8.8 t CO2 ha −1 than would plantings of Leptospermum scoparium ~6.1 t CO2 ha −1 or a mixed- species planting of indigenous broadleaved and coniferous species ~3.8 t CO2 ha -1. To account for the variability in densities between outer-wood (and bark) and inner-wood with tree height, estimates of the mean density of whole stems will require the collection of stem-wood data from discs at intervals along the stem, as opposed to just breast height or by coring. List of abbreviations DBH Diameter at Breast Height BH Breast Height 1BT One billion Trees Programme ETS Emission Trading Scheme GHG Greenhouse Gas LSD Least significant difference RCD Root Collar Diameter WSG Wood Specific Gravity Competing interests The authors declare that they have no competing interests. Authors’ contributions MM was the primary author. SL compiled the data into spreadsheets and completed the statistical analyses. LB contributed data. All authors read and approved the manuscript. Acknowledgements We acknowledge the support of the Tairāwhiti Polytechnic Rural Studies Unit, Gisborne, on whose land the plot-based softwood and hardwood plant Marden et al. New Zealand Journal of Forestry Science (2021) 51:1 Page 10 trial was located and to other landowners for allowing access to their respective properties at the time these studies were undertaken. We thank interns Claire Butty (France), Sandra Viel (Germany), Kaisa Valkonen (Finland), and Landcare Research colleague’s Dr Chris Phillips, Alex Watson, Richard Hemming and Scott Bartlam for assistance with data collection. Hawke’s Bay Regional Council provided Stevie and Jack Smidt to assist with data collection at Lake Tutira. John Dando and Ted Pinkney assisted with the collection of discs and growth- ring counts. Graphics were drawn by Nic Faville. Anne Austin edited the script and GIS support was provided by Anne Sutherland of Landcare Research, NZ, Ltd. This paper was reviewed by Dr Mark Smale, thanks also to the anonymous external reviewers for their valuable comment. 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(2011). Influence of stocking on radial and longitudinal variation in modulus of elasticity, microfibril angle, and density in a 24-year-old Pinus radiata thinning trial. Canadian Journal of Forest Research, 41(7), 1422-1431. https://doi.org/10.1139/x11-070 Williamson, G.B, Wiemann, M.C. (2010). Measuring wood specific gravity correctly. American Journal of Botany, 97(3), 519-524. https://doi.org/10.3732/ ajb.0900243 Marden et al. New Zealand Journal of Forestry Science (2021) 51:1 Page 14 https://doi.org/10.1139/x11-070 https://doi.org/10.3732/ajb.0900243 https://doi.org/10.3732/ajb.0900243 Marden et al. New Zealand Journal of Forestry Science (2021) 51:1 Page 15 APPENDIX TABLE A1: Location and physical characteristics of 21 sample sites throughout New Zealand. Site 1: Tautoro. 8 km south of Kaikohe, Northland (173° 50´ 13 15 E, 35° 28´ 52 00 S). Regenerating Leptospermum scoparium (Table A4) stand on gently, southwest-facing slope 100-140m above sea level. Bedrock consists of greywacke argillites and sandstones (Geological Map of New Zealand, 1967). Soils are deeply weathered and classified as Altic Soils (Hewitt, 2010). Site 2: Waitakere Range. Within the Waitakere Range (174° 35´ 14 42 E, 37° 00´ 10 17 S) stem-wood discs were collected from naturally reverting stands of well-established Kunzea spp. (Table A3) and L. scoparium (Table A4) of unknown age. At an elevation of ca. 40 m, slopes ranged between 0 and 35°. The geology comprises volcanic andesitic lava, conglomerates, and breccia of the Waitemata and Waitakere groups of early Miocene (late Otaian-middle Altonian) age. Soils comprise weathered volcanics consisting of yellow-brown granular clay grading to a compact yellow brown to brown subsoil (Hayward, 1983). The climate is relatively mild and moist with annual rainfall of ca 1250 mm increasing to over 2000 mm in the higher central parts at elevations of ca 460 m (New Zealand Meteorological Service, 1966). Site 3: Nikau Valley. 8km south of Whakatane, Bay of Plenty (176° 58´ 23 85 E, 38° 01´ 25 27 S). Managed, dense, east-facing Kunzea robusta (Table A3) stands of all ages 40–100 m above sea level. Bedrock consists of undifferentiated greywacke (Geological Map of New Zealand, 1967). Pumice Soils consisting of Tarawera and Whakatane Ash overly bedrock on rolling hill country (Hewitt, 2010). Sites 4–6: Tolaga Bay and site 7: Waimata Valley. Sites 2–4 are located approximately 8 km inland of Tolaga Bay (178˚ 12΄ 19 29 E, 38˚ 20΄42 58 S), and site 5 is located 15 km inland of Gisborne City (178° 03΄ 13 66 E, 38˚ 28΄ 33 84 S). Each site represents an even-canopied stand of naturally reverting Kunzea robusta (Table A3) at a different stage of development, the age of which was determined by the history of vegetation clearance, and verified by growth ring counts (Watson et al., 1994). The Tolaga Bay sites occur on slopes between 23° and 32°, have a NW (300o) to NE (60o) aspect, and are at elevations between ca 64 m and 160 m above sea level. The Waimata site is on a SW aspect at an elevation of 207 m. The underlying bedrock at these sites consists of Pliocene-age calcareous sandy siltstones with banded sandstones and thick tuffaceous horizons (Kingma, 1965). Soils are a stony colluvium varying from Orthic Recent Soils and their intergrades to Brown Soils (on well-drained sites) and Gley Soils (on poorly drained sites) typical of slopes being eroded or has received sediment mainly as a result of slope processes (Hewitt, 2010). The climate is warm temperate maritime, with moist summers and cool wet winters. Mean annual rainfall varies from about 700 mm at the coast to 2500 mm at higher elevations (New Zealand Meteorological Service, 1973). Lengthy periods of little or no rainfall are common during January to April (mid-summer to late autumn). This region has a history of extreme rainfall events (Kelliher et al., 1995), often associated with storms of tropical origin (e.g. Cyclone Bola in 1988). Site 8: Gisborne. Five indigenous softwood (Agathis australis, Prumnopitys ferruginea, Podocarpus totara, Dacrycarpus dacrydioides, Dacrydium cupressinum) and two hardwood species (Alectryon excelsus and Vitex lucens) (Table A5) were established as a planting trial to establish their relative growth performance, above-and below-ground, over a 5-year period (Marden et al., 2018). The trial site was located on a low-lying (5 m above sea level), even-surfaced alluvial terrace adjacent to the Taraheru River, in Gisborne City (178° 00´ 16 02 E, 38° 38´ 44 82 S). The soil is a naturally fertile, free draining, Typic Sandy Brown Soil of the Te Hapara soil series (Hewitt, 2010) with no physical or chemical impediments. Temperatures over summer average 23° C and over winter 12° C and mean annual rainfall is ca 1200 mm (Hessell, 1980). Site 9: Turangi. Stands of 25-, 35- and 55-year-old Kunzea spp. (Table A3) and L. scoparium (Table A4) were selected in Tongariro National Park near Turangi township in the central North Island (175° 47´ 11 53 E, 39° 09´ 19 20 S) at an elevation of 800 m, approaching the maximum elevation at which these species are found (Scott et al., 2000). Mean annual temperature is 11.1C°, and mean annual precipitation is ca 1610 mm. Soils derived from a series of rhyolitic and andesitic volcanic eruptions are classified as Podzolic Orthic Pumice soils of the Rangipo series (Hewitt, 2010). Site 10: Lake Tutira. L. scoparium (Table A4) was planted at Lake Tutira (176° 54´ 10 44 E, 39° 14´ 00 44 S) in 2011 and 2012 at a spacing (3 m × 3 m, ca 1100 stems ha–1) more typical of an exotic plantation forest. Nine permanent sample plots (20 m × 20 m) were established in 2015 (Marden & Lambie, 2015 & 2016). The terrain is 7e3 (Jessen et al., 1999) consisting of Pliocene-age mudstone, sandstone, and limestone subjected to extreme shallow landsliding during storm events. Slight tunnel gullying is also present. Slopes are predominantly west facing, between 21° and 35⁰, and occur at an elevation of 200°–375 m. Soils are Typic Immature Pallic (Hewitt, 2010). Site 11: Wainuiomata and Cannons Creek. This site consists of well-established indigenous hardwoods and lowland shrub communities dominated by mixed hardwood Coprosma grandiflora, Weinmannia racemosa, and Melicytus ramiflorus (Table A5) shrubs indicative of advanced succession progressing toward indigenous forest. Three plots were installed (174° 57´ 19 75 E, 41° 17´ 45 29 S) on slopes ranging between 17° and 28°, with a southwest aspect between 200° and 240°, and at an elevation of ca 117 m. The geology consists of complexly deformed alternating dark grey Marden et al. New Zealand Journal of Forestry Science (2021) 51:1 Page 16 argillite and greywacke sandstone, rare limestone and minor spilitic lava of Triassic age (Kingma, 1967). Soils are a stony colluvium derived from greywacke bedrock and vary from Orthic Recent Soils and their intergrades to Brown Soils (on well-drained sites) and Gley Soils (on poorly-drained sites) typical of slopes being eroded or has received sediment mainly as a result of slope processes (Hewitt, 2010). Site 12: Long Gully. 6 km southwest of Wellington (174° 40´ 55 30 E, 41° 18´ 34 82 S). Regenerating wind shorn stands of Kunzea amathicola (Table A3) on south-facing slope 300-400 m above sea level. Bedrock consists of alternating argillite and greywacke sandstone with rare limestone and volcanics (Kingma, 1967). Soils are a stony colluvium derived from greywacke bedrock and vary from Orthic Recent Soils to Brown Soils and Gley Soils typical of slopes being eroded or has received sediment mainly as a result of slope processes (Hewitt, 2010). Site 13: Riversdale. Near White Rock on the SE coast of Wairarapa (175° 25´ 53 49 E, 41° 30´ 57 74 S). Wide range of Kunzea robusta (Table A3) stands at different stages of development on mainly southwest-facing slopes 60–200m above sea level. Bedrock consists of greywacke-like dark grey muddy siltstone with minor conglomerates and spilitic lava (Kingma, 1967). Soils are a stony colluvium derived from greywacke bedrock and vary from Orthic Recent Soils to Brown Soils and Gley Soils typical of slopes being eroded or has received sediment mainly as a result of slope processes (Hewitt, 2010). Site 14: Coatbridge. 12 km west of Renwick, Marlborough (173° 39´ 23 16 E, 41° 29´ 08 99 S) Dense regenerating Kunzea spp. (Table A3) and L. scoparium (Table A4) on moderate to steep south facing slopes 200–300m above sea level. Bedrock consists of metamorphosed sedimentary lithologies and volcanics (New Zealand Geological Survey, 1972). Soils are derived from greywacke bedrock and vary from Brown Soils to Orthic Recent and Gley Soils typical of slopes being eroded or has received sediment mainly as a result of slope processes (Hewitt, 2010). Site 15: Long Spur. 9 km south of Tururumuri near the southeast coast of Wairarapa (175° 32´ 09´ 01 E, 41° 27´ 22 12 S). Dense regenerating stands of Kunzea robusta (Table A3) on slopes on a range of aspects 40–200 m above sea level. Bedrock consists of graded bedded, fine-grained, sandstone and mudstone, minor conglomerates and volcanics (Kingma, 1967). Soils are a stony colluvium derived from greywacke bedrock and vary from Orthic Recent Soils to Brown Soils and Gley Soils typical of slopes being eroded or has received sediment mainly as a result of slope processes (Hewitt, 2010). Site 16: Peggioh. 10 km west of Ward (174° 01´ 13 67 E, 41° 51´ 31 57 S). Dense, regenerating Kunzea robusta (Table A3) and L. scoparium (Table A4) stands 200–300 m above sea level. on south-facing slopes. Bedrock consists of interbedded greywacke and argillite with minor volcanics, conglomerates, and rare limestone (New Zealand Geological Survey, 1972). Soils are a stony colluvium derived from greywacke bedrock and vary from Brown Soils to Orthic Recent and Gley Soils typical of slopes being eroded or has received sediment mainly as a result of slope processes (Hewitt, 2010). Site 17: Shenandoah. 20 km south of Murchison, Buller (172° 15´ 05 30 E, 41° 53´ 36 00 S). Regenerating Kunzea ericoides (Table A3) stand on west-facing slope 200–300 m above sea level. Bedrock consists of mainly limestone and calcareous siltstone, local sandstone and coal measures (New Zealand Geological Survey, 1972). Soils are classed as Brown and Melanic Soils (Hewitt, 2010). Site 18: Avoca Station 22 km south of Cass, Canterbury (171° 53´ 23 31E, 43° 11´ 49 51 S). Regenerating stands of Kunzea serotina (Table A3) on north-facing slopes 420–540 m above sea level. Bedrock consists of interbedded greywacke and argillite with minor volcanics, conglomerates, and rare limestone (New Zealand Geological Survey, 1972). Soils are a stony colluvium derived from greywacke bedrock and vary from Orthic Recent Soils to Brown Soils and Gley Soils typical of slopes being eroded or has received sediment mainly as a result of slope processes (Hewitt, 2010). Site 19: Eyrewell. 10km south of Oxford and 6km north of Waimakariri River, Canterbury Plains (172° 11´ 41 76 E, 43° 22´ 59 35 S). Fenced remnant Kunzea serotina (Table A3) stand 200 m above sea level. Flat floodplain, well drained post- glacial alluvium and glacial outwash gravels (New Zealand Geological Survey, 1972). Soils are classed as Stony Brown Soils (Hewitt, 2010). Site 20: Hinewai. 5km east of Akaroa, banks Peninsula above Otanerito Bay (173° 02´ 18 74 E, 43° 49´ 02 85 S). Wide range of Kunzea robusta (Table A3) stands at different stages of development on steep southeast-facing slopes 20–450 m above sea level. Bedrock consists of basalt tuff and associated intrusive rocks (New Zealand Geological Survey, 1972). Soils are classed as Melanic Soils (Hewitt, 2010). Site 21: Dunedin. This study site consists of a ca 130 ha mosaic of 2–70 year old stands of Kunzea robusta (Table A3) and L. scoparium (Table A4) forest located on the western side of the Purakanui Inlet catchment (170° 36´ 37 14 E, 45° 45´ 11 19 S), 16 km north of Dunedin. Soils are described as brown granular loams and clays derived from loess, basalt and phonolite (Tomlinson & Leslie, 1978). Slopes are NE-E facing between 2° and 35°, and at 200–300 m elevation. Annual rainfall is about 680 mm (New Zealand Meteorological Service, 1984). TABLE A1 Continued... Marden et al. New Zealand Journal of Forestry Science (2021) 51:1 Page 17 TABLE A2: Non-age specific basic mean wood density values for old growth indigenous forest and shrubland species Tree species Wood density (kg m–3) Location/number/age Reference Leptospermum scoparium (mānuka) 695-714 Woodhill, CMS plot BB114 Payton (pers. comm.) 906-1042 Kirk (1989) 892 CMS plots, n=1573 Peltzer & Payton unpublished dataa 720 Puketi Forest, Northland Jager et al. (2014) Kunzea spp. (kānuka) 671-720 Camp Creek, Woodhill Payton (pers. comm.) 757 Clifton (1990), Bier (1983) 642 Akaroa, n=40, <50 years Carswell et al. (2012) 680 Auckland Schwendenmann (2014) 772 CMS plots, n=1708 Peltzer & Payton unpublished dataa Alectryon excelsus (titoki) 622 Woodhill Payton (pers. comm.) 837 CMS plots, n=4 Peltzer & Payton unpublished dataa 854 Bier & Britton (1999) Dacrycarpus dacrydioides (kahikatea) 465 Gray County, n=5 Kirk (1889) 410 Gray Country, 152-310 years Entrican (1951) 390 Hinds & Reid (1957) in Harris (1986) 450 Clifton (1990) 420 CMS plots, n=118 Peltzer & Payton unpublished dataa 440 Maungatautari (n=1) Beets et al. unpublished datab 389 Whirinaki (n=20) Beets et al. unpublished datab 410 Puketi Forest, Northland Jager et al. (2014) 429 Bier & Britton (1999) Podocarpus totara (totara) 443 14-110 years Steward (pers. comm.) 559 Kirk (1889) 430 Taupo County, n=5, 408- 612 years Entrican (1951) 410 Hinds & Reid (1957) in Harris (1986) 480 Taupo County Clifton (1990) 480 CMS plots, n=80 Peltzer & Payton unpublished dataa 383-407 Whirinaki, n-14 Beets et al. unpublished datab 435 Bier & Britton (1999) Agathis australis (kauri) 449 10-69 years Steward (pers. comm.) 489 126-240 years Steward (pers. comm.) 498-595 Kirk (1889) 520 Waitamata county, n=5 Entrican (1951) 480 Waitamata Hinds and Reid (1957) in Harris (1986) 520 CMS plots, n=1 Peltzer & Payton unpublished dataa 470 Puketi Forest, Northland Jager et al. (2014) 441 Taranaki, n=20 Beets et al. unpublished datab 495 Bier & Britton (1999) Marden et al. New Zealand Journal of Forestry Science (2021) 51:1 Page 18 TABLE A2: continued... * Note: Mean basic wood density values from Beets et al. unpublished datab are from breast height outer wood at 5–15 cm (measured from bark). bBeets, P.N., Oliver, G.R, Kimberley., M.O, Pearce, S.H. (2008). Allometric functions for estimating above ground carbon in native forest trees, shrubs and ferns. Scion Report 12679 prepared for the Ministry for the Environment 63 p. Tree species Wood density (kg m–3) Location/number/age Reference Dacrydium cupressinum (rimu) 575 Payton (pers. comm.) 550-644 Kirk (1889) 520 Raurimu, Kaitieke County, n=5, 330-443 years Entrican (1951) 490 Central North Island Hinds & Reid (1957) in Harris (1986) 560 Bier (1983) 595 Clifton (1990) 558 CMS plots, n=456 Peltzer & Payton unpublished dataa 461-466 Whirinaki, n=30 Beets et al. unpublished datab 460 Puketi Forest, Northland Jager et al. (2014) 504 Bier & Britton (1999) Prumnopitys ferruginea (miro) 787 Raurimu, Kaitieke County, n=5, 248-363 yrs Kirk (1889) 520 Kaitieke County Entrican (1951) 510 Hinds & Reid (1957) in Harris (1986) 625 Clifton (1990) 568 CMS plots, n=151 Peltzer & Payton unpublished dataa 592 Maungatautari, n=1 Beets et al. unpublished datab 527-531 Whirinaki, n=26 Beets et al. unpublished datab 510 Puketi Forest, Northland Jager et al. (2014) Vitex lucens (puriri) 573 Auckland Dale (2013) 633 CMS plots, n=8 Peltzer & Payton unpublished dataa 730 Puketi Forest, Northland Jager et al. (2014) Melicytus ramiflorus (mahoe) 396 Maungatautari, n=6 Beets et al. unpublished datab 585 CMS plot, n=638 Peltzer & Payton unpublished dataa 445 Woodhill Forest Payton (pers. comm.) 464 CMS plot AU146 Payton (pers. comm.) Weinmannia racemosa (kamahi) 484 Maungatautari, n=21 Beets et al. unpublished datab 619 CMS plot, n=4175 Peltzer & Payton unpublished dataa 542 CMS plot AZ118 Payton (pers. comm.) 520 CMS plot Q171 Payton (pers. comm.) 553 CMS plot BF117 Payton (pers. comm.) 572 Bier & Britton (1999) Coprosma grandiflora (coprosma) 368 Maungatautari, n=1 Beets et al. unpublished datab 583 CMS plot, n=208 Peltzer & Payton unpublished dataa Marden et al. New Zealand Journal of Forestry Science (2021) 51:1 Page 19 Location Age (y) Ht (m) RCD (mm) DBH (mm) Wood Density (kg m-3) Riversdale 53 9.5 16.0 707 52 11.9 15.7 698 24 5.9 7.4 706 22 6.1 7.3 707 22 4.9 7.0 691 17 4.8 5.7 721 22 4.4 6.0 792 22 5.0 7.0 742 31 5.9 9.0 710 30 6.7 9.3 730 21 5.7 7.8 742 29 9.7 10.3 763 43 8.2 11.6 717 50 8.7 11.0 741 31 5.8 8.7 737 30 7.5 12.1 741 31 6.9 8.9 749 68 9.9 19.5 715 56 10.9 18.8 765 45 9.6 19.2 732 53 12.3 24.6 699 60 12.2 20.4 772 30 6.5 9.7 760 29 6.6 9.3 713 26 7.1 8.7 738 8 2.3 1.0 687 6 2.4 1.0 640 32 8.2 11.2 698 24 7.3 9.0 755 25 8.6 10.3 725 40 8.5 16.4 753 41 9.1 16.2 727 40 6.5 12.6 749 43 10.9 23.3 759 32.3 718 23 4.3 5.0 796 23 4.1 4.8 812 TABLE A3: Basic stem-wood densities, tree age, height, RCD and DBH of individual Kunzea spp. from areas of natural regeneration at: Riversdale (site 13), Turangi (site 9), Shenandoah (site 17), Eyrewell (site 19), Waimata (site 7), Long Gully (site 12), Hinewai (site 20), Tolaga Bay (sites 4-6), Dunedin (site 21), Waitakere (site 2), Avoca (site 18), Coatbridge (site 14), Peggioh (site 16), Long Spur (site 15), and Nikau Valley (site 3). Location Age (y) Ht (m) RCD (mm) DBH (mm) Wood Density (kg m-3) Riversdale 20 4.4 5.1 802 20 3.6 3.8 815 21 4.6 4.2 783 70 8.8 23.3 756 742 Shenandoah 661 673 691 689 743 694 676 799 700 716 Eyrewell 42 11.0 759 46 9.8 642 Turangi 53 6.6 53 43 650 41 5.6 30 26 670 89 101.4 113 98 650 80 8.4 87 77 640 76 9.1 68 58 710 69 9.0 57 48 670 105 12.0 186 141 680 61 7.6 69.5 58 678 67 9.4 100 83 765 28 6.3 65 48 712 34 5.4 42 37 682 29 5.5 44 35 681 35 7.1 97 80 711 37 6.3 122 70 667 63 6.6 43.5 43 622 77 8.4 76 65 721 27 4.0 38.5 38 658 34 5.1 68 45 628 28 7.0 29 26 665 32 6.5 53 36 662 42 9.1 82 73 748 50 9.6 121 110 768 Location Age (y) Ht (m) RCD (mm) DBH (mm) Wood Density (kg m-3) Waimata 15 6.5 110 710 21 12.0 120 734 16 10.7 113 698 18 10.8 119 747 20 12.0 141 777 19 9.8 130 753 16 9.5 142 721 20 11.3 143 750 18 10.2 141 806 17 9.5 120 722 19 8.3 108 655 19 9.7 104 738 16 11.0 134 805 15 9.2 103 732 31 9.5 136 107 704 26 13.0 154 129 734 23 11.5 120 108 729 29 16.4 181 143 786 31 16.4 187 158 828 29 16.4 165 132 789 30 13.3 147 111 647 29 12.1 138 141 720 31 13.3 151 119 774 26 10.6 153 120 731 26 11.9 155 142 743 31 12.8 122 100 766 37 11.4 117 94 86 22 12.2 143 125 811 24 12.4 108 96 722 35 14.2 149 134 849 29 13.7 98 91 771 34 13.9 154 139 757 TABLE A3: continued Location Age (y) Ht (m) RCD (mm) DBH (mm) Wood Density (kg m-3) Tolaga Bay 14 6.6 80 67 758 13 5.7 74 61 674 15 7.2 78 60 703 21 7.2 100 93 790 15 6.6 54 49 694 6 5.7 60 50 686 4 4.6 40 33 647 6 6.2 60 47 652 7 6.8 48 37 704 8 7.4 67 57 730 4 2.1 24 2.4 605 3 1.9 15 1.5 660 4 2.6 36 3.6 714 Long Gully 12 781 15 762 20 690 22 760 26 793 Hinewai 13.5 747 6.5 699 Dunedin 35 10.5 108 97 699 45 10.5 119 101 702 38 9.6 81 75 699 43 11.4 150 130 730 48 10.9 168 150 671 29 8.6 101 84 681 25 9.2 95 72 602 16 7.5 44 35 619 34 9.3 114 102 706 27 7.5 98 76 722 18 6.0 72 62 704 Waitakere 75 18.7 325 247 693 59 14.7 222 177 724 37 8.2 72 62 748 35 8.7 1145 109 704 42 9.1 120 97 700 16 7.5 48 44 704 Avoca Station 748 811 737 770 834 748 742 829 778 751 Marden et al. New Zealand Journal of Forestry Science (2021) 51:1 Page 20 Location Age (y) Ht (m) RCD (mm) DBH (mm) Wood Density (kg m-3) Coatbridge 15 758 15 697 12 782 Peggioh 764 722 765 810 711 686 713 753 735 749 778 800 779 729 731 746 744 758 689 736 764 713 Long Spur 708 753 723 768 764 744 701 783 711 786 TABLE A3: continued Location Age (y) Ht (m) RCD (mm) DBH (mm) Wood Density (kg m-3) Nikau Valley 56 15.5 26.9 725 43 12.6 14.3 711 40 12.8 13.2 739 47 11.4 13.4 734 40 12.6 12.8 737 39 11.6 12.1 736 44 13.7 14.5 724 51 11.5 20.1 673 62 12.4 20.5 694 13 3.7 2.7 603 13 3.2 2.7 624 11 3.7 2.5 662 50 13.7 27.7 731 26 7.8 15.5 677 27 8.8 15.2 670 44 12.5 15.9 696 78 16.0 43.2 732 46 12.5 14.2 735 48 12.6 15.5 765 10 4.2 3.5 629 10 3.5 4.6 687 13 8.5 9.9 687 14 8.2 10.0 687 29 12.3 10.0 658 25 11.5 9.2 592 15 7.2 11.4 602 31 9.6 8.8 683 72 16.9 35.5 612 11 3.4 2.6 608 11 3.4 3.2 668 9 3.5 2.6 626 7 3.2 2.5 604 70 14.0 31.0 703 69 12.1 31.5 714 70 12.6 29.5 690 37 11.5 14.4 755 44 13.0 15.5 673 32 12.5 14.8 721 Marden et al. New Zealand Journal of Forestry Science (2021) 51:1 Page 21 Location Age (y) Ht (m) RCD (mm) DBH (mm) Wood Density (kg m-3) Nikau Valley 46 11.9 20.8 709 47 13.8 19.3 710 42 5.8 6.0 701 13 4.3 5.2 668 11 1.2 661 7 1.5 667 9 2.3 637 6 7.0 5.6 698 12 6.8 5.9 682 13 7.0 6.3 653 16 45 5.4 664 12 4.5 5.0 629 11 4.0 5.0 669 40 8.2 10.5 581 29 8.2 10.9 630 30 8.7 10.7 706 28 7.8 9.7 772 36 10.9 10.4 757 29 8.8 10.5 710 TABLE A3: continued Marden et al. New Zealand Journal of Forestry Science (2021) 51:1 Page 22 Marden et al. New Zealand Journal of Forestry Science (2021) 51:1 Page 23 TABLE A4: Basic stem-wood densities, tree age, height, RCD and DBH of individual Leptospermum scoparium from areas of natural regeneration at Turangi (site 9), Dunedin (site 21), Coatbridge (site 14), Peggioh (site 16), Tautoro (site 1), and from planted stands at Lake Tutira (site 10) Location Age (y) Ht (m) RCD (mm) DBH (mm) Wood Density (kg m-3) Turangi 29 5.4 38 25 690 32 5.9 38 28 770 33 6.1 44 37 660 39 6.4 42 33 870 40 5.8 64 46 870 27 5.5 31 25 720 39 6.2 47 37 760 47 5.6 45 37 720 60 7.5 51 43 720 21 4.9 36 31 721 25 5.1 81 36 778 26 6.3 90 52 756 28 6.2 42 38 642 29 5.6 55 37 682 30 4.6 49 45 684 31 4.0 54 40 710 34 6.1 68 59 739 40 6.7 36 29 672 48 8.0 100 55 718 51 6.7 49 44 667 53 8.4 94 80 710 55 7.6 96 72 712 27 5.8 46 31 824 68 7.8 73 59 716 Dunedin 10 4.0 34 26 665 11 4.5 42 30 680 Lake Tutira 3 2.9 8 6 680 3 2.1 10 6 690 3 2.1 3 1 610 3 2.2 3 3 650 3 2.8 5 1 590 3 2.5 5 700 3 2.0 6 5 650 4 1.8 5 4 660 4 2.3 7 4 680 6 4.2 15 33 697 6 4.8 96 42 681 6 2.9 36 7 634 6 2.3 33 6 724 Location Age (y) Ht (m) RCD (mm) DBH (mm) Wood Density (kg m-3) Coatbridge 15 709 11 710 9 723 8 684 10 715 14 719 11 690 14 743 11 682 14 742 13 696 13 734 14 742 10 624 16 692 14 707 13 694 13 637 14 686 8 689 18 704 19 718 20 700 11 680 16 744 10 735 23 718 23 744 23 611 23 666 17 704 Marden et al. New Zealand Journal of Forestry Science (2021) 51:1 Page 24 TABLE A4: continued Location Age (y) Ht (m) RCD (mm) DBH (mm) Wood Density (kg m-3) Peggioh 724 756 645 669 666 696 684 705 732 727 656 730 662 679 724 733 729 607 610 739 689 683 660 Tautoro 656 780 662 679 724 733 729 607 610 739 689 683 660 Marden et al. New Zealand Journal of Forestry Science (2021) 51:1 Page 25 TABLE A5: Basic stem-wood densities, age, height, TABLE A5: Basic stem-wood densities, age, height, Root collar diameter (RCD), and RCD), and Diameter at breast height (DBH) DBH) of individual hardwood species from areas of natural regeneration at Wainuiomata (site 11), and hardwood and of individual hardwood species from areas of natural regeneration at Wainuiomata (site 11), and hardwood and softwood species from plot trials based at Gisborne (site 8) softwood species from plot trials based at Gisborne (site 8) Species Location Age (y) Height (m) RCD (mm) DBH (mm) Wood density (kg m–3) Melicytus ramiflorus Wainuiomata 12 3.7 64 34 541 Melicytus ramiflorus Wainuiomata 14 4.7 67 55 571 Melicytus ramiflorus Wainuiomata 18 5.3 114 68 446 Melicytus ramiflorus Wainuiomata 12 5.3 101 47 484 Melicytus ramiflorus Wainuiomata 10 3.9 41 28 536 Melicytus ramiflorus Wainuiomata 13 3.6 56 37 556 Melicytus ramiflorus Wainuiomata 16 7.2 66 62 423 Melicytus ramiflorus Wainuiomata 18 7.0 125 106 453 Melicytus ramiflorus Wainuiomata 11 3.3 39 24 480 Melicytus ramiflorus Wainuiomata 9 2.9 39 26 490 Melicytus ramiflorus Wainuiomata 18 6.5 125 51.5 529 Melicytus ramiflorus Wainuiomata 25 5.4 103 65 533 Melicytus ramiflorus Wainuiomata 58 9.1 350 175 496 Melicytus ramiflorus Wainuiomata 51 8.1 258 150 476 Melicytus ramiflorus Wainuiomata 37 8.8 154 115 513 Melicytus ramiflorus Wainuiomata 35 7.1 133 92 509 Melicytus ramiflorus Wainuiomata 36 7.1 178 128 495 Melicytus ramiflorus Wainuiomata 27 6.5 198 128 519 Melicytus ramiflorus Wainuiomata 41 7.5 135 96 521 Melicytus ramiflorus Wainuiomata 23 6.1 137 90 480 Melicytus ramiflorus Wainuiomata 15 6.4 84 54 429 Melicytus ramiflorus Wainuiomata 19 5.4 143 82 467 Melicytus ramiflorus Wainuiomata 19 1.7 92 69 474 Melicytus ramiflorus Wainuiomata 14 4.5 117 47 430 Melicytus ramiflorus Wainuiomata 25 5.1 154 102 444 Melicytus ramiflorus Wainuiomata 17 — 165 65 405 Melicytus ramiflorus Wainuiomata 17 5.0 130 64 465 Melicytus ramiflorus Wainuiomata 5 — 47 11 457 Melicytus ramiflorus Wainuiomata 9 4.7 77 31 464 Melicytus ramiflorus Wainuiomata 15 4.2 70 45 495 Coprosma grandiflora Wainuiomata 20 — 128 83 476 Coprosma grandiflora Wainuiomata 21 6.1 130 88 433 Coprosma grandiflora Wainuiomata 23 6.1 121 61 460 Coprosma grandiflora Wainuiomata 17 7.2 106 40 493 Coprosma grandiflora Wainuiomata 23 6.5 107 68 485 Coprosma grandiflora Wainuiomata 20 6.0 124 55 465 Coprosma grandiflora Wainuiomata 17 6.8 109 57 442 Coprosma grandiflora Wainuiomata 23 5.8 71 53 512 Coprosma grandiflora Wainuiomata 19 4.0 45 27 426 Coprosma grandiflora Wainuiomata 18 6.6 92 71 412 Marden et al. New Zealand Journal of Forestry Science (2021) 51:1 Page 26 TABLE A5: continuedTABLE A5: continued Species Location Age (y) Height (m) RCD (mm) DBH (mm) Wood density (kg m–3) Weinmannia racemosa Wainuiomata 44 6.9 152 115 544 Weinmannia racemosa Wainuiomata 38 7.6 120 97 576 Weinmannia racemosa Wainuiomata 26 6.2 89 67 573 Weinmannia racemosa Wainuiomata 69 10.2 220 143 543 Weinmannia racemosa Wainuiomata 47 10.3 160 113 551 Weinmannia racemosa Wainuiomata 30 7.7 107 80 548 Weinmannia racemosa Wainuiomata 61 6.8 150 105 614 Weinmannia racemosa Wainuiomata 51 8.9 215 108 541 Weinmannia racemosa Wainuiomata 63 10.2 158 128 538 Weinmannia racemosa Wainuiomata 46 7.7 159 120 509 Alectryon excelsus Gisborne 5 2.4 34 4 391 Alectryon excelsus Gisborne 5 2.4 34 13 426 Alectryon excelsus Gisborne 5 1.9 36 6 429 Alectryon excelsus Gisborne 5 2.5 50 18 464 Alectryon excelsus Gisborne 5 2.2 44 9 533 Alectryon excelsus Gisborne 5 2.2 44 10 478 Alectryon excelsus Gisborne 5 2.2 43 15 590 Alectryon excelsus Gisborne 5 2.5 36 11 556 Alectryon excelsus Gisborne 5 2.5 36 12 467 Alectryon excelsus Gisborne 5 2.0 28 7 500 Alectryon excelsus Gisborne 5 2.0 28 6 529 Alectryon excelsus Gisborne 5 2.7 52 17 618 Alectryon excelsus Gisborne 5 2.7 52 13 605 Dacrycarpus dacrydioides Gisborne 4 2.3 36 7 385 Dacrycarpus dacrydioides Gisborne 4 2.3 36 8 360 Dacrycarpus dacrydioides Gisborne 4 2.8 39 11 386 Dacrycarpus dacrydioides Gisborne 4 2.8 39 14 413 Dacrycarpus dacrydioides Gisborne 4 2.3 32 10 385 Dacrycarpus dacrydioides Gisborne 4 1.9 25 4 375 Dacrycarpus dacrydioides Gisborne 4 1.9 25 5 444 Dacrycarpus dacrydioides Gisborne 4 2.4 31 9 394 Dacrycarpus dacrydioides Gisborne 4 1.9 34 3 400 Dacrycarpus dacrydioides Gisborne 4 1.9 34 5 417 Dacrycarpus dacrydioides Gisborne 4 2.9 42 16 382 Dacrycarpus dacrydioides Gisborne 4 2.1 34 6 417 Dacrycarpus dacrydioides Gisborne 4 2.1 23 7 389 Dacrycarpus dacrydioides Gisborne 4 2.7 43 13 432 Dacrycarpus dacrydioides Gisborne 4 2.2 30 9 450 Dacrycarpus dacrydioides Gisborne 4 2.2 30 6 444 Dacrycarpus dacrydioides Gisborne 5 3.4 63 27 331 Dacrycarpus dacrydioides Gisborne 5 3.0 57 22 362 Marden et al. New Zealand Journal of Forestry Science (2021) 51:1 Page 27 TABLE A5: continuedTABLE A5: continued Species Location Age (y) Height (m) RCD (mm) DBH (mm) Wood density (kg m–3) Dacrycarpus dacrydioides Gisborne 5 3.0 57 13 376 Dacrycarpus dacrydioides Gisborne 5 3.1 48 18 328 Dacrycarpus dacrydioides Gisborne 5 3.1 49 21 338 Dacrycarpus dacrydioides Gisborne 5 1.6 47 12 375 Dacrycarpus dacrydioides Gisborne 5 2.4 43 13 340 Dacrycarpus dacrydioides Gisborne 5 2.9 47 15 338 Dacrycarpus dacrydioides Gisborne 5 2.9 47 13 317 Dacrycarpus dacrydioides Gisborne 5 2.9 47 11 366 Dacrycarpus dacrydioides Gisborne 5 2.7 45 17 365 Dacrycarpus dacrydioides Gisborne 5 2.6 54 18 328 Dacrycarpus dacrydioides Gisborne 5 2.6 54 16 329 Dacrycarpus dacrydioides Gisborne 5 2.7 32 13 361 Podocarpus totara Gisborne 5 2.2 43 23 359 Podocarpus totara Gisborne 5 3.0 57 27 397 Podocarpus totara Gisborne 5 3.3 60 24 362 Podocarpus totara Gisborne 5 3.2 64 33 345 Podocarpus totara Gisborne 5 3.0 50 16 375 Podocarpus totara Gisborne 5 2.6 50 18 383 Podocarpus totara Gisborne 5 2.4 49 17 452 Podocarpus totara Gisborne 5 2.8 41 16 526 Podocarpus totara Gisborne 5 3.2 49 24 436 Agathis australis Gisborne 5 1.5 24 7 318 Agathis australis Gisborne 5 1.5 28 9 286 Agathis australis Gisborne 5 1.6 21 8 294 Agathis australis Gisborne 5 1.5 19 5 250 Agathis australis Gisborne 5 1.7 20 13 210 Agathis australis Gisborne 5 1.9 25 10 220 Agathis australis Gisborne 5 1.6 26 10 268 Agathis australis Gisborne 5 1.8 24 18 326 Dacrydium cupressinum Gisborne 5 2.3 34 8 484 Dacrydium cupressinum Gisborne 5 2.2 36 10 463 Dacrydium cupressinum Gisborne 5 2.2 36 8 484 Dacrydium cupressinum Gisborne 5 2.0 40 9 417 Dacrydium cupressinum Gisborne 5 2.0 40 6 385 Dacrydium cupressinum Gisborne 5 1.5 34 11 482 Dacrydium cupressinum Gisborne 5 2.3 41 12 471 Dacrydium cupressinum Gisborne 5 2.5 44 13 483 Dacrydium cupressinum Gisborne 5 2.4 38 6 385 Dacrydium cupressinum Gisborne 5 2.4 38 13 462 Dacrydium cupressinum Gisborne 5 1.9 39 8 435 Dacrydium cupressinum Gisborne 5 2.2 30 11 455 Marden et al. New Zealand Journal of Forestry Science (2021) 51:1 Page 28 Species Location Age (y) Height (m) RCD (mm) DBH (mm) Wood density (kg m–3) Dacrydium cupressinum Gisborne 5 2.1 42 10 424 Dacrydium cupressinum Gisborne 5 2.1 42 8 414 Prumnopitys ferruginea Gisborne 5 1.5 11 2 333 Prumnopitys ferruginea Gisborne 5 1.6 30 5 429 Prumnopitys ferruginea Gisborne 5 1.7 17 3 286 Prumnopitys ferruginea Gisborne 5 1.5 25 3 250 Prumnopitys ferruginea Gisborne 5 1.9 28 6 500 Prumnopitys ferrugínea Gisborne 5 1.5 15 2 333 Prumnopitys ferrugínea Gisborne 5 1.9 24 7 500 Vitex lucens Gisborne 4 1.9 44 8 302 Vitex lucens Gisborne 4 1.6 45 5 145 Vitex lucens Gisborne 5 1.8 95 8 227 Vitex lucens Gisborne 5 2.2 95 13 354 Vitex lucens Gisborne 5 2.2 95 10 340 Vitex lucens Gisborne 5 2.2 95 13 324 Vitex lucens Gisborne 5 3.3 82 34 335 Vitex lucens Gisborne 5 3.2 84 40 348 TABLE A5: continuedTABLE A5: continued