7th HUON SEMINAR ACHIEVING VISION 2050 THROUGH HIGHER EDUCATION, RESEARCH, SCIENCE & TECHNOLOGY

November 13th to 14th 2013, Papua New Guinea University of Technology, Lae, Papua New Guinea

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HS7-2013-019

Assessment of Vulnerability and Impacts of Climate Change on Forests in

Papua New Guinea

Eko Maiguo1 2, Rodney Keenan1, Craig Nitschke1

1Melbourne School of Land and Environment, University of Melbourne, Melbourne.

2Department of Forestry, PNG University of Technology, Lae

Emails: emaiguo@student.unimelb.edu.au; rkeenan@unimelb.edu.au; cnitschke@unimelb.edu.au

ABSTRACT The vulnerability and impacts of forests in Papua New Guinea (PNG) due to climate change were assessed using Tree and Climate Assessment (TACA) model, which predicts the suitability for plants to regenerate and grow under varying climate scenarios. Twenty key tree species were tested using the secondary sourced climate and soil parameters from 15 sites in PNG. The results showed that by the year 2080 the lowland tree species are expected to shift to high altitudes, leading to alterations in species composition. It is predicted that sites between 800 m to 2000 m in altitudes to be rich in plant species, while shrinkage in species composition and even extinction in the lowland. It was also observed that Nothofagus and conifers currently found in the upper montane zone are likely to have narrow chances of migrating upslope as treeline is predicted to be at about 3500 m elevation. Species which have similar ecological niches to the 20 tree species used in this study are expected to behave comparably. The predicted climate change is likely to cause negative impacts on the species composition and distribution of forests of PNG which are expected to affect the current states of national economy, biodiversity and community dependency for goods and services. Therefore, tree planting and effective natural forest conservation should be undertaken in PNG to ensure sustainable forestry that supports ecosystems, national economy and community livelihood under the changing climate. Keywords: adaptation and mitigation, climate change, Papua New Guinea, TACA model, tropical forests.

1.0 INTRODUCTION Papua New Guinea (PNG) is a geographically complex country comprised of a number forest and vegetation types [1], which are floristically rich in species, harbouring about 7.5% of world’s plant diversity, about 15,000-20,000 plant and about 2,000 trees of which 400 are currently used as commercial timber trees [2]; some species are endemic to PNG [3]. PNG is regarded as having some of the most extensive areas of tropical forests in the world [4]; some areas still unexplored [5]. The distribution of these forests are governed by temperature and rainfall [6, 1] with the main factors that influence climatic patterns being the northwest and southeast monsoons, South Pacific Convergence Zones, and El Nino [7]. Future climate change predictions for PNG suggest a warmer and wetter climate, with the projected temperature increases from 0.7oC to 0.9oC by the 2030s and 1.9oC to 2.7oC in 2080s, and increases of precipitation by 9% by the 2030s and 19% in 2080s [7]. The predicted change in climate is expected to have considerable impacts on PNG’s forests. The expected responses of forest ecosystems to climate change include changes in phenological patterns, growth,

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morphology, delay or absence of germination and seedling establishment, migration of species to new ranges, invasion of exotic species, outbreaks of pests and diseases and species extinction [8]. Changes in climatic conditions, particularly temperatures and precipitation may not only influence the mature plants, but germination and regeneration as well [9]. These early phases of plants can be adversely affected by the harsh climatic and other environmental conditions. Thus, sensitivity of species during establishment can be effective indicators for detecting the impacts of climate change. 2.0 METHODOLOGY 2.1 TACA Model This study assessed the vulnerability and impacts of climate change on forests in PNG, using a mechanist modeling approach. The model to be used in this research is tree and climate assessment model (TACA) which was developed and used in British Columbia (BC) forests [10] and South East Australia [11]. The model predicts the suitability for plants to regenerate and grow under varying climate scenarios. 2.2 Study Area The study comprised an altitudinal and latitudinal transect across PNG. A total of 15 weather stations selected were between the northern coastline in Wewak and Madang ascending through Mount Wilhelm and descending to the southern coastline of Daru. Figure 1 shows details of the selected sites. The numbers in the map relate to the order of the stations in the graph.

Figure 1a: Location of selected sites Figure 1b: Cross-section profile 2.3 Biophysical parameters Relevant biophysical parameters for this study were trees species, climate and soils. Details of each data are provided below.

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2.2.1 Selected tree species Twenty tree species were selected are summarized in Table 1. They were selected based on the commercial importance [12], historical adaptability [13], representative of altitudinal zones [2] and availability of botanical and ecological information [2, 14] Table 1: Details of selected tree species Trade Name Scientific Name Ecological Zone Altitude (m)

Mersawa Anisoptera thurifera Blume Lowland 300-1000 Hoop Pine Araucaria cunninghamii Aiton Mid montane 1500-2700 Klinkii Pine Araucaria hunsteinii K.Schum Mid montane 1500-2700 Calophyllum Calophyllum papuanum Lauterb Mid montane 1500-2700 Oak PNG Castanopsis accuminatissima (Bl.) Mid montane 1500-2700 Podocarp Dacrycarpus imbricatus Blum Upper montane 2700-3200 Dacrydium Dacrydium novoguineense Gibbs Upper montane 2700-3200 Ebony Diospyros hebecarpa Benth Lowland 300-1000 Walnut Dracontomelon dao Merr. & Rolfe Lowland 300-1000 Wau Beach Elmerrillia tsiampacca (L.) Dandy Mid montane 1500-2700 Kamerere Eucalyptus deglupta Blume Lowland 2700-3200 Kwila Intsia bijuga Kuntze Lowland 300-1000 Mango Mangifera minor Blume Lowland 300-1000 Beech Nothofagus carrii Steenis Upper montane 2700-3200 Erima Octomeles sumatrana Miq. Lowland 300-1000 Pencil cedar Palaquium galactoxylum (F.Muell.) Lowland 300-1000 C-top-Pine Phyllocladus hypophyllus Hook f. Upper montane 2700-3200 Brown Pine Podocarpus neriifolius D. Don Upper montane 2700-3200 Taun Pometia pinnata J.R.Forster Lowland 300-1000 Rosewood Pterocarpus indicus Wild Lowland 300-1000 2.3.2 Climatic parameters Climatic parameters used in TACA model were minimum temperature, maximum temperature, precipitation, radiation, drought, frost, growing degree day and projected climate variables. The use of each parameter in the model is detailed in the subsequent sub-headings. 2.3.2.1 Temperature and precipitation Mean annual climate data for PNG were obtained from [6]. Information on daily maximum and minimum temperatures, precipitation and radiation were gathered from [7] for the selected sites which are shown in Figure 1. Apart from Port Moresby and Madang, daily climate data for all weather stations in PNG were not available. Due to lack of daily climate data, Madang was used as base weather station to extrapolate daily climate at all other weather stations. All regression models were developed based on relationships for temperature and precipitation between Madang and all other weather stations. All regression models were significant (P<0.05) and 95% confidence interval for temperature was (5.4, 47.20) and for precipitation was (46.3, 256.8). Climatic change inputs were from [7].

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2.3.2.2 Radiation The solar radiation of 160 m W-h/cm2 per year based on [6] was used for all the weather stations. 2.3.2.3 Annual heat moisture index (AHMI) Annual heat moisture index is also called the moisture index and it is calculated as: AHMI = Mean annual temperature (MAT) + 10/Annual Precipitation/1000. (1) 2.3.2.4 Growing degree day (GDD) Growing degree days (GDD) is a way of allocating heat values to each day, and is added to give an estimation of the amount of seasonal growth of plants [15]. Equations for calculating GDD are below: GDD = maximum temperature (Tmax) + minimum temperature (Tmin)/2 – base temperature (Tbase) (2) Maximum GDD = (Tmax) + Tmin)/2 –Tbase)*(365 days * 1.25) (3) Minimum GDD = (Tmax) + Tmin)/2 –Tbase)*(365 days * 0.75) (4) Base temperatures (Tbases) in this study used are shown below:

i. Low altitude species: Tbase of 10oC; ii. Mid altitude species: Tbase of 5oC; and iii. High altitude species: Tbase of 3oC.

Annual mean maximum and minimum temperatures from [6] were used to calculate GDD. 2.3.3 Soil types and parameters 2.3.3.1 Soil types

Major soil types of PNG based on [16] used were: Low altitude: Tropaqualf and Hapuldoll; Mid altitude: Eutropepts; and High altitude: Drytropepts and Eutropepts

2.3.3.2 Soil parameters Soil parameters used were soil texture, soil rooting depth and coarse fragment content. Three soil textures used were clay, clay loam and sandy clay loam. 2.4 Prediction periods

The TACA model was used to predict changes in forests in PNG for the time periods of current, 2020s, 2050s and 2080s.

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2.5 Data analysis Data analysis was done using the model output and the statistics using student’s “t test” from the Excel Microsoft to compare regeneration probabilities of species at different sites between the current and 2080s. Prior to performing “t tests”, all data were transformed into logarithm as they were in probabilities. The transformations were made using formula given below: Normal value = log(y+0.005)/ (1-y+0.005). (5) 3.0 RESULTS For brevity, selected tree species were summarised into one of three forest types: lowland, mid altitude and high altitude forests. The TACA model provides scores from 0 to 100% which represent the ability of a species to regenerate and grow given the climate and soil conditions modelled. 3.1 Lowland species Walnut, Kamarere, Erima, Pencil cedar, Taun and Rosewood are lowland species found along the valley floors and on the lower valley sides, while Mersawa, Ebony, Kwila and Mango occur along the well-drained hill tops and in the shallow soils on the ridge tops [1]. The graph below shows the trends of regeneration and distrubtion of these species at various sites over the time period from the current to 2080s.

Figure 2: Regeneration of lowland tree species between current and 2080s The results suggest that by the 2080s lowlnd tree species have an 8% chance of regenerating in their current sites as indicated by the probabilities of Madang, Wewak and Daru. The results also suggested that Eram which is about 268 m altitude seems to have conditions ideal for the regeneration of the lowland tree species at present and also by the 2080s, as this site experienced less soil moisture loss under the predicted climate change. It was further observed that by the 2080s lowland tree species are likely to migrate into higher altitude areas such as Kundiawa and Hagen which are not within their current natural range.

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3.2 Mid altitude species

Figure 3: Regeneration of mid altitude tree species between current and 2080s The mid altitude species were Calophyllum, Wau Beach, Castanopsis, two Araucrias and Nothofagus. They are currenly found in the altitudinal range between 268 m (Eram) and 2500 m (Wabag). The results showed that in future these species are unlikely to regenerate and occur in the areas below 800m (Koinambe) by 2080s, but they are likely to shift to 2500 m altitude (Denglagu), which they are currently absent. 3.3 High altitude species

Figure 4: Regeneration of high altitude tree species between current and 2080s The model showed that, at the moment, conifers namely Dacrycarpus, Dacrydium and Phyllocladus are found in areas between 2500 m (Denglaugu) and 3500 (Mt Giluwe). However, by the 2080s, the regeneraion of these species are likely to be only in areas about 3500 m elevation which should be treeline of PNG.

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3.4 Species distribuition trends btween now and 2080s

Figure 5a: Current forest type Figure 5b: Distribution of forest type by 2080s

dsitribution Figure 5 shows the distribution of species between now and 2080s. Figure 5b illustrates that by 2080s, lowland tree species are likely to have only 8% chance of regenerating in current sites below 800 meters, but they are expected to shift to about 1700 m altitude at which they are currently absent. The mid altitude tree species are expected to regenerate and occur between 800 m to 2500 m elevation suggesting they may be able to expand their range witth suffering a climate driven contraction a lower elevations. The high altitude conifers and Nothofagus were found to be the most vulnerable to climate change with a possible contraction in their range from 1900 m to 2500 meters and the inability to increase their range above 3500 m due to the occurrence of frosts and drought as result of the thin soils on Mount Wilhelm. The results suggest the encroachment of the studied tree species on the treeline of Mount Wilhelm will be limited underr the range of climate change used in this study. 4.0 DISCUSSION 4.1 The vulnerability and impacts of climate change on forests 4.1.1 Tree Species

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Our analysis suggested that there is a potential for a shift in species composition across PNG as the result of predicted climate change. Lowland species will likely experience more favourable for regeneration and growth at higher altitudes as the climate change though they may suffer declines in regeneration and growth below 800 meters. Our results suggest that lowland species may contract from lower elevations and migrate to higher elevation which is similar to predictions for South America tropical forests [17]. It is anticipated that species such as Ebony and Pencil Cedar however, may be unable to migrate successfully as they are shade tolerant species [18] that may not be able to adapt or migrate fast enough under the rapid rate that climate change is predicted to occur at. These two species have relatively large seeds which will likely constrain migration, in comparison with tree species which have small seeds that are easily dispersed by wind. Even if these species are successful in dispersal, our results suggest that regeneration will be confined to sites with deep soils as those found in gullies [1]. The most vulnerable species were found to be the high altitude species, particularly the conifers and Nothofagus which are already confined to upper montane to subalpine zones. These species are currently at the tree line and with their inability to expand above the current treeline under a warmer climate. It is likely they will suffer contractions in their ranges as mid elevation species become established above 2000 meters. Past histories have revealed however that these species have adapted well through changes in the climatic conditions [14], suggesting they may able to adapt to the changing climate in the absence of disturbance or competition from other species. 4.1.2 Forest types Two forest types predicted to be vulnerable to the impacts of climate change are lowland and upper montane. The model predicted changes in the climatic conditions may cause migration of species from the lowland to the high altitude. The results suggested that the species which are currently dominant in the lowland will have about an 8% chance of being able to regenerate there by the 2080s. It is likely that the species with the similar environmental niches to the ones being used this study are expected to migrate as well, leading to likely alteration on the species composition in the lowland forests [19]. On the other, secondary forest species are likely to be less affected by climate change; therefore, these species may become more dominant in the lowland forests as have been found in Amazonian rainforests [20]. Upper montane forests are also vulnerable to climate change. This forest is rich in species and exceptionally high endemism, and a great sensitivity to climate. Global climate change threatens all ecosystems through temperature and rainfall changes, with a typical estimate for altitude shifts in the climatic optimum for mountain ecotones of hundreds of meters by the time of temperature increases. This suggests complete replacement of many of the narrow altitude range cloud forests by lower altitude ecosystems and even into extinction. However, the upper montane forest will also be affected by other climate changes, in particular changes in cloud formation [21]. A number of global climate models suggest a reduction in low level cloudiness with the coming climate changes. This will lead to biodiversity loss, altitude shifts in species' ranges and subsequent community reshuffling, and possibly forest death [22]. In this ecosystem, changing climate is likely to cause forest species’ ability to regenerate and migration will be slim. 4.2 Consequences of changing forest types 4.2.1 Biodiversity

PNG is highly regarded for its biodiversity richness [3, 5]. Forests are important habitats for biodiversity in PNG [23] and [24] describes critical habitats and biodiversity values that are threatened by development or natural disaster and damage or loss would have a profound implication on the stability

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and viability of local ecosystems [25]. The model suggested that the current states of forests are likely to change in the future and this is expected to have implications on biodiversity. It is expected that some biodiversity will shift correspondingly with the shifts in plant species. However, organisms which have very specific natural range may suffer severely or even become extinct. 4.2.2 Tree species preferences for the commercial and local consumption purposes Twenty tree species used in this study are currently classified as having high commercial values. Hardwoods are in groups 1 and 2 of the export list [12], while Ebony and conifers are banned from round log export, but they can be processed domestically. Currently, PNG depends almost entirely on natural forests for the income generation and wood and timber consumption [26]. As lowland sites become warmer in the future, causing trees to shift to high altitudes; it is most likely that preferences on the use of tree species are likely to change. It is doubtful which tree species may be present in the lowland in the future. It could be possible that tree species which are currently considered as minor timber trees [27] and lesser known timber species [28] might become major dominant commercial timber trees. Even secondary forest trees such as Anthocephalus chineensis and Canaga odorata may become commercially useful as they are light demanding species [29] and can adapt to warmer conditions. 4.2.3. Forest dependent communities Local people who depend on forest resources are vulnerable to the changes in forest ecosystems due to climate change. Approximately 85% of the people of PNG live in rural areas depend on forests for income generation and timber [30] and other social economic and cultural uses of forests [31] will be affected. Impacts of changing climate have already been experienced by local communities and the situation is expected to worsen if climate change continues [31]. According to our results, communities in lowland and high latitudes may suffer due to changes in species composition while communities in mid altitude will likely to benefit from the species richness due to the migration of species from lowland. 4.3 Adaptation and mitigation To help the forests of PNG adapt to and mitigate the impacts of climate change, both tree planting and conservation of natural forests are essential. In over 50 years of commercial forestry, PNG has now planted only about 70,000 hectares of forest plantations. This reflects that the country over the years has depended heavily on natural forests. Under climate change, the future use of natural forests is under threat. Therefore, tree plantings in small, medium and large scales are needed. The Papua New Guinea Forest Authority (PNGFA) has formulated reforestation policy and implementation program, which identifies that the forest resource of PNG is depleting at a faster rate and the country is a signatory to the Kyoto Protocol for carbon sequestration under the clean development mechanism (CDM) for planting trees for climate change issue [32]. However, still today, tree planting is not yet effective in PNG. Under climate change, growth of trees is expected increase with increases in solar radiation, air temperature and increase in atmospheric carbon dioxide (CO2) [33]. Thus tree planting seems to a sound option for both ecological and socio-economic reasons under climate change. PNG’s efforts in the management of forests for conservation purposes have been poor over the years. Burning of PNG’s first National Park -McAdam National Park in 1997 and 1998 El Nino fires is an indication of PNG’s perception about conservation efforts [34]. A number of conservation areas have not been managed and even local people who are the owners of forests do not prefer to allocate their forest land for conservation as benefits offered are not attractive.

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In recent times, developed nations have shown willingness to provide financial support to developing nations in order to protect biodiversity. This is in the form of payment for environmental services (PES) [35], and there are also funds available for allocation of forests for reduce emissions from deforestation and forest degradation (REDD) projects as well [36]. Opportunities are available to PNG to benefit if attractive gains are offered to local communities. Currently, areas identified for REDD+ projects are in Sandaun, Eastern Highland, West New Britain and Milne Bay Provinces and are only in the northern part of PNG. The southern part of PNG has some of the only pristine lowland rain forests in the world [4] and also has areas of high biodiversity values [5] which need to be considered as well. Attempts should be made to maintain forest biodiversity and ecological functions, with emphasis on protecting climatic refugia and providing connectivity [37]. Conservation to protect As indicated by the results that species contraction particularly in lowland is expected to alter due climate change, thus future states of natural forests will be under threat. Tree planting is necessary to ensure forest resources are maintained and protected. Tree planting is also necessary to enhance, create or link habitat refugia. 5.0 CONCLUSIONS The results of our study suggest that predicted climate change is likely to have impacts on the species composition and distribution of PNG. The future use of forests under changing climate highlights vulnerability and resilience as all modeled species were able to be persisting. Some species, in particular, species located in a mid elevation may benefit under climate change with expansion to higher elevations and the maintenance of regeneration at lower elevations. The mid elevation species may “March” and “Lean” in response to climate change [38]. The high elevation species appear to be the most sensitive as they are predicted to contract from lower elevations but only “Lean” upslope versus “March” above the current treeline. The lowland species may suffer contractions at lower elevations but should “March” upslope. The major implications of species shifts are on PNG economy, local people’s dependence on forests and biodiversity. Currently, industries and communities are relying on timber and wood materials from natural forests, and these resources will be impacted by climate change. Tree planting and effective natural forest management for REDD+ projects and biodiversity conservation should be undertaken in PNG to reduce the impacts of a changing climate. REFERENCES [1] Paijmans, K. New Guinea Vegetation, Elsevier, Amsterdam, The Netherlands, 1975. [2] Havel J.J. Training Manual for Forestry College, Vol. 3/2 Botanical Taxonomy, Department of Forests, Port Moresby, 1977 [3] Sekhran, N. and Miller, S., (Eds). Papua New Guinea Country Study on Biological Diversity, Department of Environment and Conservation, Port Moresby, 1994. [4] Conservation International. A Biological Assessment of the Lakekamu Basin, Papua New Guinea, Rapid Assessment Program, Conservation International, Washington DC, 1998. [5] Miller, S., Hyslop, E., Guy, K., and Burrows, I. Status of biodiversity in Papua New Guinea. In Sekhran, N. and Miller, S., (Eds). Papua New Country Study on Biological Diversity, Department of Environment and Conservation, Port Moresby, 1994. [6] McAlphine, J.R. and Keig, G.G. with Falls, R., The Climate of Papua New Guinea, Commonwealth Scientific Industrial Research Organization with Australian National University Press, Canberra, 1983. [7] Papua New Guinea National Weather Service. Current and future climate of PNG,

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[29] Edwin, P. Investigation of processing characteristics of hardwood timber from secondary forests in PNG, Master of Wood Science Thesis, Department of Forest and Ecosystem Science, Melbourne School of Land and Environment, The University of Melbourne, 2011. [30] Yosi, C., Keenan, R.J, and Fox J.C. Forest dynamics after selective harvesting in Papua New Guinea, Forest Ecology and Management 262 (2011). [31] Osman-Elasha, B., Parrotta, J., Adger, N., Brockhaus, M., Colfer, P.C.J., Sohngen, B., Dafalla, T., Joyce, L.A., Nkem, J. and Robledo, C. 2009. Future Socio-Economic Impacts and Vulnerabilities. In Seppälä, R., Buck, A. and Katila, P. (Eds). Adaptation of Forests and people to climate change – a global assessment report Prepared by the Global Forest Expert Panel on Adaptation of Forests to Climate Change, International Union of Forest Research Organizations, Vienna, Austria, 2009. [32] PNGFA. National Reforestation Policy, Ministry of Forests, Port Moresby, 2005. [33] Lloyd, J. and Farquhar, G.D. Effects of rising temperatures and [CO2] on the physiology of tropical forest trees, Philosophical Transactions of Royal Society Vol. 14/1 (2007). [34] Orsak, L. and Balun, L. El Nino drought destruction: the death of Papua New Guinea’s McAdam National Park, A newsletter for Conservation Areas in the Pacific, South Pacific Regional Environment Program (SREP), Apia, Samoa, 1999. [35] Meizlish, M. & Brand, D. 2008. Developing Forestry Carbon Projects for the Voluntary Carbon Market. In: Streck, C., O’Sullivan, R., Janson-Smith, T. & Tarasofsky, R. (Eds). Climate Change and Forests. Emerging Policy and Market Opportunities., Brookings Institution Press, Washington, DC, 2008.. [36] Portela, R., Wendland, K.J. and Pennypacker, L.L. The Idea of Market-Based Mechanisms for Forest Conservation and Climate Change. In Streck, C., O’Sullivan, R., Janson-Smith, T. & Tarasofsky, R. (Eds.). Climate Change and Forests. Emerging Policy and Market Opportunities. Chatham House London and Brookings Institution Press, Washington, DC, 2008. [37] Hannah, L., Midgley, G.F. and Millar, D. Climate change-integrated conservation strategies, Global Ecology & Biogeography Vol.11 (2002). [38] Breshears, D.D., Huxman, T.E., Adams, H.D., Zou, C.B. and Davison, J.E. Vegetation synchronously leans upslope as climate warms, PNAS Vol. 105/33 (2008).