Remote Sensing-Based Assessment of the 2005–2011 Bamboo Reproductive Event in the Arakan Mountain Range and Its Relation with Wildﬁres

remote sensing

Article Remote Sensing-Based Assessment of the 2005–2011 Bamboo Reproductive Event in the Arakan Mountain Range and Its Relation with Wildﬁres

Francesco Fava 1,* and Roberto Colombo 2

1 International Livestock Research Institute, P.O. Box 30709, Nairobi 00100, Kenia 2 Remote Sensing of Environmental Dynamics Lab., Dept. of Earth and Environmental Sciences, University of Milano-Bicocca, Piazza della Scienza 1, Milano 20126, Italy; [email protected] * Correspondence: [email protected]; Tel.: +254-20-422-3408

Academic Editors: Krishna Prasad Vadrevu, Rama Nemani, Chris Justice, Garik Gutman, Ioannis Gitas, Clement Atzberger, Lars T. Waser and Prasad S. Thenkabail Received: 26 July 2016; Accepted: 11 January 2017; Published: 18 January 2017

Abstract: Pulse ecological events have major impacts on regional and global biogeochemical cycles, potentially inducing a vast set of cascading ecological effects. This study analyzes the widespread reproductive event of bamboo (Melocanna baccifera) that occurred in the Arakan Mountains (Southeast Asia) from 2005 to 2011, and investigates the possible relationship between massive fuel loading due to bamboo synchronous mortality over large areas and wildfire regime. Multiple remote sensing data products are used to map the areal extent of the bamboo-dominated forest. MODIS NDVI time series are then analyzed to detect the spatiotemporal patterns of the reproductive event. Finally, MODIS Active Fire and Burned Area Products are used to investigate the distribution and extension of wildfires before and after the reproductive event. Bamboo dominates about 62,000 km2 of forest in Arakan. Over 65% of the region shows evidence of synchronous bamboo flowering, fruiting, and mortality over large areas, with wave-like spatiotemporal dynamics. A significant change in the regime of wildfires is observed, with total burned area doubling in the bamboo-dominated forest area and reaching almost 16,000 km2. Wildfires also severely affect the remnant patches of the evergreen forest adjacent to the bamboo forest. These results demonstrate a clear interconnection between the 2005–2011 bamboo reproductive event and the wildfires spreading in the region, with potential relevant socio-economic and environmental impacts.

Keywords: bamboo; reproduction; wildﬁres; MODIS; Arakan; pulse event; food security; biodiversity conservation

1. Introduction The important role of pulse ecological events, defined as infrequent, large-magnitude, and short-duration events of increased resource availability, on regional and global biogeochemical cycles has been increasingly acknowledged in recent literature [1]. In this context, mast flowering, the massive and synchronized flowering and fruiting of a plant species across large areas, can be considered a typical pulse event, potentially inducing a vast set of cascading ecological effects [2]. Most masting plant species are iteroparous (i.e., they flower several times during their life cycle), and have a relatively short intermast interval (3–7 years) [3]. A noticeable exception is represented by several woody bamboo species distributed in subtropical and temperate evergreen or deciduous forests [4], which are semelparous (i.e., they flower once and die) and have typical intermast intervals between 20 and 60 years [5]. These bamboo species are characterized by aggressive rhizomatous growth and develop large clonal clumps that may cover hundreds of square meters [6].

Remote Sens. 2017, 9, 85; doi:10.3390/rs9010085 www.mdpi.com/journal/remotesensing Remote Sens. 2017, 9, 85 2 of 14

A large-scale mast flowering event of the bamboo species Melocanna baccifera has been reported starting from 2005 in the Arakan mountain range, which spans about 1000 km parallel to the eastern edge of the Bengali gulf in Mainland Southeast Asia. Widespread and synchronous bamboo flowering was described in several locations in Mizoram and Manipur (India), East Chittagong (Bangladesh), Chin and Rakhine (Myanmar). Following the bamboo flowering and fruiting, there were extensive reports of rodent outbreaks (also known as “rat floods”), causing serious damage to rice and other crops, and leading to food insecurity across the region [7,8]. Similar events, locally called “mautam”, were already documented in 1863, 1911, and 1959, with an approximate repeating cycle of 48 years [9]. Despite the wide environmental and food security significance of this event, most scientific and public media attention has been addressed towards the rodent outbreak dynamics and impacts, while studies on the spatial and temporal patterns of the reproductive events and other possible large scale ecological consequences have been lacking. Considering the socio-economic centrality of the tropical and sub-tropical forests for extremely vulnerable local communities [8], as well as their high value for biodiversity conservation [10], a full understanding of the impacts of this pulse event is essential for future land management and conservation planning. Previous research suggested that the mass mortality of bamboo after fruiting could favor fire ignition and propagation as a result of synchronous and widespread fuel load [11,12]. This consideration was also one of the major arguments to sustain an explanation, known as ‘fire-cycle hypothesis’, for the highly specific reproductive strategy of mast flowering and semelparity in bamboos [11]. This hypothesis stimulated a strong debate [13,14], but only a few studies addressed the possible linkage between mast flowering events and fire using empirical data, and most of them were only at the local scale [15–17]. Long time series of satellite remote sensing data are now widely available for regional and continental scale vegetation monitoring, and recent studies have demonstrated their potential for mapping bamboo flowering, fruiting, and mortality in the Amazon [18]. In addition, a number of algorithms and operational remote sensing products are now available for regional monitoring of active fires and burned area dynamics [19,20]. This opens a unique opportunity to study the interaction between bamboo mast flowering and wildfires during regional scale pulse events. Based on these considerations, this study aims at analyzing time series of satellite data and derived burned area/active fire products in the Arakan region to assess the spatial and temporal patterns of the bamboo reproductive event, and to investigate possible impacts on wildfire regime. Specifically, the following scientific questions are addressed: (a) What is the extent and geographic distribution of the bamboo-dominated forest in Arakan? (b) Which spatial and temporal dynamics characterized the bamboo reproductive event? (c) Was the wildfire regime impacted by the bamboo reproductive event? Given the reported dramatic effects on food security associated with the rodent outbreaks, which followed this reproductive event, the production of regional maps of the bamboo-dominated forest and of the dynamics of the reproductive event would provide key information not only to understand the ecology of the event, but also for planning and coordinating future interventions to support local communities and policy makers in adopting strategies to prevent crop damage and food shortage. Moreover, under the hypothesis that wildfires could increase because of the enormous fuel load generated by the synchronous mortality of bamboo, this could represent another important consequence of the masting event, which so far has been poorly documented but poses a serious threat to local populations and to ecosystems of high conservational value.

2. Materials and Methods

2.1. Study Area and Field Survey The study area is located in the Arakan mountain range, which spans for about 1000 km parallel to the eastern edge of the Bengali gulf from Cape Negrais, west of the Irrawaddy Delta, and the Remote Sens. 2017, 9, 85 3 of 14 southern Manipur State of India, touching Myanmar (Rakhine and Chin), Bangladesh (Chittagong), and India (Mizoram and Manipur) (Figure 1). Geologically, the Arakan mountain region belongs to the northern portion of the Burmese-Java arc of the Himalaian system of folding, and it is characterized by Cretaceous-Tertiary flysch sediments with basalt and ultramafic deposits and metamorphic rocks. The terrain of the region is rugged, with steep slopes and elevation reaching over 3000 m (Mt. Victoria). The region is characterized by a tropical monsoon climate, with Remoteprecipitation Sens. 2017 concentrated, 9, 85 between the months of May and October. The mountains act as a barrier3 of 14 for the southwest monsoon rains, generating a strong rainfall gradient between the western (over 3000 mm)southern and Manipureastern State(1000–3000 of India, mm) touching slopes. Myanmar This grad (Rakhineient is and also Chin), reflected Bangladesh in the (Chittagong), vegetation distribution,and India (Mizoram which shifts and Manipur) from tropical (Figure evergreen1). Geologically, forest in the the Arakan west to mountain moist upper region deciduous belongs toforest the innorthern the center portion and of dry the deciduous Burmese-Java forests arc ofin the the Himalaian east. Anthropic system activities of folding, and and intensive it is characterized agriculture by exertCretaceous-Tertiary strong pressure flysch on the sediments environment, with basalt especially and ultramaficon the east deposits side of the and region. metamorphic At the same rocks. time, The shiftingterrain ofcultivation the region is iscommon rugged, everywhere. with steep slopes and elevation reaching over 3000 m (Mt. Victoria). The regionBamboo is species, characterized such as by Melocanna a tropical baccifera monsoon, Bambusa climate, polimorpha with precipitation, and Bambusa concentrated tulda, are widespread between inthe the months study of area. May Bamboo-dominated and October. The mountains forests have act not as abeen barrier mapped for the as southwest an independent monsoon class rains, in previousgenerating land a strong cover rainfall maps gradientof the region between (e.g., the [21–25]), western (overas they 3000 are mm) generally and eastern included (1000–3000 in broader mm) forestslopes. cover This gradientclasses. Although is also reflected bamboo in thecan vegetation be associated distribution, with other which species shifts in fromdegraded tropical forests evergreen or as partforest of in the the westdeciduous to moist and upper evergreen deciduous forest forest understory, in the center very and large dry and deciduous almost forests pure inMelocanna the east. Anthropicbaccifera stands activities are common and intensive in the agriculture Arakan Mountains, exert strong especially pressure in on the the southern environment, portion especially of the area on (Chinthe east and side Rakhine) of the region. [26]. At the same time, shifting cultivation is common everywhere.

Figure 1. Study area. On the left, the study area border is evidenced on the mainland South East Asia Figure 1. Study area. On the left, the study area border is evidenced on the mainland South East Asia topographic map. On the right, the main administrative regions included in the study area are topographic map. On the right, the main administrative regions included in the study area are reported reported (i.e., Rakhine and Chin-Myanmar, Chittagong-Bangladesh, Mizoram-India). (i.e., Rakhine and Chin-Myanmar, Chittagong-Bangladesh, Mizoram-India). To support satellite image analysis and interpretation, a field survey was carried out in 2013 in SouthernBamboo species,Rakhine such (i.e., as MelocannaRakhine Yoma baccifera Elepha, Bambusant polimorpharange) to, andcollectBambusa ground tulda information, are widespread on bamboo-dominatedin the study area. Bamboo-dominated forest areas. The forests remoteness have not of beenthe area mapped did asnot an allow independent a systematic class invalidation previous study,land cover but mapsqualitative of the regionobservations (e.g., [21 along–25]), transects as they are crossing generally the included mountain in broader range provided forest cover evidence classes. Althoughof very large bamboo areas candominated be associated by young with Melocanna other species baccifera in degraded plants forestswith scatte or asred part trees, of the which deciduous could beand easily evergreen discriminated forest understory, as an independent very large vegetation and almost cover pure class.Melocanna In addition, baccifera in allstands bamboo-dominated are common in the Arakan Mountains, especially in the southern portion of the area (Chin and Rakhine) [26]. To support satellite image analysis and interpretation, a field survey was carried out in 2013 in Southern Rakhine (i.e., Rakhine Yoma Elephant range) to collect ground information on bamboo-dominated forest areas. The remoteness of the area did not allow a systematic validation study, but qualitative observations along transects crossing the mountain range provided evidence of very large areas dominated by young Melocanna baccifera plants with scattered trees, which could be easily discriminated as an independent vegetation cover class. In addition, in all bamboo-dominated Remote Sens. 2017, 9, 85 4 of 14 areas that were directly surveyed, the reproductive event was reported and evidence of recent fires was found (i.e., burned bamboo stubbles) below the young bamboo canopy. This was confirmed further by interviews with local farmers, reporting the bamboo reproductive event and subsequent large fires.

2.2. Bamboo Forest Mapping The identification of forests dominated by Melocanna baccifera, as well as other land cover typologies, has been performed by integrating different cartographic products and satellite imagery. The forest map of South East Asia [21,22], obtained from classification of SPOT VEGETATION images acquired between 1998 and 2000 with 1 km geometric resolution, was used as a reference for the forest type classification of the study area before the bamboo reproductive event. Since the forest map legend includes bamboo forest in a broader class (i.e., “Evergreen wood and shrubland and regrowth mosaics”), the Landsat GEOCOVER mosaic 2000 product [27] was used to refine the bamboo-dominated forest classification by visual interpretation of the mosaic at 1:250,000, exploiting the distinct spectral features of bamboo mature forests [18] (cf. Figure S1). Finally, the potential distribution map of the bamboo species [28,29] was used to define the border for the area dominated by Melocanna baccifera. Overall, four vegetation cover classes were used for the purposes of this study: bamboo-dominated forest, tropical evergreen forest (merging evergreen mountain forests and evergreen lowland forests classes of [22]), deciduous forest (merging deciduous forests and deciduous wood and shrubland and regrowth mosaics of [22]), and crops (other land class of [22]).

2.3. Bamboo Reproductive Event Detection Previous studies demonstrated that different bamboo life stages determine clear spectral reflectance variations, which allow their detection from MODIS and LANDSAT TM/ETM multispectral imagery [18]. In this study, MODIS Normalized Difference Vegetation Index (NDVI) images were used to detect the spatial and temporal dynamics of the bamboo reproductive event. Specifically, NDVI time series between 2000 and 2014 generated by the BOKU (University of Natural Resources and Life Sciences, Vienna, Austria) data service platform (http://ivfl-info.boku.ac.at/, accessed on 1 July 2016) [30] were used. Among the options offered by the service, the combined MODIS TERRA/AQUA (MOD13 and MYD13) smoothed NDVI time series with 16-day temporal frequency and 250 m spatial resolution was selected for the study region. For smoothing and gap filling, the BOKU service applies the Whittaker method, deemed accurate and computationally efficient for global-scale NDVI analyses [31–33]. Mapping the bamboo reproductive event (i.e., flowering, fruiting, and mortality) was based on the analysis of the phenological behavior of Melocanna baccifera forests during the reproductive season [9] and on the consequent greenness variations. Figure2 schematically illustrates the expected (Figure2a) and an example of the observed (Figure2b) trajectories of greenness/NDVI during a non-reproductive and a reproductive season. In addition, the seasonal frequency distribution of wildfires is shown in Figure2a. According to this conceptual model and observed NDVI time series, the presence of a significant November/December NDVI negative anomaly, with respect to previous years, was selected as an indicator of the ongoing reproductive event. This is the period when observed anomalies could be clearly associated to the ongoing bamboo reproduction, with minimal expected impact of wildfires on the signal. Based on this assumption, the following steps were performed on the MODIS NDVI time series to detect the reproductive event:

(i) Computation of November-December mean NDVI (NDVIND). (ii) Starting from the year 2005 (as no bamboo ﬂowering was reported before 2005 [7–9], a t-test was applied to identify statistically signiﬁcant anomalies (p < 0.001) between NDVIND of the year i and mean and standard deviation of NDVIND for the period 2000—year i − 1. These seasons were marked as ‘reproductive seasons’. RemoteRemote Sens. Sens.2017 2017, 9, ,9 85, 85 55 of of 14 14

As mentioned in Section 2.1, logistic constraints did not allow collection of sufficient ground truthAs data mentioned for a quantitative in Section 2.1 ,accuracy logistic constraints assessment did of not the allow map collection at a regional of sufﬁcient scale. groundHowever, truth to dataqualitatively for a quantitative check the accuracy consistency assessment of the reproduc of the maptive at event a regional map with scale. an However, independent to qualitatively data source, checka dataset the consistency of Landsat ofTM the images reproductive acquired event during map th withe main an independentreproductive datayears source, (i.e., 36 a datasetcloud-free of Landsatimages, TM path/row images acquired133/48, 134/46–47, during the 135/44–45, main reproductive acquired years between (i.e., 36November cloud-free and images, February path/row from 133/48,2005 to 134/46–47,2011) was visually 135/44–45, analyzed acquired at 1:300,000 between Novemberscale, following and February[18]. Despite from the 2005 different to 2011) scale was of visuallyanalysis analyzed (i.e., the atvisual 1:300,000 interpretation scale, following allow [a18 lower]. Despite detail the in different the detection scale ofof analysisthe reproductive (i.e., the visualpatches), interpretation a very good allow agreement a lower detail was infound the detectionin the extent, of the timing, reproductive and spatial patches), patterns a very goodof the agreementreproductive was event. found in the extent, timing, and spatial patterns of the reproductive event.

FigureFigure 2. 2.( a(a)) Conceptual Conceptual model model of of the the expected expected variations variations in in greenness greenness during during reproductive reproductive and and non-reproductivenon-reproductive seasons. seasons. WildﬁreWildfire monthlymonthly frequencyfrequency distributiondistribution assessedassessed fromfrom thethe active active ﬁre fire MODISMODIS product product over over the the study study area area (see (see next next paragraph) paragraph) is is also also reported. reported.δ δindicates indicates the the expected expected November/DecemberNovember/December difference difference in in NDVI NDVI during during the reproductivethe reproductive season, season, the indicator the indicator used to used detect to thedetect event; the (event;b) Examples (b) Examples of MODIS of MODIS NDVI NDVI time seriestime series of bamboo-dominated of bamboo-dominated forests forests in the in casethe case of detectedof detected (red) and(red) not and detected not detected (green) reproductive(green) repr events.oductive In theevents. example, In the the example, detected reproductivethe detected eventreproductive occurred event in late occurred 2008/beginning in late 2008/beginning 2009. 2009.

2.4.2.4. Evaluation Evaluation of of Wildfire Wildfire Temporal Temporal and and Spatial Spatial Patterns Patterns ToTo investigate investigate the the spatial spatial and and temporal temporal dynamics dynamics of of wildfires wildfires before, before, during, during, and and after after the the reproductivereproductive event, event, the the MODIS MODIS burned burned area area (MCD45A1) (MCD45A1) [34] [34] and activeand active fire [ 35fire] products [35] products were used. were Theused. burned The areaburned product area providesproduct provides monthly estimatesmonthly estimates of area burned of area at 500burned m geometric at 500 m resolution geometric byresolution identifying by identifying rapid changes rapid in dailychanges surface in daily reflectance surface reflectance associated associated to deposits to of deposits charcoal of and charcoal ash, reductionand ash, ofreduction vegetation of cover,vegetation and vegetation cover, and structure vegetation modification structure [ 34modification]. The full-time [34]. series The betweenfull-time 2000series and between 2014 was 2000 analyzed. and 2014 was analyzed. TheThe MODIS MODIS active active fire fire products products (MOD14 (MOD14 and and MYD14) MYD14) uses uses middle-infrared middle-infrared and and thermal thermal bands bands toto detect detect changes changes in in brightness brightness temperature temperature associated associated with with fire fire presence presence [ 35[35]] at at daily daily time time intervals intervals andand 1 1 km km spatial spatial resolution. resolution. Specifically, Specifically, in in this this study, study, the the global global fire fire location location product product (MCD14ML) (MCD14ML) inin vector vector format format was was used used to to gather gather information information on on fire fire frequency frequency and and to to provide provide further further support support to to resultsresults provided provided by by the the burned burned area area product. product. ForFor the the analysis analysis of of burned burned area area patterns patterns across across different different land land covers, covers, the the generated generated land land cover cover rasterraster layers layers were were first first converted converted to vectorto vector format format and thenand overlaidthen overlaid to the to MODIS the MODIS burned burned area image area timeimage series time for series spatial for statistics’ spatial statistics’ computation. computation. A similar A approach similar approach was used forwas the used active for firethe products,active fire butproducts, the latter but being the latter in vector being format, in vector the format, analysis the was analysis performed was performed by selecting by dataselecting point data subsets point basedsubsets on based the spatial on the location spatial and location ‘year/month’ and ‘year/month’ attributes. attributes. The different The spatialdifferent resolutions spatial resolutions of the data of the data products used (i.e., from 250 m to 1 km) did not represent a major constraint for this Remote Sens. 2017, 9, 85 6 of 14 Remote Sens. 2017, 9, 85 6 of 14

analysis, as the size of the reproductive event and burned area patches was much larger than the productsdata spatial used resolution. (i.e., from 250 m to 1 km) did not represent a major constraint for this analysis, as the size of the reproductive event and burned area patches was much larger than the data spatial resolution. 3. Results and Discussion 3. Results and Discussion 3.1. Bamboo Forest Extent and Reproductive Event Dynamics 3.1. Bamboo Forest Extent and Reproductive Event Dynamics The use of multiple imaging products and of the Melocanna baccifera potential distribution map Theallows use offor multiple identification imaging of productsthe bamboo-dominated and of the Melocanna forest’s baccifera areal potentialextent. According distribution to mapthis allowsclassification, for identiﬁcation bamboo forests of the bamboo-dominatedcover approximately forest’s63,000 km areal2 in extent.the Arakan According mountain tothis range classiﬁcation, (Figure 3a). 2 bambooThe central forests and cover southern approximately parts of the 63,000 region, km whinich the are Arakan mainly mountain composed range of (FigureRakhine3a). and The Chin, central are andcharacterized southern partsby large ofthe continuous region, which bamboo-dominated are mainly composed forests locally of Rakhine alternated and Chin, with are dense characterized evergreen byforest large patches continuous and shifting bamboo-dominated cultivations. forestsThe northern locally alternatedpart of the with region, dense located evergreen in Chittagong forest patches and andManipur, shifting is cultivations.more fragmented, The northern especially part in of the region,northeastern located portion. in Chittagong Bamboo and forests Manipur, are ismainly more fragmented,located on the especially western inslopes the northeastern of the mountain portion. rang Bambooe, at elevations forests ranging are mainly approximately located on the from western 50 to slopes1050 m of a.s.l. the (Figure mountain 3b). range, This is at the elevations wetter side ranging of the approximately range due to fromthe orograph 50 to 1050ic effect, m a.s.l. with (Figure rainfall3b). Thisranging is the from wetter 2000 side to over of the 4000 range mm due per to year the orographic[36,37]. The effect, entire with region rainfall is characterized ranging from by 2000 Cambisols: to over 4000Dystric mm Cambisols per year [in36 ,the37]. Chittagong The entire regionHill region is characterized and Western by Mizoram, Cambisols: Humic Dystric Cambisols Cambisols in Easter in the ChittagongMizoram and Hill Chin, region and and Ferralic Western Cambisols Mizoram, in HumicRakhine Cambisols [38] (Figure in Easter3c). These Mizoram soils are and moderately Chin, and Ferralicfertile, but Cambisols they are inalso Rakhine prone to [38 severe] (Figure soil3 c).erosio Thesen, especially soils are moderatelywhen located fertile, over steep but they slopes are [39]. also prone to severe soil erosion, especially when located over steep slopes [39].

Figure 3. Distribution of Melocanna baccifera (a) superimposed (white stripes) to the elevation map (b) c andFigure the 3. soil Distribution map ( ) of theof Melocanna study region. baccifera (a) superimposed (white stripes) to the elevation map (b) and the soil map (c) of the study region. The spatial and temporal patterns of the reproductive event, as derived from the MODIS NDVI analysis,The arespatial reported and temporal in Figure 4patterns. First detectable of the reproduc ﬂoweringtive episodes event, as occurred derived infrom 2005 the in MODIS the northeast NDVI corneranalysis, of Manipurare reported and inin northern Figure Rakhine.4. First detec Then,table between flowering 2006 and episodes 2009, widespread occurred in ﬂowering 2005 in took the Remote Sens. 2017, 9, 85 7 of 14

Remotenortheast Sens. 2017 corner, 9, 85 of Manipur and in northern Rakhine. Then, between 2006 and 2009, widespread7 of 14 flowering took place all over the region. In 2010 and 2011 the last large bamboo patches flowered in placethe allsouthernmost over the region. portion In 2010 of andArakan, 2011 themainly last large in bambooRakhine. patches Over ﬂoweredthese years, in the the southernmost large scale portionreproductive of Arakan, event mainly affected in Rakhine. about 65% Over of these the years,mapped the bamboo large scale area. reproductive These patterns event affectedare fully aboutconsistent 65% of with the mapped the ones bamboo evidenced area. Theseby local patterns scale are studies, fully consistent which mainly with the focused ones evidenced on rodent by localoutbreaks, scale studies, reporting which general mainly information focused on about rodent bamboo outbreaks, flowering reporting in different general informationareas [9]. The about main bambooregion where ﬂowering there in is different no evidence areas [of9]. the The occurrence main region of wherethe bamboo there isreproductive no evidence event of the is occurrence located in ofthe the northeastern bamboo reproductive portion of event the study is located region. inthe In northeasternthis area, the portion bamboo-dominated of the studyregion. forest is In more this area,fragmented the bamboo-dominated and may include forest different is more vegetation fragmented types and affecting may include the NDVI different seasonal vegetation trajectory types and affectinghampering the the NDVI detection seasonal of trajectorythe event. and hampering the detection of the event.

FigureFigure 4. 4.Map Map of of the the estimated estimated year year of of occurrence occurrence of of the the bamboo bamboo reproductive reproductive event. event. For For the the main main reproductivereproductive seasons seasons (i.e., (i.e., 2006–2010) 2006–2010) the the NDVI NDVINDNDtemporal temporal trend trend is is reported reported in in Figure Figure S2. S2.

ReproductiveReproductive eventsevents occurredoccurred synchronouslysynchronously (i.e.,(i.e., duringduring thethe samesame season)season) overover ratherrather homogeneoushomogeneous patchespatches (Figure (Figure4 ).4). Patch Patch size size was was highly highly variable variable across across the the region region and and shows shows a a power-lawpower-law distribution distribution (cf. (cf. FigureFigure S3).S3). A few large patches (i.e., (i.e., over over 100 100 km km2)2 )represent represent over over 60% 60% of ofthe the area, area, and and the the largest largest patch reaches over 30003000 kmkm22.. TheThe bordersborders amongamong adjacent adjacent patches patches were were generallygenerally sharp sharp and and well well defined, defined, similar similar to to the the results results reported reported by by [ 18[18],], suggesting suggesting that that populations populations maymay be be spatially spatially exclusive. exclusive. The spatialThe spatial distribution distribu oftion the reproductiveof the reproductive event patches event across patches elevation across doeselevation not show does any not regular show any temporal regular pattern temporal (cf. Figurepattern S4). (cf. Nevertheless,Figure S4). Nevertheless, on average, on 60% average, of patches 60% floweredof patches in contiguousflowered in years, contiguous suggesting years, the suggesti possibilityng the of a possibility non-random of distributiona non-random [18]. distribution Although the[18]. methodology Although appliedthe methodology in this study applied is not intended in this tostudy map is single not bamboointended populations, to map single but onlybamboo the regionalpopulations, spatial but patterns only the of theregional reproductive spatial event,patterns these of the results reproductive seems consistent event, these with theresults flowering seems waveconsistent hypothesis with the [40 ]flowering to explain wave bamboo’s hypothesis gregarious [40] to flowering explain bamboo’s spatial and gregarious temporal flowering dynamics spatial over RemoteRemote Sens. Sens.2017 2017,,9 9,, 85 85 88 of of 14 14

and temporal dynamics over large regions. Nevertheless, the event did not show any clear largeunidirectional regions. Nevertheless, spreading dynamic, the event but did followe not showd more any complex clear unidirectional spatial patterns spreading [18,40]. dynamic, but followed more complex spatial patterns [18,40]. 3.2. Analysis of Wildfire Dynamics 3.2. Analysis of Wildﬁre Dynamics The total burned area before and during the reproductive event is reported in Figure 5. Overall, The total burned area before and during the reproductive event is reported in Figure5. Overall, the total burned area almost doubled during the years 2007–2011 (i.e., following the main reproductive the total burned area almost doubled during the years 2007–2011 (i.e., following the main reproductive event periods, which mainly occurred from late 2006 to 2011) compared to previous years (2001– event periods, which mainly occurred from late 2006 to 2011) compared to previous years (2001–2006), 2006), with total burned area reaching almost 16,000 km2 (i.e., 25% of the total bamboo forest cover). with total burned area reaching almost 16,000 km2 (i.e., 25% of the total bamboo forest cover).

FigureFigure 5. 5.( a()a Main) Main land land covers covers of theof the study study area; area; (b) total (b) burnedtotal burned area before area before (2000–2006); (2000–2006); and (c) duringand (c) (2006–2012)during (2006–2012) the bamboo the bamboo reproductive reproductive event. event.

TheThe analysisanalysis of of the the inter-annual inter-annual dynamics dynamics of burned of burned area in area bamboo-dominated in bamboo-dominated forests confirms forests thatconfirms a strong that increase a strong in increase burned areain burned took place area concurrently took place concurrently with the reproductive with the reproductive event period, event with peaksperiod, in with 2009 peaks and 2010 in 2009 (Figure and6 a).2010 From (Figure 2011 6a). onward, From yearly2011 onward, burned yearly area gradually burned area decreased gradually to valuesdecreased comparable to values to comparable years before to the years reproductive before th event.e reproductive However, event. increasing However, burned increasing area during burned this periodarea during might this be also period the consequencemight be also of the factors conseque othernce than of thefactors reproductive other than event, the reproductive primarily drought event, atprimarily regional scale.drought To testat regional this hypothesis, scale. To the test Standardized this hypothesis, Precipitation the Standa andrdized Evapotraspiration Precipitation Index and (SPEI)Evapotraspiration [41] was used Index to evaluate (SPEI) if major[41] was drought used episodes to evaluate occurred if major concurrently drought with episodes the burned occurred area increase.concurrently SPEI timewith seriesthe burned averaged area over increase. the study SP areaEI highlightedtime series twoaveraged drought over episodes the study during area the peakhighlighted years (Figure two drought6b), suggesting episodes that during drought the couldpeak years also have (Figure been 6b), a key suggesting determinant that ofdrought the burned could areaalso increasehave been in the a key region. determinant Figure7 shows of the the burned relationship area increase between in SPEI the andregion. burned Figure area 7 before shows and the duringrelationship the reproductive between SPEI event and period. burned The area two before regression and during models the have reproductive similar slopes, event but period. during theThe reproductivetwo regression years models a significantly have similar higher slopes, intercept but during was observed the reproductive (p < 0.001, years cf. Table a significantly S1), resulting higher on averageintercept in was an overobserved two to (p three-fold < 0.001, cf. increase Table S1), in burned resulting area on during average the in event an over for comparabletwo to three-fold SPEI values.increase This in burned indicates area a strong during effect the event of the for reproductive comparable event SPEI on values. wildfires This dynamics indicates and a strong supports effect the of hypothesisthe reproductive that the event massive on wildfires fuel load dynamics generated and by su thepports reproductive the hypothesis event createdthat the the massive conditions fuel load for largegenerated wildfires’ by the occurrence reproductive and propagation. event created the conditions for large wildfires’ occurrence and propagation. Remote Sens. 2017, 9, 85 9 of 14 Remote Sens. 2017,, 9,, 8585 9 of 14

Figure 6. (a) 2000–2013 time series of burned area in bamboo-dominated forests; and (b) of Figure 6.6.( a()a 2000–2013) 2000–2013 time time series series of burned of burned area in bamboo-dominatedarea in bamboo-dominated forests; and forests; (b) of Standardized and (b) of Standardized Precipitation and Evapotraspiration Index (SPEI) (three-month timescale) averaged PrecipitationStandardized and Precipitation Evapotraspiration and Evapotraspiratio Index (SPEI) (three-monthn Index (SPEI) timescale) (three-month averaged timescale) over the studyaveraged area. over the study area. Blue columns evidence positive SPEI values, red columns negative SPEI values. Blueover columnsthe study evidence area. Blue positive columns SPEI evidence values, positive red columns SPEI negativevalues, red SPEI columns values. negative SPEI values.

Figure 7. OrdinaryOrdinary RegressionRegression models models between between mean mean November-May November-May SPEI SPEI (i.e., (i.e., dry dry season season SPEI) SPEI) and Figure 7. Ordinary Regression models between mean November-May SPEI (i.e., dry season SPEI) Burnedand Burned Area beforeArea before the reproductive the reproductive event (2001–2006) event (2001–2006) and during and the during reproductive the reproductive event (2007–2012). event and Burned Area before the reproductive event (2001–2006) and during the reproductive event (2007–2012). (2007–2012). Figure8 reports the burned area and the number of active fires for different land covers before and duringFigure the8 reports reproductive the burned event. area It isand worth the number noting that of active the number fires for of different active fires land and covers the burned before areaand during only moderately the reproductive increased event. in both It is cropworth and noti deciduousng that the forest, number further of active supporting fires and the the specificity burned ofarea the only result moderately obtained increased for bamboo-dominated in both crop and forests. deciduous However, forest, a further relevant supporting increase of the burned specificity area wasof the detected result obtained also within for thebamboo-dominated evergreen forest classforests. (from However, 2.6% to a 4.1%relevant of the increase total evergreen of burned forest area area).was detected Evergreen also forest within patches the evergreen are often forest located class within (from or 2.6% adjacent to 4.1% to the of the bamboo-dominated total evergreen forest area, area). Evergreen forest patches are often located within or adjacent to the bamboo-dominated area, suggesting a possible indirect connection with the reproductive event. This hypothesis was tested by Remote Sens. 2017, 9, 85 10 of 14 Remote Sens. 2017, 9, 85 10 of 14

calculating the relative contribution to the increase of burned area of evergreen forest patches suggestingsharing (EGs) a possible and not-sharing indirect connection (EGns) a border with the wi reproductiveth bamboo-dominated event. This forest. hypothesis Burned was area tested within by calculatingEG patches the increased relative contributionfrom 125 to 369 to the km increase2 (+195%) of during burned reproductive area of evergreen years, forest while patches only a sharing limited (EGs)increase and from not-sharing 313 km (EGns)2 to 320 a km border2 (+2.4%) with occurred bamboo-dominated for EGns during forest. the Burned same area period. within These EG patchespatterns increasedclearly show from a 125 side to effect 369 km of2 (+195%)the reproductive during reproductive event on the years, last whileremaining only adense limited evergreen increase forest from 313stands km2 ofto the 320 region. km2 (+2.4%) occurred for EGns during the same period. These patterns clearly show a side effect of the reproductive event on the last remaining dense evergreen forest stands of the region.

Figure 8. (a) Burned area before and during the reproductive event. The burned area percent with Figure 8. (a) Burned area before and during the reproductive event. The burned area percent with respect to the total cover is also reported; (b) Number of active ﬁres detected before and during the respect to the total cover is also reported; (b) Number of active fires detected before and during the reproductive event. reproductive event.

A close examination of the spatial patterns of burned areas in bamboo-dominated forests at the A close examination of the spatial patterns of burned areas in bamboo-dominated forests at the regional scale shows evidence that increases in burned area are not ubiquitous (Figure5): a strong regional scale shows evidence that increases in burned area are not ubiquitous (Figure 5): a strong increase was mainly observed in the bamboo-dominated forest of Chin and Rakhine. These areas increase was mainly observed in the bamboo-dominated forest of Chin and Rakhine. These areas were mostly unaffected by large size wildfires before the bamboo reproductive event. However, were mostly unaffected by large size wildfires before the bamboo reproductive event. However, similar patterns were not evident in Manipur and Chittagong Hills, which are characterized by more similar patterns were not evident in Manipur and Chittagong Hills, which are characterized by more fragmented bamboo cover and higher fire occurrence before the event, often associated with shifting fragmented bamboo cover and higher fire occurrence before the event, often associated with shifting cultivations. Two hypotheses could explain this result. First, the larger pure bamboo forest patches, cultivations. Two hypotheses could explain this result. First, the larger pure bamboo forest patches, which characterize Chin and Rakhine, favored ignition and propagation of very large wildfires, while which characterize Chin and Rakhine, favored ignition and propagation of very large wildfires, the more fragmented landscapes of Mizoram and Chittagong limited the fire propagation. Second, while the more fragmented landscapes of Mizoram and Chittagong limited the fire propagation. both India and Bangladesh may have been successful in implementing policy plans to manage the Second, both India and Bangladesh may have been successful in implementing policy plans to forecasted bamboo reproductive event and related food security crisis, including fire management and manage the forecasted bamboo reproductive event and related food security crisis, including fire suppression [42,43]. management and suppression [42,43]. Overall, these results provide evidence that the regional scale bamboo mortality promoted the Overall, these results provide evidence that the regional scale bamboo mortality promoted the occurrence of large wildfires in the area, with potentially strong ecological impacts over the region occurrence of large wildfires in the area, with potentially strong ecological impacts over the region other than rodent outbreaks, such as damage to human settlements; fire emissions; disturbance to other than rodent outbreaks, such as damage to human settlements; fire emissions; disturbance to high conservation value ecosystems, including remnant patches of dense evergreen forests; and high conservation value ecosystems, including remnant patches of dense evergreen forests; and direct or indirect impacts on fauna resident of bamboo-dominated habitats. So far, several studies direct or indirect impacts on fauna resident of bamboo-dominated habitats. So far, several studies have highlighted that wildfires could facilitate bamboo invasion [12,17], but none have evidenced an have highlighted that wildfires could facilitate bamboo invasion [12,17], but none have evidenced an interconnection between bamboo reproduction and wildfires at regional scale. interconnection between bamboo reproduction and wildfires at regional scale. In addition, these analyses provide some level of support to the fire-cycle hypothesis [11], as a In addition, these analyses provide some level of support to the fire-cycle hypothesis [11], as a clear change in fire regime was associated with the flowering event, especially in regions with large clear change in fire regime was associated with the flowering event, especially in regions with large bamboo forest patches where natural fire propagation dynamics can develop [44], including protected bamboo forest patches where natural fire propagation dynamics can develop [44], including protected areas. Nevertheless, other evidence, such as testing for charcoal in soil profiles and colluvial sediments, areas. Nevertheless, other evidence, such as testing for charcoal in soil profiles and colluvial Remote Sens. 2017, 9, 85 11 of 14 should be collected to verify if similar fire dynamics occurred during past reproductive events, and to fully understand if fires effectively could be key determinants of a competitive advantage for bamboo [45].

3.3. Possible Limitations of the Proposed Approach The assessment of the bamboo forest’s extension is based on the analysis of different mapping products and visual interpretation of the Landsat GeoCover mosaic. Although the reflectance signature of bamboo has distinct features compared to other vegetation typologies and other recent studies successfully used this approach for bamboo forest classification [17,18], more complex approaches might be required to identify understory bamboos or bamboo forest patches within mixed forest areas in fragmented landscapes [46]. However, in the Arakan region Melocanna baccifera generally forms large and nearly pure stands [44], which makes its identification easier and the expected accuracy compatible with a regional scale analysis. Similar arguments are used to support the validity of the methodological approach used on MODIS NDVI time series for identifying the reproductive event timing and spatial dynamics. The large extension of the bamboo-dominated forest and the consistent spatial patterns of NDVI change during the expected reproductive years allowed us to simplify and make more objective the otherwise extremely time consuming process of visual image interpretation, throughout the automatic identification of the bamboo reproductive event patterns.. Nonetheless, it should be noted that the proposed approach is designed for regional level analysis and it is based on empirical observations and assumptions which are valid only for the specific geographic and ecological context. As such, it should be tested with caution in different geographic areas and/or with other bamboo species and/or for more fragmented landscapes or mixed forests. A dramatic increase in the burned area and fire frequency was observed during the years of the bamboo reproductive event, with matching spatial and temporal patterns between wildfires and bamboo reproduction dynamics. This finding evidences that the increase of standing dead biomass due to bamboo synchronous mortality favored fire propagation also in areas where large size fires were not common, with potentially relevant environmental impacts. Nothing, however, could be said about the anthropic or natural origin of wildfires and fire ignition processes. Non-scientific reports and interviews with local farmers during the field survey indicated fire as a strategy to control rodent outbreaks during the bamboo reproductive event. However, the extent of this practice is unknown and the vastness of the burned patches in a single season suggests uncontrolled fire propagation, at least in regions such as Chin and Rakhine. This remains an open question to be clarified in order to fully understand the ecology of this event, as well as to support future policy planning to reduce food and environmental insecurity in the area. Despite the above-mentioned potential sources of inaccuracy recommending caution in the interpretation of the final mapping products, especially for local scale analyses, this study demonstrates consistent spatial and temporal patterns in different satellite data products (i.e., Landsat TM/ETM+, MODIS NDVI, MODIS Burned Area, and MODIS Active Fire), all supporting the large extension of the bamboo reproductive event and a clear change in wildfire regime, and provides the first regional scale assessment for future land policy planning.

4. Conclusions This study generated the first map of bamboo-dominated forest and describes, for the first time, the spatial and temporal dynamics of the 2005–2011 bamboo reproductive event that occurred in the Arakan mountain range. The results provide evidence of a clear connection between flowering, fruiting, and mortality of the bamboo species Melocanna baccifera and a strong increase in fire occurrence and burned area extent after the reproductive event, offering, to some extent, empirical support to the fire-cycle hypothesis about the bamboo reproductive strategy of mast flowering and semelparity. Remote Sens. 2017, 9, 85 12 of 14

The steady increase of burned area during the reproductive event, particularly in Myanmar, suggests that wildﬁres could have represented a major factor of environmental and food insecurity for local communities in the region, together with the widely reported rodent outbreaks. It also marks a potential threat for the conservation of important ecosystems, such as the remaining evergreen forest patches. These results emphasize the regional relevance of this pulse event, calling for integrated and coordinated management strategies between the involved states, international institutions, and non-governmental organizations. The generated mapping products of bamboo forest extension and reproductive event dynamics may offer a baseline for supporting a better understanding of bamboo ecology in the region, as well as for planning mitigation strategies to reduce the impact of the next reproductive event. Finally, this study also highlights the potential role and impact of pulse ecological events in South East Asia, especially in the framework of monitoring and assessment studies based on Earth observation data. The rapidness, relevance, and signiﬁcant impacts of this event suggests the need for using multiple-scale satellite data products in order to detect rapid landscape changes, as well as the importance of a better understanding of forest ecology dynamics at a sub-continent scale.

Supplementary Materials: The following are available online at www.mdpi.com/2072-4292/9/1/85/s1, Figure S1: Bamboo-dominated forest map; Figure S2: Z-score NDVI time series; Figure S3: Patch-size distribution; Figure S4: Patch elevation distribution; Table S1: Burned area vs. SPEI relationship. Acknowledgments: This study was funded by Istituto Oikos Onlus (Italy). We are extremely grateful to the Myanmar team of Istituto Oikos, and, in particular, to Milo Todeschini, Lara Beffasti, U Aye Cho, and Maung Maung Pyone for their support during the field survey in Myanmar. We also wish to thank Nathaniel Jensen, Rupsha Banerjee, and the anonymous reviewers for the useful comments and suggestions. Author Contributions: The general conception of the study was shared between Francesco Fava and Roberto Colombo. Both authors also participated to fieldwork activities. Data processing and analyses have been mainly done by Francesco Fava. Both authors contributed to the paper writing. Overall, authors contributed equally to this study. Conflicts of Interest: The authors declare no conflict of interest.

References

1. Yang, L.H.; Edwards, K.F.; Byrnes, J.E.; Bastow, J.L.; Wright, A.N.; Spence, K.O. A meta-analysis of resource pulse–consumer interactions. Ecol. Monogr. 2010, 80, 125–151. [CrossRef] 2. Yang, L.H.; Bastow, J.L.; Spence, K.O.; Wright, A.N. What can we learn from resource pulses? Ecology 2008, 89, 621–634. [CrossRef][PubMed] 3. Silvertown, J.W. The evolutionary ecology of mast seeding trees. Biol. J. Linn. Soc. 1980, 14, 235–250. [CrossRef] 4. Soderstrom, T.R.; Calderon, C.E. A commentary on the bamboos (Poaceae: Bambusoideae). Biotropica 1979, 11, 161–172. [CrossRef] 5. Janzen, D.H. Why bamboos wait so long to flower? Annu. Rev. Ecol. Syst. 1976, 7, 347–391. [CrossRef] 6. Blatter, E. The flowering of bamboos. J. Bombay Nat. Hist. Soc. 1930, 34, 135–141. 7. Normile, D. Holding back a torrent of rats. Science 2010, 327, 806–807. [CrossRef][PubMed] 8. Singleton, G.R.; Belmain, S.; Brown, P.R.; Aplin, K.; Htwe, N.M. Impacts of rodent outbreaks on food security in Asia. Wildlife Res. 2010, 37, 355–359. [CrossRef] 9. Singleton, G.R. Rodent Outbreaks: Ecology and Impacts; International Rice Research Institute: Los Banos, Philippines, 2010. 10. Rao, M.; Htun, S.; Platt, S.G.; Tizard, R.; Poole, C.; Myint, T.; Watson, J.E.M. Biodiversity conservation in a changing climate: A review of threats and implications for conservation planning in Myanmar. AMBIO 2013, 42, 789–804. [CrossRef][PubMed] 11. Keeley, J.E.; Bond, W.J. Mast flowering and semelparity in bamboos: The bamboo fire cycle hypothesis. Am. Nat. 1999, 154, 383–391. [CrossRef][PubMed] 12. Smith, M.; Nelson, B.W. Fire favours expansion of bamboo-dominated forests in the south-west Amazon. J. Trop. Ecol. 2011, 27, 59–64. [CrossRef] Remote Sens. 2017, 9, 85 13 of 14

13. Saha, S.; Howe, H.F. The bamboo fire cycle hypothesis: A comment. Am. Nat. 2001, 158, 659–663. [CrossRef] [PubMed] 14. Keeley, J.E.; Bond, W.J. On incorporating fire into our thinking about natural ecosystems: A response to Saha and Howe. Am. Nat. 2001, 158, 664–670. [CrossRef][PubMed] 15. Barlow, J.; Silveira, J.M.; Mestre, L.A.; Andrade, R.B.; D’Andrea, G.C.; Louzada, J.; Vaz-de-Mello, F.Z.; Numata, I.; Lacau, S.; Cochrane, M.A. Wildfires in bamboo-dominated Amazonian forest: Impacts on above-ground biomass and biodiversity. PLoS ONE 2012, 7, e33373. [CrossRef] 16. Franklin, D.C.; Prior, L.D.; Hogarth, N.J.; McMahon, C.R. Bamboo, fire and flood: Consequences of disturbance for the vegetative growth of a clumping, clonal plant. Plant Ecol. 2010, 208, 319–332. [CrossRef] 17. McMichael, C.H.; Bush, M.B.; Silman, M.R.; Piperno, D.R.; Raczka, M.; Lobato, L.C.; Zimmerman, M.; Hagen, S.; Palace, M. Historical fire and bamboo dynamics in western Amazonia. J. Biogeogr. 2013, 40, 299–309. [CrossRef] 18. De Carvalho, A.L.; Nelson, B.W.; Bianchini, M.C.; Plagnol, D.; Kuplich, T.M.; Daly, D.C. Bamboo-dominated forests of the southwest Amazon: Detection, spatial extent, life cycle length and flowering waves. PLoS ONE 2013, 8, e54852. [CrossRef][PubMed] 19. Mouillot, F.; Schultz, M.G.; Yue, C.; Cadule, P.; Tansey, K.; Ciais, P.; Chuvieco, E. Ten years of global burned area products from spaceborne remote sensing—A review: Analysis of user needs and recommendations for future developments. Int. J. Appl. Earth Obs. 2014, 26, 64–79. [CrossRef] 20. Giglio, L.; Loboda, T.; Roy, D.P.; Quayle, B.; Justice, C.O. An active-fire based burned area mapping algorithm for the MODIS sensor. Remote Sens. Environ. 2009, 113, 408–420. [CrossRef] 21. Stibig, H.J.; Achard, F.; Fritz, S. A new forest cover map of continental Southeast Asia derived from SPOT-VEGETATION satellite imagery. Appl. Veg. Sci. 2004, 7, 153–162. [CrossRef] 22. Stibig, H.J.; Belward, A.S.; Roy, P.S.; Rosalina-Wasrin, U.; Agrawal, S.; Joshi, P.K.; Beuchle, R.; Fritz, S.; Mubareka, S.; Giri, C. A land-cover map for South and Southeast Asia derived from SPOT-VEGETATION data. J. Biogeogr. 2007, 34, 625–637. [CrossRef] 23. Giri, C.; Defourny, P.; Shrestha, S. Land cover characterization and mapping of continental Southeast Asia using multi-resolution satellite sensor data. Int. J. Remote Sens. 2003, 24, 4181–4196. [CrossRef] 24. Food and Agriculture Organization. Global Forest Resources Assessment 2015. Available online: http://www.fao.org/forest-resources-assessment/en/ (accessed on 20 July 2016). 25. Giri, C.; Pradhan, D.; Ofren, R.S.; Kratzschmar, E. Land Use/Land Cover Change in South and South-East Asia; UNEP Environment Assessment Programme for Asia and the Pacific: Bangkok, Thailand, 1998. 26. Rao, A.N.; Ramanatha Rao, V. Bamboo-Conservation, diversity, ecogeography, germplasm, resource utilization and taxonomy. In Proceedings of the Training Course Cum Workshop, Kunming and Xishuanbanna, Yunnan, China, 10–17 May 1998. 27. Landsat Orthorectified Dataset (January 2005–December 2011). The Global Land Cover Facility 2005. Available online: http://www.glovis.org (accessed on 31 December 2015). 28. Bystriakova, N.; Kapos, V.; Stapleton, C.M.A.; Lysenko, I. Bamboo Biodiversity; UNEP-WCMC: Cambridge, UK, 2003. 29. Bystriakova, N.; Kapos, V.; Lysenko, I.; Stapleton, C.M.A. Distribution and conservation status of forest bamboo biodiversity in the Asia-Pacific Region. Biodivers. Conserv. 2003, 12, 1833–1841. [CrossRef] 30. Vuolo, F.; Mattiuzzi, M.; Klisch, A.; Atzberger, C. Data service platform for MODIS vegetation indices time series processing at BOKU Vienna: Current status and future perspectives. Proc. SPIE 2012.[CrossRef] 31. Atzberger, C.; Eilers, P.H.C. Evaluating the effectiveness of smoothing algorithms in the absence of ground reference measurements. Int. J. Remote Sens. 2011, 32, 3689–3709. [CrossRef] 32. Atkinson, P.M.; Jeganathan, C.; Dash, J.; Atzberger, C. Intercomparison of four models for smoothing satellite sensor time-series data to estimate vegetation phenology. Remote Sens. Environ. 2012, 123, 400–417. [CrossRef] 33. Eilers, P.H.C. A perfect smoother. Anal. Chem. 2003, 75, 3631–3636. [CrossRef][PubMed] 34. Roy, D.P.; Jin, Y.; Lewis, P.E.; Justice, C.O. Prototyping a global algorithm for systematic fire-affected area mapping using MODIS time series data. Remote Sens. Environ. 2005, 97, 137–162. [CrossRef] 35. Giglio, L.; Descloitres, J.; Justice, C.O.; Kaufman, Y.J. An enhanced contextual fire detection algorithm for MODIS. Remote Sens. Environ. 2003, 87, 273–282. [CrossRef] Remote Sens. 2017, 9, 85 14 of 14

36. FAO. Agricultural Atlas of the Union of Myanmar-Agricultural Year 2001–2002. Available online: http://dwms.fao.org/atlases/myanmar/index_en.htm (accessed on 20 July 2016). 37. Attri, S.D.; Tyagi, A. Climate profile of India. Met. Monogr. Environ. Meteorol. 2010, 1, 1–122. 38. FAO. Digital Soil Map of the World 2007. Available online: http://www.fao.org/geonetwork/srv/en/ metadata.show?id=14116 (accessed on 10 July 2016). 39. Dudal, R. Soils of Southeast Asia. In The Physical Geography of Southeast Asia, 1st ed.; Gupta, A., Ed.; Oxford University Press: Oxford, UK, 2005; pp. 94–104. 40. Franklin, D.C. Synchrony and asynchrony: Observations and hypotheses for the flowering wave in a long-lived semelparous bamboo. J. Biogeogr. 2004, 31, 773–786. [CrossRef] 41. Vicente-Serrano, S.M.; Beguería, S.; López-Moreno, J.I. A multi-scalar drought index sensitive to global warming: The standardized precipitation evapotranspiration index. J. Clim. 2010, 23, 1696–1718. [CrossRef] 42. Planning & Programme Implementation Department, Government of Mizoram. Government of Mizoram Comprehensive Action Plan for Bamboo Flowering and Famine Combat Schemes (BAFFACOS) (2004–2005 to 2008–2009). Available online: http://mizoram.nic.in/dept/planning/baffacos.htm (accessed on 20 July 2016). 43. United Nations Development Program, Bangladesh. Scientific Report on Bamboo Flowering, Rodent Outbreaks and Food Security: Rodent Ecology, Pest Management, and Socio-Economic Impact in the Chittagong Hill Tracts. 2008. Available online: http://projects.nri.org/bandicoot/docs/bamboo.pdf (accessed on 20 July 2016). 44. Platt, S.G.; Ko, W.K.; Myo, K.M.; Khaing, L.L.; Platt, K.; Maung, A.; Rainwater, T.R. Notes on Melocanna baccifera and bamboo brakes in the Rakhine hills of western Myanmar. Bamboo Sci. Cult. 2010, 23, 1–12. 45. Rayle, C.M.; Franklin, S.B.; Lu, Z. Fire occurrence in relation to bamboo dominance in the Qinling Mountains of China: Evidence from phytolith and charcoal records in Holocene sediments. Sci. China Earth Sci. 2015, 58, 1182–1190. [CrossRef] 46. Linderman, M.; Liu, J.; Qi, J.; An, L.; Ouyang, Z.; Yang, J.; Tan, Y. Using artificial neural networks to map the spatial distribution of understorey bamboo from remote sensing data. Int. J. Remote Sens. 2004, 25, 1685–1700. [CrossRef]

© 2017 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).