Gelam tree or Melaleuca cajuputi (M. cajuputi) is an important species for the local economy as well as coastal ecosystem protection in Terengganu, Malaysia. This study aimed at producing a current habitat suitability map and predicting future potential habitat distribution for M. cajuputi in Terengganu based on Species distribution modeling (SDM) using the Maximum Entropy principle. Our modeling results show that for the current potential distribution of M. cajuputi species, only 10.82% (1346.5 km²) of Terengganu area is suitable habitat, which 0.96% of the areas are under high, 2.44% moderate and 7.42% poor habitat suitability. The model prediction for future projection shows that the habitat suitability for M. cajuputi would decrease significantly in the year 2050 under RCP 4.5 where the largest contraction from suitable to unsuitable habitat area is about 442.1 km² and under RCP 2.6 is the highest expansion from unsuitable to suitable habitat area (267.5 km²). From the future habitat suitability projection, we found that the habitat suitability in Marang would degrade significantly under all climate scenarios, while in Setiu the habitat suitability for M. cajuputi remains stable throughout the climate change scenarios. The modeling prediction shows a significant influence on the soil properties, temperature, and precipitation during monsoon months. These results could benefit conservationist and policymakers for decision making. The present model could also give a perception into potential habitat suitability of M. cajuputi in the future and to improve our understanding of the species’ response under the changing climate.

In humid forests in Southeast Asia, many species from dozens of plant families flower gregariously and fruit synchronously at irregular multi-year intervals^1–4. Little is known about how climate change will impact these community-wide mass reproductive events. Here, we perform a comprehensive analysis of reproductive phenology and its environmental drivers based on a monthly reproductive phenology record from 210 species in 41 families in Peninsular Malaysia. We find that the proportion of flowering and fruiting species decreased from 1976 to 2010. Using a phenology model, we find that 57% of species in the Dipterocarpaceae family respond to both drought and low-temperature cues for flowering. We show that low-temperature flowering cues will become less available in the future in the RCP2.6 and 8.5 scenarios, leading to decreased flowering opportunities of these species in a wide region from Thailand to the island of Borneo. Our results highlight the vulnerability of and variability in phenological responses across species in tropical ecosystems that differ from temperate and boreal biomes.

Precise spatio-temporal measurements of rainfall during seasonal monsoons are critical for accurate hydrologic analyses in the tropical regions of Southeast Asia. The use of satellite precipitation data is technologically sound but requires downscaling to minimize inherent uncertainties. The uncertainties at a local climate regime that are essential to be resolved are rarely reported; consequently, such work needs attention. To address this problem, we validated the Tropical Rainfall Measuring Mission (TRMM) precipitation data using high-resolution areal precipitation (0.125 deg.) at a seasonal scale. This study examined the performance of the monthly rainfall data product (TRMM 3B43) at the seasonal monsoon scale in the local climate region of Peninsular Malaysia. The high-resolution areal precipitation data (0.125 deg.) were derived from a dense rain gauge network ever collected in Peninsular Malaysia (n = 984). Three relevant performance elements were evaluated: (i) the ability to depict temporal rainfall variation (ii) the quantitative error between TRMM and ground rainfall; and (iii) the ability to estimate the actual rainfall amount. We found that the ability of monthly TRMM data to depict rainfall variation and its tendency to propagate large errors varied seasonally. The correlation between TRMM and ground rainfall was good during the wettest period in all local climate regions. The error was related to the northeast monsoon and inter-monsoon 2 (September–October). Meanwhile, the TRMM ratio varied regionally, rather than seasonally. Determining the local-scale uncertainties will facilitate future downscale activities using TRMM satellite data in this region.

In South-East Asian dipterocarp forests, many trees synchronize their reproduction at the community level, but irregularly, in a phenomenon known as general flowering (GF). Several proximate cues have been proposed as triggers for the synchronization of Southeast Asian GF, but the debate continues, as many studies have not considered geographical variation in climate and flora. We hypothesized that the spatial pattern of GF forests is explained by previously proposed climatic cues if there are common cues for GF among regions. During the study, GF episodes occurred every year, but the spatial occurrence varied considerably from just a few forests to the whole of Peninsular Malaysia. In 2001, 2002 and 2005, minor and major GF occurred widely throughout Peninsular Malaysia (GF2001, GF2002, and GF2005), and the geographical patterns of GF varied between the episodes. In the three regional-scale GF episodes, most major events occurred in regions where prolonged drought (PD) had been recorded prior, and significant associations between GF scores and PD were found in GF2001 and GF2002. However, the frequency of PD was higher than that of GF throughout the peninsula. In contrast, low temperature (LT) was observed during the study period only before GF2002 and GF2005, but there was no clear spatial relationship between GF and LT in the regional-scale episodes. There was also no evidence that last GF condition influenced the magnitude of GF. Thus, our results suggest that PD would be essential to trigger regional-scale GF in the peninsula, but also that PD does not fully explain the spatial and temporal patterns of GF. The coarse relationships between GF and the proposed climatic cues may be due to the geographical variation in proximate cues for GF, and the climatic and floristic geographical variations should be considered to understand the proximate factors of GF.

This paper described the development of a spatial downscaling algorithm to produce finer grid resolution for satellite precipitation data (0.05°) in humid tropics. The grid resolution provided by satellite precipitation data (>0.25°) was unsuitable for practical hydrology and meteorology applications in the high hydrometeorological dynamics of Southeast Asia. Many downscaling algorithms have been developed based on significant seasonal relationships, without vegetation and climate conditions, which were inapplicable in humid, equatorial, and tropical regions. Therefore, we exploited the potential of the low variability of rainfall and monsoon characteristics (period, location, and intensity) on a local scale, as a proxy to downscale the satellite precipitation grid and its corresponding rainfall estimates. This study hypothesized that the ratio between the satellite precipitation and ground rainfall in the low-variance spatial rainfall pattern and seasonality region of humid tropics can be used as a coefficient (constant value) to spatially downscale future satellite precipitation datasets. The spatial downscaling process has two major phases: the first is the derivation of the high-resolution coefficient (0.05°), and the second is applying the coefficient to produce the high-resolution precipitation map. The first phase utilized the long-term bias records (1998–2008) between the high-resolution areal precipitation (0.05°) that was derived from dense network of ground precipitation data and re-gridded satellite precipitation data (0.05°) from the Tropical Rainfall Measuring Mission (TRMM) to produce the site-specific coefficient (SSC) for each individual pixel. The outcome of the spatial downscaling process managed to produce a higher resolution of the TRMM data from 0.25° to 0.05° with a lower bias (average: 18%). The trade-off for the process was a small decline in the correlation between TRMM and ground rainfall. Our results indicate that the SSC downscaled method can be used to spatially downscale satellite precipitation data in humid, tropical regions, where the seasonal rainfall is consistent.