Improved NDVI based proxy leaf-fall indicator to assess rainfall sensitivity of deciduousness in the central Indian forests through remote sensing

Comparison between old and new deciduousness metrics

At first, to check the reliability of the proposed metric, we estimated the deciduousness from the equation proposed by Cuba et al.¹⁴ (Eq. 1; referred as ‘old’) and the new metric proposed in this study (Eq. 2; referred as ‘new’) during the extreme and normal rainfall years. The results of dry and moist deciduous samples and 4 pheno-classes revealed an over-estimation and under-estimation of deciduousness with the old-metric, whereas the new metric revealed the accurate relative variability (Fig. 2b,c, Table S1). Table 1 provides the estimated deciduousness values from the old and new metrics for 22 homogeneous sample pixels representing four major vegetation types in the study area (refer Fig. 1 for their spatial locations and Fig. S1 for their annual growth profile). The litter fall information collected from literature revealed a higher litter fall quantity of 10–14.4 Mg Ha⁻¹ year⁻¹ for the moist deciduous forest^39,40,41,42 and lower litter fall quantities of 1–8.65 Mg Ha⁻¹ year⁻¹ and 5.63–7.84 Mg Ha⁻¹ year⁻¹ for the dry deciduous forest^42,43,44 and the semi-evergreen and evergreen forest⁴⁴ , respectively. The new metric showed a relatively similar variability in deciduousness to ground observations especially for the moist and dry-deciduous forests than the old metric (Table 1).

Further, the difference between the old and new metric was spatially checked and is shown at the center of Fig. 3, and the actual values are presented in the surrounding in eight different sub-set locations. The difference image denotes the under-estimated (70.76% of forest area) and the over-estimated (29.23% of forest area) deciduousness obtained by the old metric (Fig. 3). The under-estimated area observed was mainly in the moist forested regions of states- Chhattisgarh, Odisha, and Jharkhand states, whereas, the over-estimated area observed was mainly in the dry forested region of states—Madhya Pradesh, Maharashtra, Northern Chhattisgarh and some parts of Jharkhand (Fig. 3). The over- and under-estimations are with respect to the new metric, and not with the real in-situ measurements. However, the new metric is in good agreement with annual growth profiles of different vegetation types, and have positive relation with ground litter fall observations^{39,40,41,42,43,44}.

The deciduousness derived from these two metrics were also tested for their statistical significance using ANOVA (Table 2). In this test 800 stratified random samples belonging to different deciduous forests of different density classes for dry (2002), normal (2011) and wet (2013) years were used. It was found that the mean deciduousness values from the old metric were similar in the majority of the cases and different rainfall conditions. Hence, it could not be used for understanding rainfall impact on the deciduousness. On the other hand, the new metric performed better than the old metric in terms of its variability under (a) different rainfall conditions (p < 0.001), (b) different vegetation types (p < 0.001) and (c) different forest densities (p < 0.05). Thus, we used the new metric for further analysis to get a greater detail about the deciduousness behaviour of the Central Indian forests.

Spatio-temporal distribution and variation in deciduousness

We estimated Annual Deciduousness (AD) and Relative Annual Deciduousness (RAD) from 18 years (2001–2018) of MODIS NDVI data, and analysed their spatio-temporal variability in different rainfall scenarios i.e. during dry, normal and wet years (Fig. 4). For description purpose, we grouped deciduousness into four different classes such as: (1) 0–20% as low deciduousness (LD), (2) 20–40% as moderate deciduousness (MD), (3) 40–60% as high deciduousness (HD) and (4) above 60% as very high deciduousness (VHD). The intra- and inter-annual differences in spatial distribution and magnitude of deciduousness could be attributed to the effect of local, micro to macro-climatic regimes in the landscape.

From the rainfall anomaly pattern of 18 years (Fig. S2), it was observed that the year 2002 received the lowest rainfall, as 98.97% of the area was under negative anomaly and 47% of the area was under severe dry condition i.e., rainfall was much less than (< − 20%) the normal range. The year 2013 received the highest rainfall, where 45% of the area was under heavy rainfall (> + 20% of normal rainfall), and in the year 2011 more than 95% of the area received normal rainfall. So, these three years (2002, 2011 and 2013) were chosen as the representative years of extreme and normal conditions for further analysis of the deciduousness. During the dry spell around 12% of the study area experienced lower magnitude of deciduousness (Fig. 4a), especially in the ecoregions like Kathiar-Gir dry deciduous forests, Upper Gangetic plains, north-eastern parts of the Narmada valley, western parts of the Chhota-Nagpur and eastern parts of Eastern highlands. The hotspot pattern of VHD was observed only in the densely forested areas. In the year 2013 (wet year), healthy deciduousness was seen all over the study area with prominence in the Central Deccan Plateau (CDP) (Fig. 4c). A lower magnitude of deciduousness (~ 5%) was observed mainly in the non-deciduous forest types such as evergreen and semi-evergreen.

In the year 2011 (normal year), patches of VHD were observed in the CDP and some parts of the Chhota-Nagpur Region (Fig. 4b). Based on the long-term (18 years) mean deciduousness analysis around 36.85% of the forested area exhibited VHD (Fig. 4d), which was distributed as 11.5%, 8.82%, 8.13%, 5.16% and 3.24%, in states- Madhya Pradesh, Maharashtra, Chhattisgarh, Odisha and Jharkhand, respectively. The spatial distribution of long-term deciduousness (Fig. 4d) revealed a dominant deciduous nature of vegetation in this region. However, the high values of VHD were observed in the central-southern part of the study area and the low values in the evergreen and semi-evergreen forests of the Western Ghats and Similipal area of the Odisha state (Fig. 4d).

The yearly deciduousness images were classified into different categories and the variations observed during extreme years are listed in Table 3. The area statistics of deciduousness for all 18 years is provided in the supplementary data (Table S2). During the dry year, the forest area under VHD category was about 34.38% but in the normal year, it increased to 42.38%. In the wet year, it was the highest (51.06%) under VHD category. The area of deciduousness variability from 2001 to 2018 is presented in Fig. 5. During the study period (18 years), the mean deciduousness was observed to be fluctuating. A clear area reduction in VHD category during the dry years (i.e., 2002 and 2014), and increase during the wet years (2010 and 2017) was observed.

Spatio-temporal distribution and variation in relative deciduousness (RAD)

The spatial distribution of RAD derived from annual deciduousness for dry, normal and wet years, respectively is given in Fig. 6a–c. The benchmark deciduousness value at each pixel was computed from 18 years of annual deciduousness (Fig. 6d) and was used to estimate RAD. In the dry year (2002), a high RAD was observed in the CDP region, and a low RAD was observed in the northern and eastern regions. In the normal year (2011), the majority of vegetation in the northern region showed a high RAD and southeastern region showed a low RAD. During the wet period (2013), a high RAD was observed all over (~ 81% of the study area) the deciduous forest dominated area than the dry (~ 65%) and normal years (~ 75%).

The area of different RAD classes in percent (ranging from 0 to 100%) is given in Table 4 and the area of RAD classes for all 18 years is given in Table S3. In the dry year (2002), the area under the highest RAD class (90–100%) was about 3.64% which increased to 5.28% in the normal year. In the wet year (2013), the highest RAD area was 7.16%. Though the RAD variations showed a clear link with rainfall pattern, the soil moisture availability also plays a crucial role. Hence, a positive relationship with rainfall in all the deciduous vegetation could not be found out.

Spatio-temporal distribution of rainfall anomalies and their frequency

Figure 7a–c reveals the spatial distribution of rainfall anomalies in dry, normal and wet years, and the area statistics of these is given in Table 5. Even in the normal year some regions received low rainfall which is natural as the area is vast. The mean of the yearly rainfall anomaly of 18 years (Fig. S2) revealed that there was more negative anomaly than positive. Nearly 8% of the study area was under shortage of rainfall. Figure 7d shows the long-term average rainfall in the study area.

To analyze the spatial distribution of extreme rainfall at different locations, we estimated the frequency of rainfall anomaly events exceeding ± 25% and ± 15% at every pixel during 2001–2018. Figure S3a,c show the spatial pattern of the frequency of positive rainfall anomaly events (> + 25% and >  + 15%), and Fig. S3b,d reveal the frequency of negative rainfall anomaly events (< − 25% and < − 15%) in the study area. Overall, the states- Madhya Pradesh (MP) and Maharashtra (MH) experienced a greater number of extreme rainfalls than other states. Around 75% of the forested area in MP and 61% of the forested area in MH experienced >  + 25% rainfall anomaly at least for twice or more. Around 35% of the forested area in MP and 33% of the forested area in MH experienced < − 25% anomaly for at least twice or more in 18 years. Overall, around 20% of the forested area in the study region was susceptible to extreme rainfall anomaly.

Spatio-temporal distribution of deciduousness in different terrestrial ecoregions

Out of the total 15 terrestrial ecoregions (Fig. S5, classified on the basis of long-term climatic regimes and characteristic plant species⁴⁵), only four ecoregions: (1) Narmada valley dry deciduous forests (18%), (2) Chhota-Nagpur dry deciduous forests (11%), (3) the Eastern highlands moist deciduous forests (40%) and (4) Northern dry deciduous forest (6%) have the majority of forests (~ 75%) in the study area. Therefore, these four ecoregions were only considered for examining the impact of rainfall variability on the deciduousness in different years (Figs. S4, S5).

The area percentage of different deciduousness classes for these four ecoregions are provided in the supplementary Tables S4, S5, S6 and S7. Forests under VHD class in the Eastern highlands showed a significant influence of rainfall. For the wet years 2003, 2007, 2012 and 2013, the areas estimated under VHD class were 56%, 47%, 56% and 49%, respectively, which in the dry years 2002, 2004, 2014 and 2015 reduced to 37%, 35%, 19% and 35%, respectively. The Narmada valley region experiences frequent dry period, and during 2001–2018 the region experienced 7 severe dry periods (i.e., more than 75% area was under negative rainfall anomaly). During the wet years 2005, 2011 and 2013, VHD areas were 54%, 49% and 58%, respectively, which during the dry years 2002, 2004 and 2014 reduced to 30%, 39%, and 22%, respectively in this region. However, the reduction in the deciduousness was not significant during other dry years i.e., 2009, 2017 and 2018 in this region (refer Tables S5 and S9 for details) which requires further investigation.

A random deciduousness pattern was observed in the Chhota-Nagpur plateau and the Northern dry deciduous region. In these areas, rainfall dependency was not found significant. In the Chhota-Nagpur region, the VHD class areas were 35%, 19%, 26% and 55% during the wet years 2006, 2007, 2008, and 2011, respectively and the areas were 33%, 37%, 49%, 55%, and 17% during the dry years 2002, 2005, 2009, 2010 and 2014, respectively. In this region, the year 2010 was the driest year but in the same year a high deciduousness (~ 54% of the area) was observed. In the Northern dry deciduous region, the VHD class areas were 51%, 38%, 51% and 56% during wet years 2001, 2006, 2007 and 2013, respectively and the areas were 46%, 40%, 59%, 43% and 58% during the dry years 2002, 2004,2009, 2015 and 2016, respectively. The area of VHD class remained high in the Northern dry deciduous region irrespective of rainfall variability, and it might be due to high ground water table in this region. The Chhota-Nagpur region exhibited an unpredictable deciduousness response with respect to rainfall. Rainfall anomalies in these 4 ecoregions for all the 18 years are provided in the supplementary Tables S8, S9, S10 and S11.

Stratified analysis and sensitivity of deciduousness

Tropical forest species exhibit different phenological strategies to cope with the water shortage and leave shedding during the dry spells^46,47. Therefore, to understand the sensitivity of deciduousness towards micro-climatic effect and physical factors, the long-term (LT) mean of the deciduousness (18 years) was grouped into four classes of the deciduousness as mentioned earlier. The area distribution of these classes were: VHD; ~ 36.85%, HD; ~ 57.84%, MD; ~ 5.12% and LD; ~ 0.19%. Vegetation type-wise variations of the long-term mean deciduousness (Fig. 4d) revealed that out of ~ 29% of the major dry deciduous forest area, around 13% of the area was under VHD and ~ 15% of the area under HD class. Out of ~ 52% of the major moist deciduous forest area, ~ 18% of the area was under VHD and ~ 32% of the area under HD class.

The forest density plays an important role in identifying the status of forest health and growth. Thus, we used Vegetation Cover Fraction (VCF) data to classify forest into three different forest density classes: (1) 0–10% as open forest, (2) 10–40% as moderately dense forest and (3) above 40% as dense forest. We analysed the deciduousness in each of the density classes, and observed that in the open density forest class, out of 34.92% of the forested area only 5.5% of the area exhibited VHD. In the case of moderate density forest class, out of 60.88% of the forested area only 31% of the area exhibited VHD. In the dense forest class, out of 4.21% of the area only 0.32% of the area exhibited VHD. The areas under HD in open, moderate and dense forest classes were 26.32%, 28.76% and 2.79%, respectively. The analysis of long-term mean deciduousness with long-term mean VCF revealed a non-linear relationship (Fig. S6, R² = 0.98). In fact, the deciduousness increased with the increasing canopy density (upto VCF < 25) and then it started to decrease with the high canopy density. Also, the standard error was found to be higher in the lower density values (VCF < 40) than the higher values.

Topography plays an important role in shaping and driving the micro-habitat environment affecting species distribution, biodiversity, primary production and water resources^8,48,49 and hence the distribution of forested area and their deciduousness in different combinations of rainfall and elevation zones was analysed. We observed that around 90.65% of the forested area is located in > 200 m above mean sea level (amsl) and 57.37% of the forested area is in > 400 m amsl elevation zones. In different elevation zones of < 300 m, 300–600 m, and > 600 m amsl, the VHD exhibited was 8.95%, 22.73% and 5.16% of the forested area, respectively. Similarly, in these three elevation zones the HD exhibited was 12.63%, 31.59% and 13.62% of the forested area, respectively. The maximum deciduousness was observed in the elevation zone of 300–600 m amsl. Around 16.01% of the deciduous forested area received low rainfall (< 1000 mm) in which 0.95% area was located in the flat (FL) regions (< 100 m), 11.01% area under medium elevated (ME) region (200–500 m), 3.7% area under high elevated (HE) region (500–800 m) and 0.88% area under very high elevated (VHE) region (> 800 m). Around 42.95% of the forested area received moderate rainfall (1000–1500 mm) with the area distribution of 2.45%, 24.74%, 10.62% and 5.14% in different elevation zones like FL, ME, HE and VHE, respectively (Table S12). Around 41.04% of the area was under high rainfall region (> 1500 mm) with the area distribution of 5.44%, 19.65%, 10.51%, and 5.43% under FL, ME, HE and VHE zones, respectively. Out of all the forested area around 95% of the area exhibited high to very high deciduousness in which 35.24% area was observed in the elevation zone of > 500 m amsl.

Source: Ecology - nature.com