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Primary productivity connects hilsa fishery in the Bay of Bengal

Tropical hilsa shad (Tenualosa ilisha) contributes significantly to the society and economy of Bangladesh, India and Myanmar, but little is known about their habitats across the life cycle and their relationship with environmental drivers. This study describes spatial and temporal variability of productivity in the Bay of Bengal (BoB) relating to hilsa fishery. Decadal data on net primary productivity, nutrients (i.e. nitrate, phosphate and silicate) and zooplankton were collected from Aqua MODIS, world ocean database and COPEPOD respectively with spatial resolution 1°×1°. Moreover, monthly abundance of phytoplankton, hilsa catch and long-term catch dynamics were analyzed to determine the associations between variables. The present study was extended over 3.568 million km2 area, of which 0.131–0.213 million km2 area characterized as the most productive with net primary production of >2,000 mg C/m2/day, 0.373–0.861 million km2 area as moderately productive with 500–2,000 mg C/m2/day, and 2.517–3.040 million km2 area as the least productive with <500 mg C/m2/day which were consistent with field verification data. In case of nutrients, the Ganges-Brahmaputra-Meghna (GBM) delta was rich in nitrate and phosphate than that of the Ayeyarwady delta, while silicate concentration persisted high all over the northern BoB including the deltas. A peak abundance of phytoplankton was observed in GBM delta during the months of August-November, when ~80% of total hilsa are harvested in Bangladesh annually. Variations in seasonal productivity linked with nutrients and phytoplankton abundance are important factors for predicting hilsa habitat and their migration patterns in the deltaic regions and shelf waters of BoB. These results can be useful in forecasting potential responses of the hilsa in BoB ecosystem to changing global ocean productivity.

Data and software. Monthly gridded data during 1998-2018 on net primary productivity (NPP) were collected from Aqua MODIS from NOAA (https://coastwatch.pfeg.noaa.gov) in the area between 5°N-24°N and 79°E-100°E corresponding to the Bay of Bengal. Nutrients data (i.e. silicate, nitrate and phosphate) were collected from the world ocean database (https://www.nodc.noaa.gov/) for the same study domain. Zooplankton data were collected from the Coastal & Oceanic Plankton Ecology, Production, & Observation Database (COPEPOD) (https://www.st.nmfs.noaa.gov/copepod/). The NetCDF format data, which were level 3 products (e.g. SeaWiFS, MODIS and MERIS) with spatial resolution 1° latitude × 1° longitude grid 48 (Kodama et al. 2017), were downloaded and geospatially analyzed in ArcGIS software. Marine regions' data of International Hydrographic Organization (IHO) Sea Areas (version 3) for the Bay of Bengal were collected from http://www.marineregions. org/ and used as base map. The monthly net primary productivity was rated in terms of significance for hilsa habitat modeling ( Table 1). The spatial extension module was used for surface interpolation in ArcGIS. All maps and data were transformed into decimal degrees projection. Monthly phytoplankton abundance in the GBM delta was collected from Zafar 49 . Long term hilsa catch data of 1983-2018 was collected from the Department of Fisheries (DoF), Government of Bangladesh and used for the analysis of hilsa catch dynamics. Besides, monthly hilsa catch data were generated through focus group discussions (FGD) and key informant interviews (KII) with experienced fishers, fish traders and distributors in the coastal fishing villages 50 . Data integration. The shape file of study area was converted to grid with cell size of 0.0085 degree, equivalent to 4 km to prepare the mask layer with values 1 inside the mask and 0 outside. The geospatial tabular data of monthly net primary productivity were converted to grids by interpolation, maintaining the same geographic extent and cell size as the mask 51 . In map calculation, individual parameter grid layers multiplying with the mask layer thus resulted in masked grid layers of corresponding months. These parameter grid layers were then reclassified into three classes with <500, 500-2,000 and > 2,000 mg C/m 2 /day as most productive, moderately productive and least productive zones (Table 1) respectively, and then evaluated by adding respective months. The two seasons i.e. southwest monsoon (SWM) and northeast monsoon (NEM) were calculated by Eqs. (1 and 2) to develop productivity classification map for hilsa migration in the Bay of Bengal.  For this, a stratified simple random sampling was used in different habitats (e.g. estuary and delta, shelf water, and high sea) to identify 32 sites for subsequent assessment. Such an approach is appropriate to verify individual locations after the Aqua MODIS have been employed to assess spatial patterns of NPP in the Bay of Bengal. The productivity maps were verified by comparison between predicted productive zones and habitats of hilsa. For this purpose, geographical distribution map of hilsa by FAO, FishBase and GBIF (Global Biodiversity Information Facility), shads distribution by the Shad Foundation, and marine fishing zones of Bangladesh were used. In addition, participatory field visits, 120 semi-structured interviews and 60 focus group discussions were conducted with professional fishers in the coastal fishing villages of Cox's Bazar, Chittagong, Noakhali, Laxmipur, Bhola and Patuakhali 51 . In addition, direct observations of hilsa in 55 landing centers were useful and meaningful way to confirm hilsa yields across space and time. The purpose of verification was to find out whether the existing hilsa habitats are in line with productivity classes or not. In addition, members of the academia, researcher and extension manager were consulted to verify the results of geo-spatial models and the distribution of productivity classes of this study.

Results
net primary productivity (npp). The most productive zone is designated with higher NPP and the productivity ranking is presented in Table 2. Monthly and seasonal NPP classification for the study area are illustrated in geo-spatial model (Fig. 3) and summarized in Table 3. After integration of respective months, 0.168 and 0.145 million km 2 area were identified as the most productive zone with >2,000 mg C/m 2 /day during the southwest monsoon (May-Oct) and northeast monsoon (Nov-Apr) seasons respectively. There were 0.636 and 0.489 million km 2 moderately productive zone with 500-2,000 mg C/m 2 /day, and 2.763 and 2.934 million km 2 least productive zone with <500 mg C/m 2 /day ( Table 3). The most productive zone was extended over 520 × nutrients. Geo-spatial distribution of nitrate in the upper 10 m indicated that northern and eastern BoB including GBM and the Ayeyarwady deltas were devoid of nitrate (<0.20 μmol/L) during northeast monsoon, but improved situation was evident with >0.60 μmol/L in western BoB along the Indian coast and Sri Lanka during southwest monsoon (Fig. 4). During northeast monsoon the western part of the GBM delta became enrich with nitrate (~0.40 μmol/L) than the east (>0.10 μmol/L), but the Ayeyarwady delta remained with minimum nitrate. The amount of phosphate was >0.4 μmol/L in GBM delta and in western BoB, while higher concentration of >0.6 μmol/L was recorded in the coastal waters (80-120 km wide) of eastern India during southwest monsoon. There were 0.     www.nature.com/scientificreports www.nature.com/scientificreports/ January-February, followed by 2.49-2.51 mgC/m 3 in June-August and 1.58-1.70 mgC/m 3 in October-November (Fig. 6).
Productivity and hilsa fishery. Concurrent with the nutrient distribution, phytoplankton abundance in GBM delta had an enhanced concentration that also coincided with hilsa catch in the northern BoB at Bangladesh coast (Fig. 7). There were two peaks of phytoplankton in GBM delta of the northern BoB. The first peak of phytoplankton abundance with 3,085 cells/L was recorded in October, while the second peak with 2,470 cells/L was found in March. The peak period of plankton production in August-November was clearly linked to the highest hilsa catch (=~80% of 0.5 million tonnes annual catch), while the second peak in January-March can enhance growth and survival of hilsa juvenile that need scientific investigation. The model outputs for the productivity classes were accurately coincided with available maps of hilsa distribution from various sources such as FAO, FishBase, GBIF, IUCN, Shad Foundation and Discover life (Fig. 8). Acording to the fishermen, estuaries/deltas and nearshore waters are the most suitable zones for hilsa fishing. For that reason they operate hilsa gears within 80 m depth and a distance about 200 km from the coast. This fact suggests that suitable hilsa habitats are distributed in areas where primary productivity is typically high, varifying the model outputs for the productivity classes of this study.
Among 32 locations (i.e. 4 locations in the estuary and delta, 12 locations in the shelf water and 16 locations in the high sea) selected to verify the patterns of in-situ NPP distribution, the results of 27 locations were comparable to those Aqua MODIS data. Whereas, three locations in the estuary and delta (ID # 1, 2 and 4) and one location in the shelf water (ID # 15) were overestimated, and one location in the shelf water (ID # 9) was underestimated for NPP distribution. Thus, 84.4% of Aqua MODIS output did corroborate with field data ( Table 4). The varification error matrix for Aqua MODIS imagery shows the incorrectly classified locations, based on 32 field verification sites (Table 5). MODIS accuracy (MA) and field accuracy (FA) for each of the ranking classes showed that high sea had the highest value of MA and FA (1.0). The shelf water was well discriminated from the rest of the classes (MA = 0.83 and FA = 0.83). The estuary and delta was poorly represented in the sampling (4/32) with MA and FA of 0.05 and 0.25, respectively. The Kappa Index of Agreement (KIA) was generated to determine the degree of agreement between the two outputs. Its value ranges from −1 to +1 after adjustment for chance agreement. A value of 1 indicates that the two outputs are in perfect agreement (no change has occurred), whereas if the two outputs are completely different from one another, then Kappa value is −1. The Kappa (K) and Kendall's tau (T) coefficients had the value of 0.73 and 0.77 at 95% confidence, indicating that there is good agreement between field reference and Aqua MODIS data for NPP in the Bay of Bengal. We concluded that a high percentage of the pixels was classified correctly, better than would be expected by a completely random classification. www.nature.com/scientificreports www.nature.com/scientificreports/   www.nature.com/scientificreports www.nature.com/scientificreports/

Discussion
Geo-spatial distribution of nutrients in northern BoB is linked with runoff from GBM and the Ayeyarwady river systems signifying an upward pumping of nutrients from subsurface zone that overlaps with Madhupratap et al. 6 . Muraleedharan et al. 52 63 mentioned that rivers flowing into BoB might not contribute much to the inorganic nutrient pool as substantial part of the terrigenous materials are lost at its confluence due to oceanographic processes 64 . However, river discharges are associated with greater lithogenic fluxes in BoB 65 , where biogenic matters may rapidly scavenged along with terrigeneous origin and ballasts the materials in faster sedimentation to the deeper ocean 66,67 . Rivers and atmosphere can supply 20% nitrogenous inputs to BoB, while 80% nitrate comes to the surface from deeper waters by the cyclones, tidal surges, depressions or high speed winds occurring frequently in BoB during Oct-Nov and Mar-Apr 68 . In general, GBM and the Ayeyarwady deltas are categorized as eutrophic as levels of inorganic nutrients remain high throughout the year compared to the oligotrophic reference values (e.g. phosphate 0.011-0.077 µM, nitrate 0.087-1.900 µM, primary productivity 0.135-0.143 mg Cm −3 h −1 ) of Karydis 69 and Ignatiades 70 . Continental water flow, nutrients and organic matters originated from the upstream rivers maintain ecosystem functions in the deltas and supply food to the resident species including hilsa 71 . For instance, the crisscrossed rivers/tributaries of the GBM and Ayeyarwady deltas have an intimate relationship with surrounding land-based activities, such as agriculture, forest, wet meadow, human settlement, industrial development, port operation and tourism activities that play important roles on aquatic habitats. Some areas, such as the offshore deep waters and high seas, are not known as suitable hilsa habitats, but the reasons behind the fact need to uncover with scientific interpretation. Moreover, geo-spatial models can assess suitable habitats of hilsa across the life cycle 51 , which requires data on bathymetry, oceanographic processes, water quality, primary productivity and habitat characteristics specific to life stages. Some other methods including single nucleotide polymorphism technology (SNP), 87 Sr/ 86 Sr isotope ratios in otoliths 72 , allozymes and morphometric analysis 73 , and distinctive trait of the parasite fauna 74 , can provide information about the seasonal movements and residency of hilsa.
High productivity in the nearshore and deltaic waters of BoB integrates with high ambient nutrients. The distribution of NPP positively correlated with phytoplankton concentration (r = 0.75, p < 0.001) that implies that pelagic-neritic fishes like hilsa is expected to maintain their positions within productive areas for sustaining their growth and maturity. Hilsa fed on algae, diatoms, copepods, cladocerans, protozoa, rotifers and the larvae of molluscs 24,75 . The relationship between hilsa and the abundance of their diets suggests that habitat of hilsa is restricted up to the mixed layer depth (e.g. 20-40 m), which is possibly above the thermocline having maximum level of NPP. At this depth, phytoplankton, copepods, cladocerans and protozoa may be more intense 76   www.nature.com/scientificreports www.nature.com/scientificreports/ and more competently obtained. The present study indicate two peaks of phytoplankton in August-November and in January-March with the lowest abundance in April-July, and this data corresponded well with Choudhury and Pal 53 who reported maximum phytoplankton (1,611 cells/mL) in December and minimum (494 cells/mL) in July along the eastern Indian coast of the Bay of Bengal. Incidentally, spawning grounds of hilsa are located in GBM delta 77 and Ayeyarwaddy delta 78,79 , suggesting that these productive water bodies are suitable for hilsa to retain the larvae and juveniles, as illustrated in Fig. 9. In this connection, hilsa migrates to GBM delta for spawning in September-October 77 when the levels of NPP and abundance of phytoplankton are high in the system. In addition, coastal rivers and nearshore shallow waters in GBM deltaic region are also suitable nursery grounds for hilsa juveniles until March 80 . April onwards juveniles start seaward migration as the second phase of anadromous behavior and moves up to 250 km from the coast 81 with daily travels of about 71 km 82 . Moreover, Day 83 and Milton 84 mentioned that hilsa spends part of life in the sea but not far from the shallow coastal belt. However, operational limitations of gears made difficulties to determine the abundance, extent of seaward migration and fishing potential of hilsa in offshore and high seas due to lack of data and observations. Consequently, Hossain et al. 33 recommend for comprehensive study in determining the range of hilsa migration with spatial and  www.nature.com/scientificreports www.nature.com/scientificreports/ temporal distribution across the life cycle. It is evident from the present study that being plankton feeder, hilsa tend to follow plankton rich areas and keep moving from one place to another in search of productive zones and continue to grow. For example, sardine larvae requires 5.7-9.6 mg C/day of primary productivity 85 while maximum consumption rates for 1, 2 and 3 years old sardine are 0.042, 0.012 and 0.0049 g-prey g-fish −1 day −1 , respectively 22 . Thus, nursery ground of sardine larvae is located in high productivity zone, where adult sardine (1-3 years old) can live in relatively low productive zone, similar information are not available for hilsa that need to examine. Hilsa prefers zooplankton in early stages and shift towards phytoplankton in adult stage 86,87 . Diatom, green algae, and blue green algae represent phytoplankton menu of hilsa, while zooplankton menu comprises copepod, cladocera, rotifer, and ostracod 23,[88][89][90][91] . Adult hilsa comprised 97-98% phytoplankton with only 2-3% zooplankton 24,92,93 (Fig. 10).
The relationship between hilsa yield and NPP could be interesting to forecast how hilsa population in BoB might respond to future changes in productivity. The Galathea Expedition in 1950-1952 54 measured NPP 0.1-0.3 mg C m −2 d −1 in the deep sea and 0.01-2.16 g C m −2 d −1 in the shelf region of BoB 6 . Data of the subsequent studies from different regions of BoB are given in Table 6. Thaw et al. 55 proposed 300-500 g C m −2 year −1 as standard reference value of NPP for eutrophic region. The present study found NPP of >2,000 mg C m −2 day −1 in GBM and the Ayeyarwady deltas that coincided with Thaw et al. 55 , i.e. 2,590 ± 1,569 mg C m −2 day −1 at the Ayeyarwady delta. Conversely, a drop in primary productivity ranging 500-2,000 mg C m −2 day −1 was noted in the area below 22°N along the western and eastern boundary of BoB basin. The least productivity of <500 mg C m −2 day −1 was found in deeper part of BoB and the Andaman Sea. Though no specific trend was observed in www.nature.com/scientificreports www.nature.com/scientificreports/ seasonal variations, August-October represented with higher productivity in GBM delta, and lower productivity found in April-June that agrees with the findings of Routray and Patra 94 , Mohanty et al. 13 , Kumar et al. 2 and Radhakrishna et al. 95 . Phytoplankton production also follows similar pattern, i.e. phytoplankton abundance is high during August-October in GBM delta. Thus, deltas, estuaries and shelf regions of the northern BoB have higher NPP that may support rich neritic and pelagic fisheries. For instance, Sarmiento et al. 95 used coupled climate models to forecast responses of NPP in 2040-2060 and predicted that NPP in the sub-polar North Pacific could increase by 10-20% that could result 20% increase in carrying capacity of pelagic species, such as herring. In this context, distribution of NPP and nutrients in the northern BoB including mega deltas and shelf regions can explain and predict the distribution of pelagic fishes such as hilsa fishery in Bangladesh.
Data suggests that total hilsa catch in Bangladesh exceeds nine million tonnes since 1983-84. Specifically, hilsa catch has increased to 517,198 tonnes in 2017-18 from 146,082 tonnes in 1983-84, an annual growth of 7% in the past three decades. The marine waters of northern BoB share the major catch (65%), where the remaining portion fished from the Meghna estuarine system (33%) and from several rivers/tributaries (2%). As the instance in GBM delta, spatial variations in hilsa catch (Fig. 11) interpret habitat suitability and movement routes that can enhance conservation and management initiatives of hilsa fishery. The geographical distribution of hilsa along the coast of Bay of Bengal has been documented by FAO (Fischer and Whitehead 1974 96 ; Whitehead 97 ), IUCN 98 , shad foundation 99 , FishBase 100 , Global Biodiversity Information Facility (GBIF) 101 and Discover life 102 (Fig. 8). Moreover, their occurrences in the adjacent rivers were reported by Hora 103 , Motwani et al. 104 and Quereshi 105 . Interestingly, hilsa distribution maps with modelled year 2100 native range map based on IPCC A2 emissions scenario (Aquamaps) 106 has endorsed similar range for hilsa. Indeed, major efforts of hilsa fishing in Bangladesh have been concentrated within about 100 km from the coast 107 .
The majority of global oceanic data have been collected through cruises for specific periods which is expensive and not many research institutions and country can afford, especially the developing countries like Bangladesh. As a proxy, satellite imagery is useful for specific temporal resolution of any area during the routine observation schedule. For example, MODIS captures data in 36 spectral bands (0.4-14.4 μm wavelength) for 250-1000 m spatial resolutions with viewing swath of 2330 km and the revisit cycle one to two days. MODIS utilizes four on-board calibrators to provide in-flight calibration, whereas vicarious calibration enhances by using marine optical buoy. Thus, the shortwave infrared (SWIR) bands enable more robust atmospheric corrections in turbid coastal waters (Wang et al.) 108 , while the band around 685 nm is important for detection of phytoplankton fluorescence 109,110 (Gower et al., 1999;Hu et al., 2005). Thus, a comparison among the observation/cruises can enhance scientific understanding and interpret the validation process that we applied in this study. Nevertheless, primary productivity is important for pelagic fisheries recruitment, growth and yield, and found to largely controlled by variation in seasonal temperature gradient 56 , freshwater plume and haline stratification 40,43,44,57 , vertical transfer of nutrients from the subsurface levels into the euphotic zone 111 and dissolved oxygen, which were out of scope of this study. Therefore, further studies are necessary to investigate the multicriteria evaluation of above mentioned parameters to clarify the relationships of hilsa and its habitat conditions.