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GEOLOGY, ECOLOGY, AND LANDSCAPES INWASCON https://doi.org/10.1080/24749508.2022.2142186 RESEARCH ARTICLE a a b Sabrina Dookie , Sirpaul Jaikishun and Abdullah Adil Ansari a b Department of Biology, University of Guyana, Georgetown, Guyana; Professor and Dean, Faculty of Natural Sciences, University of Guyana, Georgetown, Guyana ABSTRACT ARTICLE HISTORY Received 7 June 2022 In mangrove forests, one of the most noticeable characteristics is the unique interplay between Accepted 26 October 2022 soil and water, which facilitates the movement of nutrients and sediments throughout their ecosystems. In this study, comparisons were made between the physicochemical character- KEYWORDS istics of soil (pH, EA, OC, EC, N, P, K, Mg, Ca, S, Fe, Zn, Cu, and Mn) and water (pH, temperature, Mangroves; ecosystems; and electrical conductivity) found in natural, degraded, and restored mangrove ecosystems Guyana; mangrove along the coastline of Guyana. Sampling was done using a Random Block Design (RBD) in six sediments study sites for six months. This study revealed that there were no significant variations in most of the physicochemical parameters found in soil and water within ecosystem type or season. However, notable differences were seen in the pH of water (6.45–7.88), as well as Fe (0.60–21.62 ppm, p < 0.05) and Mg (610–3944.67 ppm, p < 0.05) concentrations of soil within the three types of ecosystems. Seasonal differences were also evident in S, N, P, K, and Cu concentrations found within the mangrove soils. In both seasons, positive correlation findings (p < 0.05, R > 0.75) showed higher associations between soil physicochemical properties concerning ecosystem types, when compared to water parameters. Introduction Guyana’s fragile coastlines from strong currents by holding the soil together and preventing coastal erosion, Mangroves can be described as coastal marine forests which is perhaps their most essential function. During consisting of shrubs, palms, ferns, epiphytes, and trees. wet periods and stormy conditions, mangroves also Mangrove forests are found at the interface between protect inland areas and reduce damage (Guyana land and water; therefore, they are found in both the Forestry Commission, 2011). These unique forests are aquatic and terrestrial realms and play crucial roles in known to be the home of a diverse range of flora and both areas (Rog et al., 2016). These forests can with- fauna. Migratory shorebirds, waders, waterfowl, fishes, stand harsh environmental stresses and are uniquely mammals, crustaceans, and reptiles depend on man- adapted to marine and estuarine tidal conditions groves for nesting areas during high tides, for protec- (Alappatt, 2008; Lewis et al., 2016). Mangroves serve tion, and as a food source (Dookram et al., 2017). as a connection between freshwater and marine eco- Furthermore, mangrove trees disintegrate contami- systems, a source of nutrient flux into marine ecosys- nants play an important role in sequestering carbon tems, and a sink for contaminants (Maiti & and provide several products, including charcoal, fod- Chowdhury, 2013). The intertidal ecotones of estu- der, honey, tannin, medicine, and thatch (Ackroyd, aries and open coastlines, as well as the dynamics of 2010; Jaikishun et al., 2017). shifting water levels, temperatures, erosion, and pio- When mangrove stocks are depleted due to pollu- neer habitats, are where mangrove forest ecosystems tion or land removal, society itself becomes detached get their biological significance. Mangrove ecosystems from the flow of ecosystem services that it provides are described as diverse and have been adjusted to the (Moonsammy, 2021). The degradation of mangrove extreme conditions of highly salty, often flooded, soft, habitats manifests a decline in biodiversity richness, anoxic soils (Khairnar et al., 2009). These particular ecological diversity, and the production of services and circumstances lead to biodiversity hotspots in a small items (Friess et al., 2019). Despite their significance, number of nations (Getzner & Islam, 2020). mangroves are being degraded at a rate of 1–2% glob- Mangroves are known to provide several important ally annually, and the loss rate has escalated to 35% ecological goods and services to a number of countries, over the past 20 years. In general, the main threats to especially in Guyana. Timber extraction, critical coastal mangrove environments are climate change (sea level protection, flood management, and the sustainability of rise and changing patterns of precipitation) and fisheries and wildlife in coastal environments are exam- human impacts (urban growth, aquaculture, quarry- ples of such ecological goods and services (Guyana ing, and overharvesting of timber, fish, shellfish, and Forestry Commission, 2017). Mangroves defend CONTACT Sabrina Dookie firstname.lastname@example.org Department of Biology, University of Guyana, Georgetown, Guyana © 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group on behalf of the International Water, Air & Soil Conservation Society(INWASCON). This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 2 S. DOOKIE ET AL. crustaceans(Carugati et al., 2018). Biodiversity decline The entire coast of Guyana was fringed by mangrove is frequently correlated with habitat destruction. vegetation during colonisation. However, anthropo- According to theoretical ecology, ecosystem function- genic impacts have depleted or destroyed the majority ality can be influenced by biodiversity (Cardinale et al., of the forested sections (Winterwerp et al., 2013). 2006). Although the functionality of maritime ecosys- Natural erosional and accretive periods typical of the tems and biodiversity are frequently correlated, biodi- Guianas’ coastline (along the Amazon River moving versity loss could reduce the functioning of ecosystems towards the Orinoco River), as well as massive shifts in and, as a consequence, the potential of such ecosys- the mud banks, pose significant threats to Guyana’s tems to offer goods and services to humans (Polidoro mangroves (Ahmad & Lakhan, 2012). The emergence et al., 2010). This is especially true in tropical man- of man-made factors (through extensive coastal devel- grove habitats, which support a significant portion of opment) has encouraged cycles of erosion that have coastal biodiversity and will be affected by factors that continuously removed sections of the mangrove belt have manifested due to climate change (Alongi, 2015). (”NAREI”, 2019). Forest loss is primarily caused by Given their tidal composition, sea-level rise represents mining, logging, farming, and infrastructure construc- the principal concern. Nevertheless, it is also essential tion. During the period from 1990 to 2016, the to take into account variations in temperature, salinity, national deforestation rate peaked in 2012 (0.079%) and greenhouse gas concentrations. Furthermore, before dropping to 0.05% in 2016. Mining accounts fluctuations in precipitation can also affect the soil- for approximately 72% of the land area transformed water content and salinity, which can alter mangrove during this period, with forestry, agriculture, and uti- growth and species diversity (Lee et al., 2014). In lities accounting for the remaining 28% (Guyana Guyana, 33, 277 ha of mangroves currently cover Forestry Commission, 2017). Significant habitat loss coastal regions from Barima–Waini to East Berbice– as a result of land usage for urban development, farm- Corentyne, with the most intact forests residing in ing, aquaculture, improved infrastructure, as well as Region 1 (Barima–Waini) and the least intact in overharvesting of mangroves are all anthropogenic Region 4 (Demerara- factors currently affecting mangroves in Guyana Mahaica) ([EAME] Earth and Marine Environmental (”NAREI”, 2019). Consultants, 2018) (Figure 1). However, Guyana’s In mangrove ecosystems, there is a close connec- coastal belt is frequently exposed to considerable ero- tion between sedimentation and hydrodynamics. That sion as a result of strong currents. A 238 km-long is, soil and water movements are intricately linked and stonework and earthen barricaded sea defence struc- operate in unison. Tidal and wave-induced currents ture is regularly broken, causing economic damage to carry sediments to sediment deposits, while complex crop plants and homes due to encroaching seawater. wave motions, on the other hand, may cause Figure 1. Mangrove coverage (ha) along the coastline of Guyana, from regions 1–6 (Source: [EAME] Earth and Marine Environmental Consultants, 2018). GEOLOGY, ECOLOGY, AND LANDSCAPES 3 sediments between the roots to be remobilised by the rivers have been redirected for water storage, which water (Toorman et al., 2018). The morphodynamics of also affects the availability of freshwater in coastal mangroves is defined by dynamic interactions that areas (Lovelock et al., 2015; Sippo et al., 2016). occur between tidal flows and surfaces covered with Mangrove soils, on the other hand, can support life vegetation throughout mangrove margins (Spencer & since they provide a physical foundation for plant Möller, 2013). These interactions are crucial for anchorage, stabilisation, nutrient availability, water coastal protection, mangrove forest regeneration, for- filtration, waste recycling, and purification (Bomfim estry, conservation, and water pollution control et al., 2018). Mangrove soils are usually saline, oxygen- (Risanti & Marfai, 2020; Wang et al., 2010). Srilatha deficient, acidic, and often waterlogged (Dissanayake et al. (2013) describe how the physicochemical proper- & Chandrasekara, 2014). A sufficient supply of ties of water play an important role in organism dis- mineral nutrients is needed by mangroves. These con- tribution, inclusive of feeding and reproduction. As sist of micronutrients like iron, zinc, and manganese materials are moved between and within mangrove as well as macronutrients such as nitrogen, phos- forests with tidal movements, nutrient transfers invol- phorus, and potassium (Hogarth, 2015). Possible ving mangrove ecosystems and coastal waters are nutrient sources include precipitation, freshwater dis- regulated by the hydrology of these environments charge from river systems or the land, tide-borne (Hayes et al., 2018). Spatial and temporal variations soluble or particle-bound nutrients, animal importa- of water parameters such as pH, electrical conductiv- tion, nitrogen fixation by bacteria, and release from ity, and temperature profoundly affect the survival, organic material due to microbial decomposition development, and regeneration of mangroves (Wang et al., 2021). These sources can be significant (Kodikara et al., 2017). However, the dynamic char- or unimportant, depending on the specific situation. acteristics of water are directly influenced by physical, Although rainfall’s direct contribution to nutrient biological, and chemical processes like evaporation, input is probably negligible, mangrove regions that solar radiation, and marine climatic conditions receive a lot of rain typically receive a lot of freshwater (Ward et al., 2016). discharge from rivers. In addition, mangroves may Many recent studies have shown that environmen- also receive nutrients from regular tidal inundations tal factors can influence the physicochemical proper- (Alongi, 2020). Along the Guiana Shield, mangrove ties of water present in mangrove forests. The growth soils are created when sediments from erosion along of mangrove stands is influenced by parameters such the coastline or on riverbanks, as well as soils removed as pH, salinity (electrical conductivity), and tempera- from elevated areas, are moved through various water ture of the water in mangrove forests, which play sources ([NMMAP] National Mangrove Management a significant role in determining the species diversity Action Plan, 2012). Guyana’s coastal system is marked and productivity of the mangroves (Cabañas- by heavy mud deposits (from the Amazon) along with Mendoza et al., 2020; Peters et al., 2020). Due to huge concentrations of mud within its coastal waters variations in precipitation, river flow, evaporative (Winterwerp et al., 2007). In slow-moving “slings,” demand, and water usage by rival plants, fluctuations large amounts of soil (composed mainly of clay and in the pH and salinity of coastal settings are predicted silt) are brought along the coast from Northwest areas. to have a significant impact on species composition As these three-mile-long mud banks advance along and growth (Runting et al., 2016). Additionally, cli- the coastline, an observable trend emerges in which mate change is causing sea levels to rise and promot- as the crest of the bank moves, mud builds up in one ing extreme precipitation events in some areas, which region, following a period of degradation as an accom- affects the availability of freshwater in the coastal panying mud trough proceeds. The high banks tend to environment (Swales et al., 2019). Furthermore, cli- assist in the growth of mangrove forests, while the mate change affects sea surface density via fluctuations troughs appear to promote erosion and degradation in salinity and temperature. This can affect the buoy- ([NMMAP] National Mangrove Management Action ancy and dispersal of mangrove propagules, thus lim- Plan, 2012). iting the expansion and regeneration of forests along The physiographical location of mangroves, in the coastline (Van der Stocken et al., 2022). Strong addition to structure (mineralogy, organic content, evaporation (amplified by climate change) results in and metal concentrations) (Krauss et al., 2013; surface water with high temperature and salinity, Lunstrum & Chen, 2014), can affect the environmental which can intensify physical stress in mangrove trees functions and properties of soil. Soils and vegetation and seedlings due to the increased release of contami- interact strongly in mangrove ecosystems, resulting in nants and antioxidants in the water surrounding them the development of the former as well as the charac- (Aljahdali et al., 2021). The requirement to supply teristics of the plant environment (Perera et al., 2013). water for an expanding human population and their The physicochemical soil characteristics affect the associated agricultural and economic activities has development of mangrove plant species, which can decreased water movements to the coast since some compromise their growth and structure (Harahap 4 S. DOOKIE ET AL. et al., 2015). Mangrove soil texture, which typically The acidity of different soil types varies depending on ranges from very loose sand to very heavy clay, is their composition, rainfall amounts, and natural vege- described as a very stable feature that affects soil bio- tation. Soil pH, often referred to as the “chief soil physical properties and is long-term interconnected variable,” influences several biological, physical, and with soil fertility and quality (Yu et al., 2020). Soil chemical properties and events that influence the texture, which is linked to soil porosity, controls growth and biomass production of plants. Soil acidity water-holding capability, diffusion, and water move- is altered through leaching, degradation, crop absorp- + 2+ 2+ ment, both of which influence the soil’s overall health tion of basic cations (K , Ca , Mg , etc.), plant (Upadhyay and Raghubanshi, 2020). Factors such as residue deterioration, and plant root exudates topography, climate, hydrodynamic cycles, tidal gra- throughout different seasons. Soils with increased dients, and long-term ocean level shifts all influence CEC and a propensity for significant quantities of EA soil morphological and physicochemical characteris- (such as clays as well as those rich in OM) are well tics (Boto, 2018; Lugo & Medina, 2020). These factors buffered (Spargo et al., 2013). can cause variations in soil texture and moisture, pH, The ability of mangrove trees to access nutrients is salinity, cation exchange capacity (CEC), macronutri- regulated by a complicated system of interacting abiotic ents, micronutrients, carbon, and organic matter and biotic factors, and mangroves tend to opportunis- (OM) concentrations (Hossain & Nuruddin, 2016). tically use these nutrients when they become accessible Furthermore, mangrove soils may vary in different (Reef et al., 2010). According to Lovelock et al. (2005), ecosystems based on some environmental conditions mangrove soils have significantly lower nutritional such as nutrient availability, soil particle size, tidal availability, but nutrient content and accessibility vary effects, texture, moisture, soil fertility, and the extent considerably among mangroves as well as within their of disturbances (either natural or anthropogenic; habitats. Plants require calcium (Ca), magnesium (Mg), Dewiyanti et al., 2021). This can subsequently affect and sulphur (S) to thrive. Ca, Mg, and S concentrations the water composition, quality, salinity regime, and are adequate in soils with fair pH and good levels of pollutant removal capacity of a mangrove ecosystem organic matter. When calcium and magnesium are itself (Risanti & Marfai, 2020). Studies have shown added to the soil, they raise the pH, but sulphur from that disturbed areas (indicated by decreased numbers certain sources reduces it (Oldham, 2019). Calcium acts of mangroves) have the smallest OM levels along with as a counter-cation for both inorganic and organic low nitrogen (N) and potassium (K) concentration anions, as well as an intracellular transmitter that reg- levels, while undisturbed mangrove areas possess rich ulates response to numerous developmental indicators OM content, maximum N and K concentrations, as and environmental conditions (Thor, 2019). Sulphur well as the lowest calcium carbonate (CaCO3), pH, compounds are also used predominantly by sulphur- and salinity levels (Shahid et al., 2014; Alsumaiti & reducing bacteria (SRB) as well as sulphur-oxidising Shahid, 2018). bacteria (SOB), both of which are critical in mangrove Mangrove tree assemblages play a key role in metabolism (SamKamaleson & Gonsalves, 2019). The coastal carbon sequestration and budgeting, preser- sulphate ion, SO4, is the form that plants most often ving a greater proportion of the total environment’s absorb and is easily removed from soils by leaching. organic carbon (OC) stocks, especially in their rich soil Sulphate accumulates in heavier (higher clay content) OC pools (Sasmito et al., 2020). Allochthonous and subsoils as it is leached down into the soil (Oldham, autochthonous are the two primary sources of carbon 2019). In addition, magnesium plays an important role in mangrove soils (Sasmito et al., 2015; Stringer et al., in photosynthetic activities, enzyme activation, and 2016). Mangrove soils are frequently flooded, either ATP formation and usage (Cakmak, 2013), inclusive partially or entirely, and therefore have high OM con- of vital roles like phloem loading and photoassimilates tent, which influences pH as well as other physico- transport directly to sink organs like shoot tips, roots, chemical parameters such as oxide reduction and seeds. In general, magnesium uptake in plants is mechanisms (Cabañas-Mendoza et al., 2020; Naidoo, influenced by its concentration, behaviour, and the 2016). The pH of mangrove habitats can be affected by soil’s ability to replenish it in the soil solution (Yan dissolved calcium from shells, and brackish waters can et al., 2018). become alkaline as a result of offshore corals. Within the group of macronutrients, nitrogen (N), According to Hossain and Nuruddin (2016), man- phosphorus (P), and potassium (K) are the most funda- grove soils can be acidic or basic, with pH usually mental nutrients for plant development (White & ranging from 2.87 to 8.22. Active acidity and Brown, 2010). Plants use nitrogen to make amino exchangeable acidity are the two elements of soil acid- acids, which are then converted into proteins. It is ity. Exchangeable acidity (EA) is described as the a part of chlorophyll and plays an important role during number of hydrogen ions on cation exchange sites of photosynthesis (Reef et al., 2010). Furthermore, phos- clay (which is negatively charged) and organic mate- phorus, which is found in the soil as a phosphate ion, rial concentrations in the soil (Onwuka et al., 2016). aids plant mechanisms such as photosynthesis and GEOLOGY, ECOLOGY, AND LANDSCAPES 5 energy transfer. It also promotes early root develop- processes. Copper is needed for electron transfer in ment and growth, which allows plants to mature and photosystem II, mitochondrial and chloroplast pro- reproduce faster (Fageria, 2008). Almahasheer et al. cesses, carbohydrate processing, protein synthesis, as (2016) described nitrogen and phosphorus as two well as lignification of cell walls, among other enzyme nutrients that are most likely to restrict mangrove systems (Thanh-Nho et al., 2019). Clay composition, development. In mangrove soils, ammonium is the OM, and reduced conditions are all found to be most common source of nitrogen. Tree growth is pri- beneficial factors in mangrove soils’ capacity to marily aided by ammonium uptake in mangrove forests sequester metals (Nguyen et al., 2020). Sediments due to anoxic soil conditions (Reef et al., 2010). from tidal marshes with high clay and OM content Potassium (Kalium), absorbed by plants as potassium and higher negative redox potential can sequester ion (K ), is essential for a wide range of plant functions, more heavy metals (Almahasheer et al., 2018). As which includes the activation of numerous enzyme a result, mangrove habitats are highly efficient in systems involved in carbohydrate and protein synthesis. the accumulation of metals, which, when combined Potassium (in adequate concentrations) also decreases with their ability to maintain and immobilise soils, respiration, lowers the loss of energy, improves the results in soil elevations. This implies that mangroves plant’s water regime, and allows them to become resis- could play a significant role as metal filters and sinks tant to unfavourable conditions such as saline fluctua - within coastal communities (Nguyen et al., 2020). tions in the environment and drought (Fageria, 2008). Presently, there exist research gaps in understand- According to Kannappan et al. (2012), metals are ing the physicochemical characteristics of soil and absorbed and retained by the soils of mangrove for- water present in Guyana’s mangrove ecosystems ests from a variety of natural and anthropogenic due to a lack of published studies on the subject sources, including freshwater, saltwater, and sewage matter. Understanding what is required for the sur- runoff/leakage. Broadley et al. (2012) suggest that vival, conservation, and restoration of mangrove eco- metals may be classified as nutrients, trace metals, systems involves knowledge of soil morphology and or heavy metals depending on their degree of dense- the physicochemical characteristics of both soil and ness. Heavy metals, when used as micronutrients, water (Bomfim et al., 2018). It is also essential to provide plants with metabolic requirements. comprehend the extent to which soil and water char- However, their absence can impair the entire enzy- acteristics in mangrove ecosystems are affected by matic system and, as a result, the overall function of seasonality. Studies have shown that the physico- the plant (Singh et al., 2016). Several studies con- chemical parameters of soil and water have shown ducted by Kannappan et al. (2012), Madi et al. remarkable variations in wet and dry seasons, which (2015), and Thanh-Nho et al. (2019) have debated can affect the density, litterfall, flowering, fruiting, the dual roles of copper (Cu), iron (Fe), zinc (Zn), and nutrient uptake of the plant species found within and manganese (Mn), which can act as nutrients and/ them (Komiyama et al., 2019; Zhang et al., 2016). In or harmful elements in mangrove habitats. Zinc is an this study, we have monitored the extent of natural essential part of a variety of processes, including co- and anthropogenic disturbances occurring in six factoring enzymes, gene expression, biosynthesis of mangrove sites along the coastline of Guyana for six chlorophyll, auxin production, transduction of sig- months, which is summarised in Table 1. The types of nals and defence mechanisms, and is also recognised disturbances recorded during the period of data col- as an essential component in several dehydrogenases, lection within the mangrove ecosystem sites included proteinases, and peptidases (Hacisalihoglu, 2020). natural phenomena such as plant infestation, erosion, Similarly, iron (Fe) is essential in a variety of bio- storms, tides, and insect infestation. However, chemical and physiological mechanisms in plants anthropogenic activities were more prevalent than because it is a constituent of many important natural phenomena, which resulted in disturbances enzymes and is thus necessary for a variety of biolo- such as bark stripping, grazing, cutting, sand mining, gical processes (Schmidt et al., 2020). Plants need burning, fishing activities, garbage dumping, and iron for the production of chlorophyll and protein infrastructure development. Based on the level of in their leaves, the maintenance of their chloroplast disturbances, mangrove ecosystems were then classi- framework, and root development (Thanh-Nho et al., fied into three types within this study – degraded (D) 2019). However, a deficiency of iron is detrimental to (ecosystems exposed to a high number of human and chloroplasts because it affects the water-splitting natural disturbances/perturbations), natural (N) (eco- mechanism of photosystem II (PSII), which is systems with little to no disturbances/perturbations– responsible for supplying the electrons needed for pristine “old growth” trees), and restored (R) photosynthesis (Millaleo et al., 2010). Furthermore, (replanted ecosystems now recovering from distur- manganese (Mn) is active in protein and enzyme bances/perturbations towards a natural state). In structures that are photosynthetic in nature, making light of the aforementioned, the purpose of this it a significant contributor to a variety of biological study was to (i) examine the physicochemical 6 S. DOOKIE ET AL. Table 1. The extent of disturbances occurring within mangrove ecosystems under study. Location Ogle Montrose Hope Greenfield Novar Hopetown Ecosystem Type Restored Degraded Natural Extent of Disturbances Natural Plant infestation ** ** * * *** ***** Storms/ Tides ** ** ***** ***** ** ** Erosion ** ** ***** ***** *** ** Insect Infestation * * * * *** *** Anthropogenic Bark Stripping * ** **** **** * * Grazing * * ***** ***** *** ** Cutting ** ** ***** ***** *** ** Sand Mining * * * * * * Burning * ** ***** ***** * * Fishing activities *** ** ***** ***** *** *** Garbage Dumping ** *** ***** ***** *** ** Infrastructure Development ** ** ***** ***** * * Key: * – Very Low, ** – Low, *** – Moderate, **** – High, ***** – Very High. characteristics of soil and water found in mangrove chosen – two natural (N) (Novar and Hopetown), ecosystems that are natural, degraded, and restored; two degraded (D) (Hope and Greenfield ), and two and (ii) compare the physicochemical characteristics restored mangrove ecosystems (R) (Ogle and of soil and water found within these ecosystems in Montrose)(Figure 2). Avicennia germinans (black the wet and dry seasons. We believe that the results of mangrove), Rhizophora mangle (red mangrove), and this study will guide the scientific community Laguncularia racemosa (white mangrove) are the most towards a better understanding of soil and water common mangrove species found in these coastal properties present in natural, degraded, and restored areas (Guyana Forestry Commission, 2017; Jaikishun mangrove ecosystems in Guyana and the effect of et al., 2017). Along the seaward coast, monospecific seasonality on such properties. stands of A. germinans can be found. However, as one travels inland, the vegetation switches to A. germinans and L. racemosa mixed stands ([NMMAP] National Materials and method Mangrove Management Action Plan, 2012). The two selected natural mangrove ecosystems selected for Study sites data collection have mature “old growth” mangrove In this study, six locations in coastal Regions 4 forests which are affected by little to no disturbances. (Demerara-Mahaica) and 5 (Mahaica-Berbice) were The density of mangrove species found within these Figure 2. Map showing location of Study Sites along the coastline of Guyana(Source: Google Earth, 2020). GEOLOGY, ECOLOGY, AND LANDSCAPES 7 areas ranges from 798.33 to 1131.66 ha (Dookie et al., Water sample collection 2022). Furthermore, the two restored sites are com- Water present around the mangroves in each site prised of young mangrove forests that have not yet was collected once per month in each of the 18 attained full maturity. After complete degradation, plots and tested using a Yescom multi-parameter these sites have been artificially replanted since 2012 water tester. Water collection protocol followed as a part of the Guyana Mangrove Restoration Project, standards and guidelines outlined by Motsara and which was initiated to respond to and mitigate the Roy (2008): impact of climate change by protecting, restoring, and wisely using Guyana’s mangrove ecosystems (1) Water samples were carefully collected from ([MOA] Ministry of Agriculture, 2016). Due to strict each plot using sample cups. It was ensured monitoring and replanting programmes, these that no sediments were mixed with the water. restored ecosystems have attained the highest density (2) Sample cups were labelled with details, includ- (5986.03–20,954.17 ha) of mangrove species when ing collection time and location, to ensure that compared to the natural and degraded ecosystem samples were not misplaced. types. However, the two degraded mangrove ecosys- (3) Probes attached to the multiparameter water tems selected possess mature trees and are heavily tester were placed into the sample cups and impacted by severe natural and anthropogenic distur- the following parameters were recorded: bances (Table 1), which affect the diversity and dis- (a) pH (range: 0–14, resolution: ± 0.01 pH) tribution of mangrove trees and seedlings present (b) Temperature ( C) [range: −50°C to 70°C, reso- within the area. These ecosystems currently have the lution: ± 0.1°C] lowest density (360.00–2228.33 ha) among the three (c) Electrical Conductivity (EC) (mm/hos) [range: mangrove ecosystem types investigated (Dookie et al., 0.00–19.99 EC, resolution: ± 0.01 mm/hos] 2022). (4) Probes were washed and cleaned with distilled This study was conducted from August 2020 to water before testing was repeated. January 2021 in two seasons. Soil and water sample collections were done using a Random Block Design (RBD) every month for a total of six months – three Soil sample collection months in the dry season (DS) and three in the wet season (WS). A belt transect (120 m × 10 m) was A 21-inch soil sampler probe (with a tubular T-style placed from the inland boundary of the mangroves handle) was used to obtain uniform soil samples at going out to the shore was demarcated (Figure 3) and a depth of 0–40 cm, using the [EPA] Environmental was further divided into 10 smaller plots (10 m × Protection Agency (2009) procedure. The vegetation 10 m) in each transect. Three plots were randomly was removed from the ground where boring was to be selected along the length of the transect, one from done and the tip of the soil sampling probe was placed at each zone demarcated (Bharati, 2019; Jaikishun et al., an angle of 0° to 45° on the ground. The soil sampling 2017). The RBD was chosen to establish permanent probe was rotated once or twice and slowly retracted, and plots so that repetition of sample collection could be the soil sample was collected. Each sample was placed done each month, with each plot (from each of the into an appropriate sample bag and labelled. Soil col- three zones) having an equal chance of being selected lected from five different areas within every 10 m × 10 m transect was mixed within one container, and soil for sample collection (Lawrence et al., 2020). This samples from all three plots in one area were thoroughly ensured that the results obtained from samples were mixed to create one sample that was representative of an approximation of the results obtained if the entire that area. study site was sampled (Gumpili & Das, 2022). Figure 3. Random Block Design along Belt Transect used to demarcate plots in all six study sites. (Source: Bharati, 2019). 8 S. DOOKIE ET AL. ● Silver nitrate: 8.4 g of silver nitrate was dissolved Soil appearance and texture in 50 ml of distilled water. Soil texture and appearance were recorded using the ● Potassium Hydrogen Phthalate: 0.5106 g of method utilised by Overhue (2019): KHC H O was dissolved in 250 ml of water. 8 4 4 ● Phenolphthalein solution: 1 g of phenolphthalein (i) A sample of soil was taken, and the >2 mm was dissolved in 500 ml ethanol. fraction was manually separated. The sample ● Sodium hydroxide (0.1 M): 4.0 g of NaOH was taken was small enough to fit into the palm dissolved in 1 L of water. comfortably. (ii) A small amount of water was used to moisten the soil and knead it into a bolus. Standardisation using 1 M KCl (iii) The bolus was kneaded for 1–2 minutes until (i) Five drops of phenolphthalein solution were the soil was no longer sticky, and there was no titrated with silver nitrate to the first perma- visible improvement in plasticity. nent pink endpoint to obtain KCl acidity. (iv) The bolus was positioned between a clean, (ii) The endpoint occurred between 8 and 10 ml. moist hand’s thumb and forefinger, and the thumb was moved along the soil (shearing) to extrude a ribbon. A thin ribbon with Standardisation using sodium hydroxide solution a continuous thickness of 2 mm and a width of 1 cm was created. (i) To determine KCl acidity, five drops of phe- (v) Using a ruler, the length of the ribbon created nolphthalein solution were titrated with 0.1 M was measured and registered. Moulding the NaOH to the first permanent pink endpoint. bolus into rods additionally classified soils (ii) The endpoint occurred between 5 and 5.5 ml. with high clay content. Soil organic carbon (OC) The Walkley–Black chromic acid wet oxidation Soil pH method (Walkley & Black, 1934) was used to evaluate (i) Ten grams of soil were measured and mixed soil organic carbon: with 25 mm of distilled water. (ii) After stirring for 10 minutes, the mixture was Reagents. allowed to stand for 30 minutes. Potassium dichromate was oven dried for 1 h at (iii) The mixture was stirred once more for 2 min- 105°C, then cooled in a desiccator before being utes and after 30 minutes. weighed. (iv) The pH of the sample was then determined Potassium dichromate (0.1667 M): in a 1 L volu- using a pH meter, while it was stirred. metric flask, 49.04 g of potassium dichromate (0.1667 M) was dissolved in distilled water and made up to volume using water. Soil electrical conductivity (EC) Ferrous sulphate (0.5 M): 140 g was dissolved in (i) The same solution used for the pH was then distilled water, and 15 ml of concentrated sulphu- filtered. ric acid was added. The solution was cooled and (ii) A conductivity meter was used to take the EC diluted to 1000 ml in a volumetric flask. readings of the soil samples. Sulphuric acid (85%) Phenolphthalein solution: 5 g of phenolphthalein was dissolved in 95 mL of ethanol. Soil exchangeable acidity (EA) Exchangeable acidity was determined using a 1 M potassium chloride solution using the Sokolov Procedure Method (Sokolov, 1975). The soil was equilibrated (i) One gram of soil was weighed. with 1 M KCl, and the extract was titrated with silver (ii) Potassium dichromate (10 mL) was added. nitrate. The acidity so determined was referred to as (iii) The mixture was swirled for 1 minute. neutral or salt-exchangeable acidity. (iv) Twenty millilitres of concentrated sulphuric acid was added. Soil extracting solution: 1 M KCl (v) The mixture was swirled again for 1 minute and allowed to stand for the duration of Reagents 30 minutes. Potassium chloride (1 M): 74.55 g of KCl was (vi) Distilled water (200 ml) was poured into the dissolved in 1 L of distilled water. mixture. GEOLOGY, ECOLOGY, AND LANDSCAPES 9 (vii) Three drops of the indicator were added (3) Into each test tube, four drops of reagent NH4 (phenolphthalein). +-N no. 1, four drops of NH4+-N no. 2, and four (viii) The mixture was titrated with 0.5 M ferrous drops of NH4+-N No. 3 reagent were added. sulphate until a red colour change appeared. (4) After shaking the components of each test tube for 10 minutes, the reading was recorded. (5) The instrument was set to numerical value 1. NB The blank was inserted into the colorimetric slot, and the cover was closed. (1) The blank was made up of 10 ml of K CrO , 2 7 (6) Using the function key to enter mode 1, the up 20 ml of concentrated H SO , and 200 ml of 2 4 and down keys were pressed, respectively. The distilled water. instrument displayed 100 E, and testing began (2) Organic Carbon Calculation:HT % OC = (ml of when E disappeared. blank – ml of determination) × 0.399 (7) Using the function key, the instrument was adjusted to mode 3 before inserting the mixed standard solution. The cover was closed, and the up and down keys were pressed, respec- Extraction and determination of soil nutrients tively. The monitor displayed 50 E, and testing Concentrations of soil nutrients were determined continued when E disappeared. TM using a Harvesto Digital Soil Testing Mini Lab (8) The sample was inserted into the colorimetric through Atomic Absorption (AA) Spectroscopy. slot. (9) The cover was closed, and the results were recorded as displayed on the screen in mg/kg. Preparation of extraction reagent (1) Soil Extract: soil leaching powder was added to a beaker (1000 ml), 200 ml of distilled water was added to the dissolved content and made b) Determination of soil available phosphorus (P) up to 1000 ml using distilled water. (1) Three disposal test tubes were labelled as the (2) Preparation of Standard Solution Reagent: blank, standard solution, and sample 1, after Mixed Standard Solution: A 1 ml mixed stan- rinsing with distilled water. dard solution was added to a 100 ml volume (2) 2 ml distilled water, 2 ml mixed standard metric flask and was made up to 100 ml with 4+- solution, and 2 ml sample filtrate were added soil extract NHP N. into test tubes labelled as the blank, standard solution, and sample 1, respectively. Extraction of soil nutrients (3) Ten drops of soil P No. 1 reagent were added (i) Two grams of air-dried ground soil was added to each test tube carefully to prevent the for- to a 100 ml beaker. mation of air bubbles. (ii) One teaspoon of soil decolouriser was added (4) One drop of soil P reagent No. 2 was added, to the beaker. and the test tubes were kept standing for (iii) Forty millilitres of soil leaching agent was 10 minutes before the reading was taken. added to the beaker. (5) The instrument was set to numerical value 6. (iv) The beaker was placed on the shaker for The blank was inserted into the colorimetric 3 minutes. slot, and the cover was closed. (v) The contents were filtered. (6) Using the function key to enter mode 1, the up (vi) After filtration, the filtrate was immediately and down keys were pressed, respectively. The covered; otherwise, exposure to air can easily instrument displayed 100 E, and testing began lead to nitrogen loss. when E disappeared. (vii) All containers were labelled appropriately. (7) Using the function key, the instrument was adjusted to mode 3 before inserting the mixed standard solution. a) Determination of soil available nitrogen (N) (8) The cover was closed, and the up and down keys were pressed, respectively. The monitor (1) Three disposal test tubes were labelled as the displayed 50 E, and testing continued when E blank, standard solution, and sample 1, after disappeared. rinsing with distilled water. (9) The sample was inserted into the colorimetric (2) 2 ml distilled water, 2 ml mixed standard solu- slot. tion, and 2 ml sample filtrate were added into (10) The cover was closed, and the results were test tubes labelled as the blank, standard solu- recorded as displayed on the screen in mg/kg. tion, and sample 1, respectively. 10 S. DOOKIE ET AL. (iv) A 2 ml pipette was used to draw 2 ml each of c) Determination of soil available potassium (K) the blank (extractant), standard solution, and (1) Three disposal test tubes were labelled as the test solution, and they were placed in three blank, standard solution, and sample 1, after small reaction flasks to add three drops of rinsing with distilled water. CU5: Cu masking agent, five drops of CU3: (2) 2 ml distilled water, 2 ml mixed standard Cu strengthening colour agent, and three solution, and 2 ml sample filtrate were added drops of CU4: Cu colour developing agent. into test tubes labelled as the blank, standard (v) The mixture was then shaken well, and after solution, and sample 1, respectively. standing for 10 minutes, it was transferred to (3) Four drops of soil K No. 1 reagent were placed three cuvettes for measurement. in each test tube and shaken up and down for 1 minute. (4) Four drops of soil K reagent No. 2 were added e) Determination of soil available iron (Fe) to each test tube before taking the reading. (1) Soil-available iron extractant: 8.2 ml of concen- (5) The instrument was set to numerical value 6. trated hydrochloric acid (analytical grade) was The blank was inserted into the colorimetric added to distilled water to dilute to 1000 ml and slot, and the cover was closed. shaken thoroughly. (6) Using the function key to enter mode 1, the up (2) Preparation of soil-available iron standard and down keys were pressed, respectively. The solution: FE2 (1.0 mL): A 100 mL volumetric instrument displayed 100 E, and testing began flask was filled with a standard reserving solu- when E disappeared. tion, which was then diluted with a soil- (7) Using the function key, the instrument was available iron extractant. adjusted to mode 3 before inserting the (3) Five grams of air-dried soil sample or a 10.0 × mixed standard solution. (1 + water content) g fresh soil sample was (8) The cover was closed, and the up and down weighed and added to a 100 ml Erlenmeyer keys were pressed, respectively. The monitor flask. One scoop of decolouring agent and displayed 50 E, and testing continued when 20 ml of soil-available iron extractant were E disappeared. added and shaken for 30 minutes at a frequency (9) The sample was inserted into the colorimetric of 220 times/min. The extraction temperature slot. was about 25°C, and the filtrate was filtered (10) The cover was closed, and the results were with quantitative filter paper in a dry and recorded as displayed on the screen in mg/kg. clean Erlenmeyer flask. (4) 2 ml of blank (extractant), 2 ml of normal solution, and 2 ml of test solution (1.0 ml of d) Determination of soil available copper (Cu) test solution + 1.0 ml of extractant) were drawn (1) Soil-available copper extractant: 8.2 ml of con- with a pipette and deposited in three small centrated hydrochloric acid (analytical grade) reaction flasks. The following agents were dissolved in 1000 ml of water. added: drops of FE4: Fe deoxidiser agent, two (2) Preparation of the soil-available copper stan- drops of FE3: Fe strengthening colour agent, dard solution: A 1 ml pipette was used to and four drops of FE5: Fe colour developing draw 1.0 ml of the Cu: Cu standard reserving agent. solution into a 100 mL volumetric flask, and an (5) The mixture was shaken well and transferred to extractant was used to dilute the volume in three cuvettes for measurement after 20 minutes a volumetric flask (100 ml). of reaction. (3) Determination of soil available copper: pre- paration of a test solution for soil nutrients: f) Determination of soil exchangeable calcium (i) Five grams of air-dried soil sample was (Ca) and magnesium (Mg) weighed and placed into an Erlenmeyer flask (100 ml). (1) Soil-exchangeable calcium and magnesium (ii) One scoop of decolorising agent and 10 ml of extractant: 77.09 g of exchangeable calcium soil-available copper extractant were placed and magnesium extractant solids were weighed into the flask and then shaken (using and dissolved with an appropriate amount of a shaker) at a frequency of 220 times/min for water and placed into a volumetric flask 30 minutes. (1000 ml) and shaken evenly with water. (iii) The mixture was then filtered with filter paper (2) Soil-exchangeable calcium and magnesium in a dry and clean Erlenmeyer flask, which was developer: 3.73 g of the developer powder was the available copper test solution. weighed and dissolved in carbon dioxide-free GEOLOGY, ECOLOGY, AND LANDSCAPES 11 distilled water and was heated to dissolve to flask, and the volume with soil available man- a constant volume of 1 L. ganese extractant was set, which is a standard (3) Five grams of air-dried soil sample was weighed solution containing Mn2 + 20 mgLP-1P. This and placed into a triangular flask. 50 ml of soil- standard solution was prepared when used, and exchangeable calcium and magnesium extrac- care was taken when sealing. tant were added and shaken for 5 minutes on (3) 5 g of air-dried soil 2.5 × (1+ water content) a shaker at a frequency of 220 times per minute. g fresh soil sample was weighed and placed in The mixture was removed and filtered in a dry a 100 ml Erlenmeyer flask. 25 ml of soil- Erlenmeyer flask with quantitative filter paper. available manganese extractant was added and This filtrate is the soil solution that was tested. shaken on a shaker at a frequency of 220 rpm (4) Determination of the total amount of calcium for 10 minutes, then filtered with quantitative and magnesium in soil: 2 ml of the test solution filter paper. The filtrate was the test solution. was pipetted into a reaction flask, and four (4) 10 ml each of the blank solution (extractant), drops of GM4: Ca & Mg masking agent, 10 standard solution, and test solution were taken, drops of GM5: Ca & Mg mask-acid agent, 1 and 1.0 ml of concentrated sulfuric acid, 1.0 ml drop of GM9: Ca & Mg deoxidiser agent, and 1 of concentrated phosphoric acid, 10 ml of dis- drop of GM7: Ca & Mg indicator agent were tilled water, and 0.5 g of MN2: Mn colour added. After shaking, GM2: Ca & Mg colouring developing agents were added to it. The mix- development agent was added dropwise. The ture was placed on an electric stove and heated flask was shaken while adding it until the solu- in a fume hood. The yellow colour in the blank tion in the flask turned from red to blue-purple. solution has faded. The standard solution and The number of drops of developer used (d1) the test solution appeared purple-red. The mix- was recorded. ture was then taken off and placed aside. (5) Determination of soil-exchangeable calcium: (5) Ten millilitres of distilled water was added, 2 ml of the test solution was pipetted into the reheated, boiled, and held for approximately 3 reaction flask. Four drops of GM4: Ca & Mg minutes. It was then removed, cooled, and masking agent, four drops of GM6: Ca & Mg placed into a 50 ml volumetric flask. It was colour strengthening agent, one drop of GM9: diluted to volume using water and shaken up. Ca & Mg deoxidiser agent, and one drop of At constant volume, 2 ml of each of the blank, GM7: Ca & Mg indicator agent were then standard, and test solutions were drawn at con- added. After shaking, GM2: Ca & Mg colouring stant volume into three clean cuvettes and mea- development agent was added. The flask was sured on the machine. shaken while dripping until the solution turned from red to purple. The number of drops of h) Determination of soil available zinc (Zn) developer used (d2) was recorded. (1) Soil effective zinc extractant: 8.2 ml of concen- Calculation of titration results: trated hydrochloric acid was added to a 1000 mL a) Exchangeable Ca content = 200*d2 (mg/kg) = d2 volumetric flask containing distilled water to cmol/kg make the volume constant and shaken well. b) Exchangeable Mg content = 122 (d1-d2) (mg/ (2) Soil available zinc standard solution: A 1 ml kg) = (d1-d2) cmol/kg pipette was used to draw 0.5 mL of ZN1: Zn standard reserving solution and it was placed in a 100 ml volumetric flask, after which it was g) Determination of soil available manganese diluted to volume with acidic soil available zinc (Mn) extractant containing ZnP2+ P0.5 μg/ml. (1) Soil-available manganese extractant 38.5 g of (3) Soil zinc colour developer: one tube of the MN3: Mn leaching agent A was weighed and colour developer was taken, and 2 ml of dis- dissolved in water, diluted to 500 ml, and shaken tilled water was added to dissolve it. It was then evenly. This solution can be stored for a long poured into a 100 ml volumetric flask to make time. When testing the soil, the above solution the volume constant. can be absorbed according to the amount of (4) Five grams of air-dried soil sample or 5.00× (1+ extract used, and 0.2 g per 100 ml of the MN1: water content) g fresh soil sample was weighed Mn leaching agent B was added and shaken well. and placed in a 100 ml conical flask. About 25.00 The extractant was prepared whenever used. ml of soil-effective zinc extractant was then (2) Soil available manganese standard solution – added. 4.0 ml of MN4: Mn standard reserving solution (5) The extract was filtered using filter paper in was absorbed and placed in a 100 ml volumetric a dried Erlenmeyer flask (after 30 minutes of 12 S. DOOKIE ET AL. shaking), which is the test solution for soil- Results efficient zinc nutrients. The physicochemical parameters of soil and water (6) A 2 ml pipette was used to draw 2.00 ml each of collected during the six-month period were log10 the blank (extract solution), standard, and test transformed to stabilise variation among groups and solution into the reaction flask, and 10 drops of to shift the datasets towards normality. The datasets stabiliser were added to the colorimetric tube TM were analysed using Microsoft Excel and containing the test solution, and the mixture TM RStudio programming software. The results were was shaken well. summarised as follows: (7) Five drops of ZN4: Zn masking agent were then added and shaken well. (8) Five drops of ZN2: Zn colour-developing agent Water parameters were added and shaken well. The mixture was allowed to stand for 10 minutes and was then Mangrove ecosystem type measured on the machine. One-way ANOVA analyses, conducted at a significance level of p < 0.05, indicated significant differences only in the average pH values found within i) Determination of soil available sulphur (S) the three mangrove ecosystem types. A Tukey test conducted at a level of significance of p < 0.05 on pH (1) Soil available sulphur extractant: 2.12 g of S1: values [MSE = 3.1e-04, Df = 12, M = 0.93, CV = 1.91, S leaching agent was weighed and dissolved MSD = 0.05] showed significant differences between with an appropriate amount of water, trans- Hopetown (N), Montrose (R), Hope (D), and ferred into a volumetric flask (500 ml), and Greenfield (D). diluted to volume with the use of distilled water. The mixture was then shaken evenly. (2) Preparation of soil-available sulphur standard Seasonality solution: The 1.0 mL of S2: S standard reserving The average EC values of water samples ranged from solution was pipetted into a 100 ml volumetric 0.47–0.81 mmhos/cm (DS) to 1.02–1.42 mmhos/cm flask and diluted with the extractant. (WS)(Table 2) with no significant differences within (3) A triangular flask was filled with 5.0 × (1+ water seasons (one-way ANOVA test with significance content) g of fresh soil sample or 0 g of air-dried level: p > 0.05). Furthermore, a paired-sample T-test soil. 25 ml of soil-available sulphur extractant was indicated that there was a significant difference added, placed on a shaker for 5 minutes, and between the average measurements obtained in both filtered with quantitative filter paper to get the seasons in all mangrove ecosystems [M = −0.17, t filtrate. This filtrate was used to simultaneously (5) = −10.16, p < 1.582e-04]. The average pH values determine the available sulphur in soil samples. among water samples ranged from 6.86–8.17 (DS) to (4) 2 ml each of the blank solution (extractant), 6.62–8.48 (WS). Significant differences in the means standard solution, and test solution were of pH values were seen in both seasons (paired- drawn into, respectively, labelled tubes. sample T – test at a significance level of p < 0.05). (5) Two drops of S3: S mask-acid agent, eight drops Lastly, temperature values obtained varied from of S5:S masking agent, three drops of S4:S sta- 29.34°C to 30.96°C (DS) to 28.77–29.37°C (WS) biliser agent, and eight drops of S6:S turbidity (Table 2). A paired-sample T-test further confirmed agent were added and shaken well. significant differences [M = 0.02, t (5) = 3.35, (6) The mixture was allowed to stand for 5 minutes p = 0.02] between the average temperature values and transferred to three clean cuvettes, after obtained in both seasons within the different man- which it was measured on the machine. grove ecosystems. Table 2. Physicochemical parameters of water samples from six mangrove sites (data expressed as Mean ± SEM). Physicochemical Parameters of Water EC (mmhos/cm) pH Temperature ( C) Location Ecosystem Type Dry Season Wet Season Dry Season Wet Season Dry Season Wet Season c d Ogle R 0.81 ± 0.42 1.42 ± 0.00 6.86 ± 0.37 6.62 ± 0.01 29.50 ± 0.24 29.23 ± 0.05 abc c Montrose R 0.47 ± 0.47 1.03 ± 0.00 7.37 ± 0.08 7.10 ± 0.03 29.34 ± 0.80 29.34 ± 0.04 abc b Hope D 0.47 ± 0.47 1.42 ± 0.00 7.24 ± 0.13 7.83 ± 0.01 30.92 ± 1.69 28.77 ± 0.03 bc ab Greenfield D 0.65 ± 0.41 1.42 ± 0.00 7.17 ± 0.18 8.02 ± 0.00 30.92 ± 2.08 28.99 ± 0.03 a a Novar N 0.47 ± 0.47 1.42 ± 0.00 8.17 ± 0.14 8.48 ± 0.02 30.66 ± 1.11 29.37 ± 0.02 ab b Hopetown N 0.47 ± 0.47 1.02 ± 0.00 7.94 ± 0.05 7.96 ± 0.02 30.96 ± 2.21 28.97 ± 0.05 *Letters in table show significant pairwise associations using Tukey HSD Test. GEOLOGY, ECOLOGY, AND LANDSCAPES 13 Correlation among water parameters and pH, Salinity (EC), exchangeable acidity (EA), and seasonality organic carbon (OC) Pearson correlation tests were conducted to measure Mangrove ecosystem type. One-way ANOVA (signif- the strength and extent of association between the icance level: p < 0.05) results revealed insignificant water parameters investigated in this study and the differences in the means of OC, pH, EA, and EC season type (wet or dry). The Pearson correlation found in the soil samples concerning ecosystem type. coefficients established for water parameters showed a weak, positive relationship between temperature and Seasonality. Within the six mangrove areas, OC per- pH [p = 0.38, R = 0.44] in the dry season, while other centages ranged from 2.39–3.71% (DS) to 0.96–1.99% associations showed negative correlations in both sea- (WS). Furthermore, the mean EC values shifted from sons (Figures 4a and 4b). 1.16–1.29 mmhos/cm (DS) to 1.42 mmhos/cm (con- sistent in WS). pH values ranged on average between 6.45–7.338 (DS) and 6.49–7.338 (WS), while the EA of Soil parameters soils fluctuated between 0.09–0.22 (DS) and 0.09–0.12 meq/100 g soil (WS) (Table 3). However, the paired Soil texture and appearance sample T-test revealed statistically significant differ - Soil samples collected from restored areas were com- ences between the two seasons in the mean values of posed of heavy clay (ribbon length: ≥75 mm, approx- OC [M = 1.46, t (5) = 4.53, p = 6.248e-03], EC imate clay content: ≥50%), while degraded mangrove [M = −0.19, t (5) = −8.51, p = 3.684e-04], and EA ecosystems consisted of light, sandy clay (ribbon [M = 0.05, t (5) = 2.55, p = 0.05] among the three length: 50–75 mm, approximate clay content: 35– mangrove ecosystem types. 40%). However, the texture of soil samples collected from the natural mangrove ecosystems varied as sandy soils (ribbon length: nil, approximate clay content: Soil nutrient composition <10%) were found in Novar, while heavy clayey soils Mangrove ecosystem type. A one-way ANOVA test, (ribbon length: ≥75 mm, approximate clay content: conducted at a significance level of p < 0.05, revealed ≥50%) were found in Hopetown. The soil textures in statistically significant differences only in Mg concen- all three mangrove ecosystem types remained consis- tration in the dry season only [F (5,17) = 14.94, tent in both wet and dry seasons. p = 8.52e-05] among the three ecosystem types. Figure 4. Correlation Matrix for Physicochemical Parameters of water in (a) dry season and (b) wet season. Table 3. Summary of results of OC, EC, pH and EA of soil samples (data expressed as Mean ± SEM). Physicochemical Parameters of Mangrove Soil OC (%) EC (mmhos/cm) pH EA (meq/100 g) Dry Wet Dry Wet Dry Wet Dry Wet Location Ecosystem Type Season Season Season Season Season Season Season Season Ogle R 2.52 ± 0.13 1.49 ± 0.71 1.17 ± 0.25 1.42 ± 0.00 6.45 ± 0.06 6.66 ± 0.48 0.19 ± 0.06 0.12 ± 0.03 Montrose R 3.59 ± 1.22 1.92 ± 0.90 1.29 ± 0.13 1.42 ± 0.00 6.65 ± 0.24 6.49 ± 0.03 0.16 ± 0.03 0.12 ± 0.03 Greenfield D 2.39 ± 0.92 1.59 ± 0.46 1.20 ± 0.22 1.42 ± 0.00 7.13 ± 0.49 7.86 ± 0.59 0.22 ± 0.03 0.09 ± 0.00 Hope D 3.71 ± 1.34 0.96 ± 0.45 1.28 ± 0.14 1.42 ± 0.00 7.26 ± 0.43 7.88 ± 0.70 0.09 ± 0.05 0.09 ± 0.00 Novar N 2.92 ± 1.41 1.06 ± 0.27 1.25 ± 0.17 1.42 ± 0.00 7.38 ± 0.43 7.87 ± 0.55 0.16 ± 0.03 0.09 ± 0.00 Hopetown N 2.91 ± 1.09 1.99 ± 0.00 1.16 ± 0.26 1.42 ± 0.00 7.33 ± 0.35 7.22 ± 0.56 0.09 ± 0.05 0.09 ± 0.00 14 S. DOOKIE ET AL. Furthermore, a Tukey test on Mg concentrations (DS) Novar pt(N) and the highest in Ogle (R). Lower concen- [MSE = 0.02, Df = 12, M = 3.16, CV = 5.02, tration values were present in soils found in natural and MSD = 0.43] further revealed that average Mg con- degraded mangrove ecosystems, while higher values were centrations obtained from Montrose (R) (3.59 > 0.43), found in the restored mangrove stands (Table 4). Ogle (R) (3.39 > 0.43), and Hope (D) (3.39 > 0.43) Moreover, phosphorus concentration values [ranging were similar to each other but differed significantly from 147.17 ppm (Greenfield (D))−298.75 ppm from Hopetown (N) (2.91 > 0.43), Greenfield (D) (Montrose (R)) (DS) to 52.46 ppm (Ogle (R))−243.22 (2.88 > 0.43), and Novar (N) (2.78 > 0.43)(Table 4). ppm (Hope (D)) (WS)] varied between mangrove eco- Furthermore, the one-way ANOVA test also indicated systems and seasons (Table 4). A similar trend was also significant differences in the mean Fe concentration observed with potassium concentrations in the dry sea- values (DS only) (F (5,17) = 3.47, p = 0.04) in Novar son [111.38 ppm (Novar (N))–297.31 ppm (Ogle (R))] as (N), Montrose (R), Greenfield (D), and Hopetown (N) well as the wet season [120.77 ppm (Hope (D))–337.93 [Tukey Test: MSE = 0.14, Df = 12, M = 0.76, ppm (Ogle (R))] among the three types of mangrove CV = 49.46, MSD = 1.02] (Table 5). ecosystems (Table 5). In both wet and dry seasons, N, P, and K concentrations were above the critical limits (N: <240 ppm, P: >96 ppm, and K: >200 ppm), with restored Seasonality ecosystems retaining higher concentrations of N and Mean values of Ca ranged from 2800.00 ppm K (Table 4). However, paired T-tests (p < 0.05) conducted [Montrose (R)] – 6533.33 ppm [Hope (D)] in the dry season and 2533.33 ppm [Hope (D)] – 5000.00 showed statistically significant differences in the mean ppm [Hopetown (N)] in the wet season, while average concentrations of N [M = −0.25, t (5) = −5.14, p = 3.636e- Mg concentrations ranged from 610.00 ppm [Novar 03], P [M = 0.36, t (5) = 4.67, p = 5.48e-03] and (N)] – 3944.67 ppm [Montrose (R)] and 610.00 ppm K [M = 0.33, t (5) = 3.39, p = 0.02] between the two [Hope (D)] – 2414.00 ppm [Montrose (R)] in the dry seasons. and wet seasons, respectively. Furthermore, Lastly, Zn concentration values ranged from 0.55– S concentration values fluctuated between 111.38 2.60 ppm (DS) to 1.34–2.80 ppm (WS), while Mn ppm–287.97 ppm (DS) and 159.90 ppm–406.07 ppm concentration values fluctuated between 57.91–85.85 (WS), with the lowest concentrations found in Novar ppm (DS) and 30.90–84.19 ppm (WS) among the (N) and highest in Montrose (R) (Table 4). Ca, Mg, ecosystem types (Table 5). Concentrations of copper and S concentrations of soils found in all six sites were found in the three different mangrove ecosystems above the critical limits (critical limits: Ca: 2500 ppm, varied from 0.09–0.59 ppm (DS) to 0.44–1.85 ppm Mg: 100 ppm, and S: >50 ppm) in both wet and dry (WS), while iron concentration values shifted from seasons (Table 4). A paired T-test, conducted at 0.60–21.62 ppm (DS) to 3.54–11.00 ppm (WS) a significance level of p < 0.05, confirmed significant (Table 5). Most mangrove sites had Zn, Cu, and Fe differences [M = −0.14, t (5) = −3.54, p = 0.02] only concentrations above the critical limits (Zn: 1.5 ppm, between the average S concentrations in both seasons, Cu: 0.2 ppm, Fe: 4.5 ppm), but Mn levels were mod- among the different ecosystem types. erately low (200 ppm) in both wet and dry seasons. In addition, average nitrogen concentrations ranged Higher values for Fe were seen within restored and from 3.10 ppm to 16.19 ppm (DS) to 7.93 ppm to 28.01 natural sites when compared to degraded sites. ppm (WS), with the lowest concentrations detected in A paired T-test, on the other hand, revealed Table 4. Summary of Ca, Mg, S, N, and P concentrations found in soil samples (data expressed as Mean ± SEM). Nutrient Composition of Mangrove Soils Ca (ppm) Mg (ppm) S (ppm) N (ppm) P (ppm) Dry Wet Dry Wet Dry Wet Dry Wet Dry Wet Location Ecosystem Type Season Season Season Season Season Season Season Season Season Season Ogle R 2333.33 4400.00 2519.33 1382.67 269.24 357.51 16.19 28.01 278.14 52.46 ± 405.52 ±2107.13 ± 283.67 ±247.37 ±76.53 ±226.94 ± 7.86 ±10.68 ±99.42 ±27.70 Montrose R 2800.00 3066.67 3944.67 2414.00 287.97 406.07 14.02 25.63 298.75 169.61 ± 923.76 ±751.30 ± 317.62 ±196.41 ±77.20 ±229.05 ± 7.50 ±6.63 ±113.61 ±97.97 Greenfield D 3400.00 4200.00 813.33 1057.33 116.30 236.12 4.54 11.55 147.17 55.51 ± 1113.55 ±503.32 ± 162.67 ±146.63 ±53.67 ±129.58 ± 4.54 ±4.57 ±27.92 ±24.85 Hope D 6533.33 2533.33 2684 610.00 247.74 256.27 11.34 12.19 303.15 243.22 ± 2136.46 ±371.18 ± 671.92 ±70.44 ±40.77 ±164.13 ± 5.93 ±3.93 ±94.85 ±209.61 Novar N 3133.33 3200.00 610.00 854.00 111.38 159.90 3.10 7.93 224.21 182.72 ± 569.60 ±800.00 ± 70.44 ±140.87 ±18.94 ±91.65 ±3.10 ±2.07 ±73.76 ±91.49 Hopetown N 3066.67 5000.00 894.67 1342.00 209.99 257.62 6.40 13.81 211.50 78.16 ± 240.37 ±1732.05 ± 247.37 ±865.54 ±36.89 ±225.72 ± 6.40 ±7.88 ±40.35 ±39.15 *Letters in table show significant pairwise associations using Tukey HSD Test. GEOLOGY, ECOLOGY, AND LANDSCAPES 15 Table 5. Summary of K, Zn, Mn, Cu, and Fe concentrations found in soil samples (data expressed as Mean ± SEM). Nutrient Composition of Mangrove Soils K (ppm) Zn (ppm) Mn (ppm) Cu (ppm) Fe (ppm) Dry Wet Dry Wet Dry Wet Dry Wet Dry Wet Location Ecosystem Type Season Season Season Season Season Season Season Season Season Season Ogle R 297.31 337.93 2.06 1.88 57.91 84.19 0.59 1.44 21.62 11.00 ±86.60 ±205.73 ±0.59 ±0.46 ±2.63 ±38.04 ±0.25 ±0.27 ±7.27 ±2.29 ab Montrose R 321.77± 435.73 2.33 2.80 65.41 61.55 0.44 1.01 11.83 9.72 88.34 ±208.47 ±0.89 ±0.43 ±2.28 ±34.61 ±0.08 ±0.25 ±2.98 ±2.08 ab Greenfield D 116.30± 163.56 1.81 1.34 66.77 42.55 0.24 0.44 4.33 3.54 53.67 ±42.35 ±0.35 ±0.50 ±0.58 ±22.14 ±0.07 ±0.09 ±4.02 ±2.47 Hope D 247.74± 120.77 0.55 1.45 75.90 31.51 0.09 1.67 0.60 8.87 40.77 ±27.01 ±0.26 ±0.62 ±17.20 ±14.94 ±0.05 ±0.50 ±0.48 ±1.40 ab Novar N 111.38± 144.91 2.60 1.94 85.85 30.90 0.58 1.85 13.54 10.06 18.94 ±45.71 ±0.68 ±0.78 ±14.12 ±15.57 ±0.24 ±0.96 ±4.96 ±4.34 ab Hopetown N 209.99± 289.83 1.97 1.92 74.46 58.09 0.30 0.94 3.08 4.05 39.89 ±9.92 ±0.19 ±0.02 ±8.67 ±17.63 ±0.19 ±0.56 ±2.49 ±2.21 *Letters in table show significant pairwise associations using Tukey HSD Test. statistically significant differences (p < 0.05) in mean seasonality. This was done to determine if soil para- Cu concentrations in both wet and dry seasons meters change in the same direction (+ve or -ve) [M = −0.20, t (5) = −4.49, p = 6.465e-03] (Table 5). concerning seasonality. In Figure 5a, it can be seen that in the dry season, the most significant positive Correlation between soil parameters and correlations were observed between (in descending seasonality order): Cu~Fe (R = 0.97), N~Mg (R = 0.95), N~S Like water parameters, Pearson correlation coeffi - (R = 0.95), Mg~K (R = 0.95), N~ EA (R = 0.93), cients were also established to determine the strength Mg~S(R = 0.89), Mn~pH (0.89), Mn~N (R = 0.89), of the association between soil parameters and N ~ K (R = 0.86), Zn~Cu(R = 0.85), EA~S (0.84), Figure 5. Cormatrix plots for soils parameters in the a) Dry Season and b) Wet season. 16 S. DOOKIE ET AL. Zn~Fe (R = 0.83), OC~K (R = 0.82), EA~K (R = 0.81), (2018), which showed no significant relationship Mg~Zn (R = 0.80), S~K (R = 0.79) and S~ Mn between the two parameters. In most circumstances, (R = 0.79). EC shows a greater relationship with temperature than However, in the wet season, the number of positive pH (Oyem et al., 2014). However, the correlation associations increased between the parameters of soil between EC and temperature was not consistent with when compared to the dry season. This can be seen in results from other research (Rusydi , 2018; Tyler et al., Figure 5b as the number of positive R values increased. 2017), which indicated that temperature has a direct It was also observed that the number of very strong effect on the electrical conductivity of water. The find - positive associations between soil parameters ings in this study showed a weak, negative relationship decreased in the wet season when compared to the between the two parameters. A possible explanation dry season. However, strong positive correlations were for the inverse relationship showcased between tem- maintained by parameters such as EA and OC and perature and EC was offered by Schmidt et al. (2018), nutrients such as (in descending order): Mg~K who posited that the temperature and density of salt- (R = 0.95), S~N (R = 0.95), EA~N (R = 0.93), Mn~K water (oceanic in nature) are inversely proportional. (R = 0.90), Mn~N (R = 0.89), N ~ K (R = 0.85), As the temperature rises, the space within water mole- OC~Mg (R = 0.85), EA~S (R = 0.84), OC~K cules expands, causing the density to decrease. He also (R = 0.82), EA~K (R = 0.81), Cu~Fe (R = 0.81), noted that salinity (demonstrated in this study as S ~ K (R = 0.79), and S~Mn (R = 0.79). measurements of electrical conductivity) and density share a positive relationship. As a result, as water’s temperature drops, its density rises, but only to a limit. Findings on the various relationships between the Discussion physicochemical parameters of water in this study Water provide further evidence that the relationships between pH, temperature, and EC may be affected by The EC values obtained in this study showed seasonal many factors, some of which are reflected in differ - variations that may be caused by the mobility of ences within the environmental setting of various groundwater, water temperature, and soil rock leach- mangrove ecosystems, which encompasses their ing (Terungwa Temaugee et al., 2020). This may con- hydrological framework and patterns, including tidal tribute to the fluctuating salinity levels caused by high wave impacts, riverine forces and influences, ground- temperatures and oceanic fluctuations, affecting man- water flow, and surface runoffs from highlands (Li grove trees and seedlings found in the various man- et al., 2008). Wan et al. (2014) and Atwell et al. grove ecosystem types (Chowdhury et al., 2019). The (2016) also confirmed that tidal inundation is a key pH levels observed in mangrove ecosystem water sam- determinant of abiotic variables including salinity, ples were within the appropriate range of 6.5–8.5, physicochemical properties of water, and redox poten- which is consistent with prior studies that recorded tial. Climate change, water degradation, contamina- pH values in the range of 6.95–7.42 (Samara et al., tion, changes in water flow, groundwater, and light 2020). Slight differences in pH levels among mangrove regimes are all examples of factors that affect the ecosystems may be due to ocean acidification and physicochemical characteristics of water resulting organic matter putrefaction (Dattatreya et al., 2018). from anthropogenic activities ([EPA] Environmental Mangrove aerial roots have evolved to efficiently meta- Protection Agency, 2018). bolise organic compounds from soils experiencing anoxia to release alkaline compounds into the water- ways encroaching upon them. This stabilises the pH Soils caused by increased carbon dioxide in the atmosphere and local waterways and facilitates the creation of Texture and appearance equilibrium in open oceans (Thomas et al., 2017). Despite variations in soil texture and appearance of Sippo et al. (2016) discovered that water surrounding soil samples collected in the three mangrove ecosys- the mangroves has a higher pH (8.1) than seawater tems, the soil textures recorded in this study were farther away from the coastal mangroves (pH = 7.3). consistent with other research on mangrove soils, Such values are consistent with those reported only which revealed that mangrove soil surfaces are mostly from natural mangrove ecosystems in this study. composed of freshly deposited sediment particles and Cabañas-Mendoza et al. (2020) also showed that are known as sandy or silty loams (Andrade et al., although the association was poor (R = 0.26 for 2018; Bomfim et al., 2018). Furthermore, Moreno A. germinans), elevations in the salt concentrations and Calderon (2011) discovered that within mangrove of a substrate may also cause an increase in the pH forests, the soil is partly composed of sand, clay, and of water in mangrove areas. loam with 53.17% of the total comprising sand parti- Findings for the correlation between pH and EC cles. Silty clay is primarily found in logged and undis- were based on results obtained by Dattatreya et al. turbed mangroves, though some species may prefer GEOLOGY, ECOLOGY, AND LANDSCAPES 17 different types of soil. However, moving towards the seawater. This was further clarified by research con- seaward zone, Avicennia sp. can be detected on sandy ducted by Lambs et al. (2008) on black mangroves soils (Ibrahim & Hossain, 2012; Sofawi, 2017). This found in French Guiana, in which the groundwater zonation pattern was evident within the degraded can acquire a salty nature which is mainly caused by areas of this study as the soils found in these areas the seepage of freshwater from marshes found inland were mostly composed of sand. and stormwater in the rainy season, which causes marine evaporite to be dissolved repeatedly. Furthermore, they have also confirmed that seasonal pH, salinity (EC), exchangeable acidity (EA), and patterns, transpiration, and the presence of freshwater organic carbon (OC) influx influence salinity changes in the upper sediment In this study, results showed significant differences in of mangrove soils. This affects the accumulation of salt percentages of EC, EA, and OC concerning seasonality under the mangrove forest, causing the formation of but not ecosystem type. Mangroves are well known for brine during the dry season. This will subsequently their abundant carbon stores and high rates of carbon dissolve in the wet season, owing to the natural con- sequestration in soil and biomass (Rovai et al., 2022). vection processes. The OC percentages obtained in this research are Soil pH values in this study ranged from 6.45 to consistent with those obtained by Matsui et al. 7.88, which were considered to be within a neutral pH (2015), in which OC percentages are usually higher range and were consistent with values obtained by in the wet seasons than in the dry seasons (Kathiresan Bomfim et al. (2015), Tran Thi (2018), and Andrade et al., 2014). However, Georgiadis et al. (2017) and Lei et al. (2018). The neutrality of the pH of mangrove et al. (2019) confirmed that many factors could influ - soils in varying seasons (evident in this study) was ence seasonal variations in OC levels in the soil. Such explained by Hseu and Chen (2012) as the impact of factors would include land use, species of plants, site seawater on the mangrove areas. Mangroves can flour - characteristics (slope and location), underlying soil ish at their optimum rate even with a soil pH level of properties, stand age, microbial activity, and species 5.16 to 7.72, according to Lim et al. (2012), so they can density (Babur & Dindaroglu, 2020; Sofawi, 2017). adjust themselves to withstand adverse environmental Climate change (such as water temperature elevations) conditions and lower nutritional accessibility. and anthropogenic activities such as logging, pollu- However, young mangrove seedlings, particularly tion, and land-use conversions, along with insect inva- those in the early growth stages, cannot withstand sion, are all factors that affect mangrove SOC in severe pH conditions (>5.16–7.72) since they prevent different mangrove ecosystem types (Gao et al., nutrients from reaching the plants (Alsumaiti & 2019). While it was not evident within this study, Shahid, 2018). The low EA values found in this analy- studies have shown that OC % is usually higher in sis were similar to those found by Adamu et al. (2014), mature forests and two times greater in replanted while Onwuka et al. (2016) found that hydrogen, sul- forests when compared to non-vegetative soils due to phate, iron, and aluminium ions were the key factors enrichment provided by litter fall and stored carbon influencing soil exchangeable acidity when soil pH is content in vegetation (Kathiresan et al., 2014). low. Therefore, soils present within the mangrove sites Shahid et al. (2014) and Alsumaiti and Shahid in this study do not need to be neutralised to buffer (2018) describe electrical conductivity (EC) as their pH since their values (corresponding to low EA a parameter that indirectly serves as an indicator of values) were within an acceptable range. soil salinity and can be considered a key component of soil health. Jeyanny et al. (2018) reported EC values of 11.99 ms/cm in regenerating mangrove ecosystems Nutrient composition and 20.92 ms/cm in established mangrove ecosystems. Sulphur concentrations reported in this study were These values are significantly higher when compared sufficient in mangrove soils and showed no significant to the values observed in this study. However, Sudduth differences among locations. This was consistent with et al. (2005) and Kida et al. (2017) observed that the results obtained by Madi et al. (2015) in similar man- physical and biological characteristics of soil, includ- grove stands found in Brazil. However, sulphur con- ing soil type, organic compounds, moisture and tem- centrations varied among the seasons within the six perature of the soil, and Cation Exchange Capacity mangrove stands, with elevated values in the wet sea- (CEC), can influence soil EC readings, thus creating son when compared to the dry. Studies conducted by significant soil EC variations. The evaporation and Hofer (2018) and Jørgensen et al. (2019) showed that evapotranspiration over the salt flats and mangroves microorganisms are considered to be the primary may cause rapid increases in salinity and may cause source of sulphur oxidation and reduction, although variations during dry and wet seasons (Komiyama in numerous cases, chemical reactions such as organic et al., 2019). Variations in EC values between seasons matter degradation are included. The sulphur cycle, (wet and dry) can also be due to instances where the and thus the rate of soil sulphur oxidation, is influ - origin of the water among mangroves may not be enced by environmental conditions such as pH, 18 S. DOOKIE ET AL. temperature, moisture, microbial activity, organic amount of substrate available for microorganisms material, particle size, and atmospheric pollution. (Guntiñas et al., 2013; Xue et al., 2017). Alsumaiti Reduced water supply encourages aeration of the and Shahid (2018) explain that low phosphorus avail- soil, degradation, and depletion of metal sulphides ability and efficiency in mangrove soils may be due to from mangrove soils, mostly during the dry season phosphorus fixation with high CaCO levels, which (Nóbrega et al., 2013). Seasonal fluctuations in forms may result in reduced P accessibility and efficiency in of sulphur found in mangroves suggest that seasonal plants unless the release of fixed phosphorus is aided weather conditions may affect geochemical processes by acidic conditions. in these ecosystem types. Furthermore, low N levels in the soil may be due to The results of this study, being consistent with denitrifying bacteria being prevalent within mangrove results obtained by Rivera-Monroy et al. (2004) and soils, resulting in high rates of denitrification owing to Khan and Amin (2019), confirmed that Ca concentra- anaerobic environmental conditions and high OM tions are sufficient in the soils and show no significant content, which in turn causes a lowering of nitrogen differences between mangrove locations or seasons. levels (Alfaro-Espinoza & Ullrich, 2015; Pupin & However, when calcium is (1) dissolved or extracted Nahas, 2014). As a result of the high accumulation of from irrigation water, (2) extracted by plants, (3) cations in ocean water competing for binding sites, ingested by organisms in the soil, (4) removed from absorption of ammonium by soil particles in man- the soil by rain, or (5) taken in by clayey particles, grove areas is generally poorer when compared to variations in the concentration of available calcium in terrestrial habitats, rendering ammonium accessible the soil may occur (Oldham, 2019). Not much is for plant roots to absorb (Reef et al., 2010). High known about the Ca content of mangrove soils in K concentrations obtained in this study were consis- Guyana. However, based on observations made within tent with results obtained by Sofawi (2017) and the various mangrove ecosystems, the high Ca content Alsumaiti and Shahid (2018), who concluded that found within the soils may be due to organism inges- there are two major explanations for the high potas- tion (crabs) as well as the presence of broken shells, sium content in the soil: a) mud rich in organic mate- which can increase the CaCO content within the soils rial and accumulation of deteriorated organic matter (Andrade et al., 2018). over time by pneumatophores, which facilitate potas- Furthermore, an examination of the results sium release into the soil (located in areas that have obtained from the Mg concentrations showed that low disturbance and are minimally affected by there were sufficient amounts of Mg present within humans); and b) potassium is found in the crystal all six sites, with differences in locations but not sea- structure of minerals like K-feldspar and mica, which sons. The values obtained were consistent with studies release it during weathering (Reef et al., 2010). conducted by Motamedi et al. (2014) and Windusari Cuzzuol and Rocha (2012) and Madi et al. (2015) et al. (2014). Similar results were also obtained by give explanations for dissimilarities in the proportions Gutiérrez (2016), who reported increased amounts of of Mn, Zn, Cu, and Fe in soils, both between species Mg in low-disturbance mangrove ecosystems, and and mangroves, which may be due to variations (spa- small concentrations were detected in mangrove tially and temporally) as well as physicochemical soil stands with high disturbances. Such variations in Mg properties. Earlier studies conducted by D. Alongi can be caused by strong tidal rhythms owing to the (2018) and Taillardat et al. (2019) further explained mixing of estuarine and mangrove waters, salinity, and that tidal variations can also interfere with the avail- primary aquatic productivity (Manju et al., 2012). ability of chemical elements, which could result in the The findings of this study are consistent with those alterations of the nutrient concentrations present in of Madi et al. (2015), who showed no significant dif- various mangrove ecosystems. This was observed in ferences between NPK levels in the mangrove soils the differences between Cu concentrations, with found in the six different study sites. However, there higher concentration values in the wet season when were marked differences between seasons, with con- compared to the dry season. Fluctuations of Fe were centrations fluctuating between the different locations detected among the six mangrove ecosystems, with and with values of nitrogen and phosphorus being low natural and restored mangrove ecosystems having in most sites. During wet periods, certain soil nutrients the most significant differences and higher concentra- may be more easily accessible than during dry periods, tions when compared to degraded mangrove ecosys- according to Sonko et al. (2016), who pointed out that tems, which showcased low Fe levels in the soils. It has the moisture content in the wet season subsequently been observed that manmade irrigation structures promotes soil nutrient availability for plant root located at Hope and Greenfield (degraded mangrove absorption. Low water availability slows down decom- stands) cause frequent flooding of the area due to the position and biogeochemical cycles because the water size of the structures, which may interfere with incom- film surrounding soil particles prevents nutrients and ing and outgoing tidal patterns. This may provide enzymes from diffusing into the soil, which limits the a possible explanation for the reduced Fe GEOLOGY, ECOLOGY, AND LANDSCAPES 19 concentrations in degraded mangrove soils since high the physicochemical parameters of soil and water levels of water promote the leaching of nutrients. between the natural, restored, and degraded areas. Differences in Fe concentrations may also be caused However, notable differences were seen in the pH of by variations in sediment origin because seasonal water as well as Fe and Mg concentrations of soil waterlogging causes Fe to accumulate in clay-rich within the three types of ecosystems. Additionally, soils. However, a build-up of organic detritus and Fe- seasonal differences were also evident in S, N, P, K, rich soil particles in streams allows Fe to be released and Cu concentrations found within the mangrove under anaerobic conditions and then bound by soils. In both seasons, positive correlations were evi- organic matter (Löhr et al., 2010). dent among soil parameters, while negative correla- In this study, Mn concentrations were below the tions were established among the water parameters critical limit in all mangrove sites. Mn insufficiency is investigated in this study. The findings of this study brought on by two different inadequacies: those suggest that though variations exist, the physico- caused by chemical factors in the soil and those asso- chemical parameters of soil and water found within ciated with biological factors. Between seasons, areas the mangrove ecosystems along Guyana’s coastline that fluctuate between well-drained and waterlogged are not heavily influenced by ecosystem type (natural, conditions may develop manganese deficiencies due to degraded, or restored) or seasonality (wet and dry constant flow between the mangrove forest sediments periods). and tidal water (Alongi, 2021). This is usually observed within mangrove forests along the coastline Geolocation information since they experience rapid tidal inundations. As they lead to Mn accumulation and may be actively engaged Study locations in Guyana (SA) with GPS Coordinates: in retaining its level as well as other associated metal (1) Ogle, Georgetown (Region 4):HT 6.82349, −58.09528 quantities like Fe among mangrove sites, both auto- (2) Montrose, Georgetown (Region 4):HT 6.82024, chthonous heterotrophs and autotrophs work cohe- −58.07688 sively to mitigate Mn and associated metals such as Fe (3) Hope, East Coast Demerara (Region 4):HT 6.74644, within mangrove swamps (Krishnan et al., 2007). −57.95619 (4) Greenfield, East Coast Demerara (Region 4):HT 6.73843, −57.94596 Correlations between nutrient concentrations and (5) Novar, East Coast Demerara (Region 5):HT 6.56846, seasonality −57.76294 Examination of the correlation values within the cor- (6) Hopetown, West Coast Berbice (Region 5):HT 6.40364, relation matrices for wet and dry seasons shows com- −57.59729 plex and significant associations between soil nutrients and other physicochemical parameters. Such fluctua - Acknowledgments tions are thought to be directly linked to the accumu- lation of nutritionally rich silt during the rainy season, The authors would like to express gratitude to the followed by depletion due to plant absorption and Department of Biology, Centre for the Study of Biological tidal leaching at various periods throughout the year Diversity (CSBD) (UG), World Wildlife Fund Guianas, and National Agricultural Research and Extension Institute (Sofawi, 2017). The results derived from this study (NAREI) for their valuable contributions. show consistency with earlier studies (Fernandes et al., 2013; Rahaman et al., 2013) that have shown strong positive correlations between nutrient concen- Disclosure statement trations in mangrove soils, in which they have indi- No potential conflict of interest was reported by the cated that changes in hydroperiods, as well as leaf litter author(s). quantity and quality within mangrove stands, can cause seasonal patterns of nutrient immobilisation. Furthermore, Numbere (2019) reported that the con- Funding centration of metals and nutrients in mangrove soils This work was supported by the WWF Guianas under Grant can vary in seasons, with emissions from anthropo- number UGUFWWF0017; and National Agricultural genic activities identified as the key source. Research and Extension Institute (NAREI) under Grant number NAREI/2020-01. Conclusion ORCID This study focused on the physicochemical para- meters of water and soil found in natural, degraded, Sabrina Dookie http://orcid.org/0000-0002-7292-091X and restored mangrove ecosystems in Guyana, con- Sirpaul Jaikishun http://orcid.org/0000-0003-0301-6844 cerning ecosystem type as well as seasonality. Our Abdullah Adil Ansari http://orcid.org/0000-0002-9845- results did not show significant variations in most of 6182 20 S. DOOKIE ET AL. E Ambiente, 25(2). https://doi.org/10.1590/2179-8087. References Ackroyd, ca. 2010. Final report of the mangrove technical Atwell, M. A., Wuddivira, M. N., & Gobin, J. F. (2016). assistance for capacity building and institutional strength- Abiotic water quality control on mangrove distribution ening of the sea defences sector -, EDF 2007 Europe Aid/ in estuarine river channels assessed by a novel 127405/D/SER/GY. boat-mounted electromagnetic induction technique. Adamu, U., Muhammad, A., & Adam, I. (2014). 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Geology Ecology and Landscapes – Taylor & Francis
Published: Nov 12, 2022
Keywords: Mangroves; ecosystems; Guyana; mangrove sediments
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