Trophic cascading interrelationship of aquatic communities
Monitoring and Conservation of tropical lake using cascading interrelationship analysis of aquatic communities with reference to climate changes.
Dr. Asma Ali
[Ecologist]
INTRODUCTION:
Trophic relationships are a vital component of community structure in aquatic bodies, particularly with respect to predation, competition and resource spiraling of the major components such as plankton, macroinvertebrate and fishes. Dietary habits can potentially influence every aspect of the life of the aquatic fauna, such as life cycle, choice of habitat and behavior.
Consequently the trophic ecology of aquatic fauna has received much attention from ecologists, however most of the work has been done in temperate regions of the Northern Hemisphere (Hairstone and Hairstone 1993, Merrit and Cummins 1996, Duffy 2005) and to a lesser extent, the Southern Hemisphere (Chessman 1986, Yule 1996, Kaunzinger and Morin 1998, Winemiller and Layman 2005). Data on the dietary habits of aquatic invertebrates and vertebrates are not common, particularly for organisms of tropical water bodies of central India.
Aquatic ecosystem functioning depends on multiple interactions between physical, chemical and biological determinants. Indeed, ecosystem process (productivity and nutrient recycling) result directly from the diversity of functional traits in the biotic communities, which is in turn determined by the species composition and diversity (Kelly and Haves 2005, Zanden and Fetzer 2007, Adandedjan et al. 2010). This species diversity results from both biotic interaction and environmental pressures. As a result, changes in biodiversity in response to environmental selection pressures tend to have a direct impact on ecosystem process.
Thus these intricate relationships between aquatic biodiversity and ecosystem functioning has been the focus of numerous researches for several years, particularly in the event of drastically changing global climate scenario, however large tropical man made water body, such as the Upper Lake in Bhopal, has not at all been subjected to a food web interrelationship analysis. Thus there is no information available on the comparative assessment of climate change scenarios based on aquatic food web modeling, resulting in a rapid eutrophication of this largest man made lake.
In an aquatic ecosystem, each species either invertebrate or vertebrate has the potential to perform an essential role in the persistence of the aquatic food web and the ecosystem and that species may remain as the sole representative of a particular functional group. At some level where each species is unique, overlapping in resource use among species in not unusual, especially in freshwater food webs.
Many benthic invertebrates are predators that control numbers, locations and sizes of their prey, benthic invertebrates supply food for both aquatic and terrestrial vertebrate consumers e.g. fishes, turtles and birds, finally benthic organism accelerate nutrient transfer to overlaying open waters of lakes as well as to adjacent riparian zones of streams (Abell et al., 2008, Heino et al. 2009, Matthews and Wickel 2009).
The extent of understanding the effect of aquatic fauna and flora in a freshwater ecosystem food web process varies with the type of fresh water system. Food chain length is a measure of the number of energy transfer or trophic link between primary producers and top predators in an ecosystem also plays an important role in regulating biogeochemical fluxes, fisheries productivity and contaminant bioaccumulation in top predators of any water body.
Climate change is one of the most crucial and influential ecological problems of our age, therefore a large number of investigations is required to deal with this problem which is increasing permanently. Climatic changes and variability can influence aquatic ecosystem in a very sensitive way, so the research of the possible effects of climate change on aquatic ecosystem means an indispensable task.
Global warming and climate change which has caused the ecological systems, biodiversity and human life to control the biggest problem of history have started to show their impacts on all living beings in the aquatic ecosystem from plankton to mammals. Global surface temperature has increased on an average of 0.74 ± 0.18ºC between the start and the end of the 20th century (Abell et al. 2008, Matthews and Wickel 2009, Heino et al. 2009).
Since we do not have the chance to reverse global warming and climate change phenomena, the only thing that needs to be done is to minimize the foreseen harms in the future. To this end, mankind needs to understand the global warming problem and cooperate on an international level using aquatic model studies of invertebrate and vertebrate species preferably in large tropical water bodies, which are in brink of eutrophication and extinction.
Upper Lake of Bhopal the largest man made lake built by Raja Bhoj in 1100 is such an example. The present work will be a very important step towards its conservation.
Previous studies of Upper Lake have often dealt with the physico-chemical parameters for taxonomy of flora and fauna of the lake (Durrani 1993, Tiwari 1999), which are clearly important components of food webs, but how their functional relationships respond to changes in species composition are not known at all. Crores of rupees have been spent by Lake Authority Bhopal and other agencies on only physicochemical and limnological studies of the lake with no data available on cascading trophic interactions of invertebrate communities; except for the preliminary work of Parveen et al. (2009), Parveen and Ali (2010), which have shown interesting findings.
In the present research work, we will be highlight examples of how some species have a disproportionately large impact on food-web dynamics, how particular species provide essential ecosystem services and how changing climate impacts aquatic biodiversity. These ecosystem functions include sediment mixing; nutrient cycling, cascade prey predator relationship and energy flow through food webs. The present investigation will prepare a working model of lake monitoring and conservation using aquatic food web cascading interrelationships in changing climate factors likes temperature, humidity, rainfall and nutrients.
AIMS AND OBJECTIVES :
To investigate the trophic importance of plankton (phytoplankton and zooplankton) in relation to species richness and pelagic primary productivity of the Lake with regard to rainfall, temperature humidity and nutrient.
To determine the number of trophic in an aquatic ecosystem and to focus the role of benthic invertebrate species in freshwater ecosystem.
To assess the role of insect fauna in water quality assessment programme and their importance in aquatic food web in relation to limnological factors.
To group the various fish species according to their feeding preferences, for assessing functioning of cascade trophic prey-predator relationship in the Lake.
To investigate the role of macrophytes with regard to their trophic status for management and conservation of the Lake.
Comparative assessment of the alternative climate change scenarios using statistical methods.
BRIEF REVIEW OF THE WORK DONE IN THE FIELD:
Food chain length is a measure of the number of energy transfer or trophic links between primary producers and top predators in an ecosystem, and the importance of food chain for ecosystems and their functioning have been widely documented. For example, the number of trophic levels in a central consideration to the study of the food chain dynamics (Fretwell 1987) and the structuring of the ecosystem via trophic cascades (Kelly and haves 2005, Zanden and Fetzer 2007) as well as mediating the relationship between species diversity and function (Worn 2002, Schmitz 2003, Duffy 2005).
Food chain also plays a role in regulating biochemical fluxes, fisheries productivity (Pauly and Christensen 1995) and contaminant bioaccumulation in top predators (Kidd 1995, Winmiller and Layman 2005).
The earliest consideration of food chain, Elton (1927) speculated that available energy ultimately limits the number of trophic levels in ecosystems. A clear prediction is that more productive should have longer food chains. This “productivity hypothesis” has found support in some studies (Kaunzinger and Morin 1998, Thompson and Townsend 2005, Kundzewicz et al., 2008), but not others (Briand and Cohen 1987).
Since then, variants of the productivity hypothesis have been forwarded, most notably the productive space hypothesis, which argues that total ecosystem production should best reflect the capacity of an ecosystem to support additional trophic levels and the hypothesis that food chain length should increase with increasing ecosystem size (Post et al. 2000).
In the case of aquatic ecosystems the astonishing species richness in phytoplankton communities has stimulated many studies of the importance of competition for light and /or nutrients, or of the intermediate disturbance hypothesis have been reported by several workers such as Elliott et al. (2002) and Schippers et al., (2001).
Similarly in case of zooplankton many views have been stressed by several investigators such as Leveque (1997) and Matondo and Msibi (2006), who showed the relationship between zooplankton and physico-chemical features of a water body, while Ward (1998) stated that there is no obvious relationship between zooplankton and dissolved nutrients. In freshwater sediments, benthic invertebrates are diverse and abundant and the integrity of the freshwater supply depends on how various benthic species make their living and contribute to complex food web.
Furthermore, there are many papers that deal more specifically with the mechanisms involved in the relationships between biodiversity of water bodies and ecosystem functioning. Notably have Yule (1996), Loreau (1998) and Conway (2005). Using a freshwater microbial community Fukami and Morin (2003) found that food web relationships in the different assemblage of species took various forms (U-shaped, hump-shaped) after 30 generations.
Concerning aquatic ecosystems more particularly Dobson et al. (2000) found in their study based on a survey of 33 lakes that for both phytoplankton and fish, the richness-productivity relationship was highly dependent on the area of the lake.
Climate change has and will continue to affect freshwater ecosystems in a variety of ways (Fukamy and Marin 2003, Heino et al.,2009). When flow regimes shift, quantitative and qualitative changes to aquatic habitat result, indirectly influencing ecosystem productivity and biodiversity. Freshwater systems are expected to experience an increase in the frequency and intensity of extreme events, such as droughts and floods ;freshwater species adapted to different, historic flow regimes might be unable to complete their life histories under these conditions.
Climate change-induced air temperature shifts are already altering water temperature and attendant biogeochemical processes, and changes in lake volume and thermal structure are expected (Lake et al. 2000; Mohseni et al. 2003). Coastal wetlands and the lower reaches of most rivers in many regions have been affected by sea-level rise for over a century (Bates et al. 2008).
However there are very few studies on trophic relationships of water bodies and ecosystem functioning, some of these studies which have contributed to the significant advances of our knowledge on this subject in the last ten years and have provided a good overview of the challenges likely to face us in the future.
With this goal in mind, new experiments based on trophic relationships and food web must be performed at aquatic ecosystem of tropical water bodies, which have variant cycles of trophic interactions due to large number of environmental factors. Thus in the view of above lacunae, the present study has been taken, where a detailed study of tropical lake using cascading interrelationship analysis of aquatic communities with reference to climate change.
DESCRIPTION OF STUDY AREA :
The Upper Lake is located in Bhopal city, the capital of Madhya Pradesh, the largest state of India. Constructing on earthen dam across the river Kolans in the 11th century created this lake. The Upper Lake has water spread area of 30.72 sq.km at FTL. The storage capacity is 101.6 million cu.m, the maximum and mean depth being 11.7 and 6 m. respectively.
The Upper Lake is under a massive conservation, restoration and management project funded by overseas Economic Cooperative Fund (OECF) Japan to protect it from environmental degradation not only due to its natural aesthetic value and rich biodiversity, but also since it is the main source of potable water. Selection of the sampling sites of the Upper Lake chiefly was done on the basis of weeds and consequent biomass sampling. Sampling will be done at four sampling sites of Upper Lake viz. Bhadbhada, Van-vihar (National Park), Pump-house and Bairagarh
REFERENCES:
APHA (2010) Standard methods for the examination of water and wastewater, 23rd ed. American Public Health Association, Washington DC, Pp. 1134.
Abell R., Thieme M., Revenga C. (2008) Freshwater ecoregions of the world: a new map of biogeographic units for freshwater biodiversity conservation. BioScience 58, 403–414.
Adandedjan D., P. Laley, A. Ouattara and G. Gourena (2010) Distribution of benthic insect fauna in a west Africal Lagoon: Porto Novo Lagoon in Benin: Science alert. Asian J. Biol.Sci.,4:116-127.
Briand F. and M. Cohen (1987) Environmental correlates of food chain length. Science 238: 956-960.
Conway, D. (2005) From headwater tributaries to international river: observing and adapting to climate variability and change in the Nile Basin. Glob Environ Change-Hum Policy Dimens 15, 99–114.
Cranston P.S. (2000) Electronic guide to the chironomidae of Australia http://entomology, UC davis. Edu/Chiro Pp.963-978.
DicksL.V., Corbet S.A., Pywell R.F. (2003): Compartmentalization in plant-insect flower visitor web. J. Animal Ecol., 71,32-43.
Dobson S.I. ,S.E. Arnott and K. L. Kottingham (2000) The relationship of lake communities between primary productivity and species richness, Ecology 81, 2662-2679.
Duffy J.E. (2005) Ecosystem consequences of diversity depend on food chain length in estuarine vegetation. Ecol.Lett.8:301-309.
Durrani I.A. (1993) Oxidative mineralization of Plankton with its impact on eutrophication of Bhopal, Barkatullah University. Ph.D. thesis ,Pp.289.
Elliot J.A., Irish A.E., Reynolds C.S. (2001) The effects of vertical mixing on phytoplankton community: a modelling approach to the intermediate disturbance hypothesis. Fresh Biol. 46, 1291-1297.
Fretwell S. (1987) Food chain dynamics:The central theory of ecology? Oikos 50:291-301.
Fukami T. and P. J. Marin(2003) Productivity biodiversity relationships depend on the history of community assembly. Nature 424, 423-426.
Hairstone N.G. and Hairston N.G.(1993) Cause affects relationships in energy flow, trophic structure and inter specific interactions.Am.Nat.142:379-411.
Heino J., Virkkala R., Toivonen H. (2009) Climate change and freshwater biodiversity: detected patterns, future trends and adaptations in northern regions. Biol Rev 84, 39–54.
Kaunzinger C.M.K. and Morin P.J. (1998) Productivity Controls food chain properties in microbial communities. Nature 395: 495-497.
Kelly D.,J. and Haves I. (2005) Effects of invasive macrophytes on littoral zone productivity and food web dynamics in New Zealand high Country Lake.J. N. Ame.Benthological Soc. 24 (2): 300-320.
Kidd K.A. (19950: High concentration of toxaphene in fish from a subArctic Lake. Science, 269:240-242.
Kundzewicz, Z.W., Mata L.J., Arnell N. (2008) The implications of projected climate change for freshwater resources and their management. Hydrol Sci J-Journal des Sciences Hydrologiques CA 53, 3–10.
Lévêque, C. (1997) Biodiversity dynamics and conservation: the freshwater fish of tropical Africa. Cambridge University Press, Cambridge , UK .
Loreau, M. (1998) Biodiversity and ecosystem functioning: a mechanistic model. Proc. Nat. Acad. Sci.. USA, 95,5632-5636.
Matthews J.H., Wickel A.J. (2009) Embracing uncertainty in freshwater climate change adaptation: a natural history approach. Climate and Development 1, 269–279.
Merrit R.N. and Cummins K.W.(1996) An introduction to the aquatic insects of North America.Kendall/Hunt publishing, 488.
Matondo J.I., Msibi K.M. (2006) Water resource availability in three catchments of Swaziland under expected climate change. Water International 31, 514–527.
Parveen A. and A.S. Ali (2010): Temperature and food as a determinant of population persistence in the shoreline odonata community. Biosci. Biotech. Res. Comm., Vol(3) No(1), 69-73.
Parveen A., A.S. Ali and S.A. Ali (2009) Role of shoreline macrophytes in management and conservation of tropical lake. Biosci. Biotech. Res. Comm. Vol(2), no(2), 195-199.
Pauly D. and Christensen V. (1995) Primary production required to sustain global fisheries- Nature, 374:255-257.
Poff N.L., Brinson M.M., Day J.W. (2002) Aquatic ecosystems and global climate change. Pew Center of Global Climate Change, Arlington, VA.pp. 489.
Schippers P., A.M. Verschoor, M. Vos and W.M. Mooij (2001) Does super saturated coexistence resolve the paradox of the plankton. Ecol. Let. 4, 404-407.
Schmitz O.j.(2003) Top predator control of plant biodiversity and productivity in an old field ecosystem. Ecol. Lett.6:156-163.
Taki h. and P.G. Kevan: Does habitat loss affect the communities of plants and insects equally in plant pollinator interactions, preliminary findings. Biodivers. Conserv.16, 3147-3161.
Tiwari D.R. (1999) Physicochemical studies of Upper Lake water Bhopal, Madhya Pradesh, India,Pollution res., 18 (3), 322-326, Environ.
Thompson R. M. and Townsend C.R. (2005) Energy availability, spatial heterogeneity and ecosystem size predict food-web structure in streams. Oikos 108:137-148.
Wrona F.J., Prowse T.D., Reist J.D., Hobbie J.E., Levesque L.M.J., Vincent W.F. (2006) Climate change effects on aquatic biota, ecosystem structure and function. Ambio 35, 359–369.
Ward J.V. (1998) Riverine landscapes: biodiversity patterns, disturbance regimes, and aquatic conservation. Biol Conser 83, 269–278.
Worn J. (2002) Consumer versus resource control of species diversity and ecosystem functioning-Nature ecosystem-Oecologia, 65:86-88.
Winemiller K.O. and Layman C.A. (2005) Food web science: Moving on the path from abstraction to prediction. In De Ruiter. P.C. et al (eds), Dynamic food webs. Elsevier Press, Pp.10-23.
Yule C. M. (1996): Trophic relationships and food webs of the benthic invertebrate fauna of two seasonal tropical streams on Bougainville Island, Papua New Guinea, Journal of tropical ecology, 12: 517 – 534
Zanden M.J.V. and W.W. Fetzer (2007) Global patterns of aquatic food chain length. Oikos 116:1378-1388.
