The climate sensitive zone along an altitudinal gradient in central Himalayan rivers: a useful concept to monitor climate change impacts in mountain regions Ram Devi Tachamo Shah, Subodh Sharma, Peter Haase, Sonja C. Jähnig & Steffen U. Pauls Climatic Change An Interdisciplinary, International Journal Devoted to the Description, Causes and Implications of Climatic Change ISSN 0165-0009 Climatic Change DOI 10.1007/s10584-015-1417-z
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Author's personal copy Climatic Change DOI 10.1007/s10584-015-1417-z
The climate sensitive zone along an altitudinal gradient in central Himalayan rivers: a useful concept to monitor climate change impacts in mountain regions Ram Devi Tachamo Shah 1,2 & Subodh Sharma 3 & Peter Haase 1,2 & Sonja C. Jähnig 1,2,4 & Steffen U. Pauls 1
Received: 4 September 2014 / Accepted: 26 April 2015 # Springer Science+Business Media Dordrecht 2015
Abstract Highland freshwater ecosystems respond rapidly to changing climatic conditions making the biota of mountain streams and rivers particularly vulnerable to climate change. Lack of data and concepts to monitor and manage the potential effects of climate change on freshwater biota is particularly evident in developing countries. Many of the highest and longest mountain systems are found in these regions and provide fundamental water-based services to these countries. The climate sensitive zone (CSZ) concept is based upon changes in Sonja C. Jähnig and Steffen U. Pauls shared senior authorship. Electronic supplementary material The online version of this article (doi:10.1007/s10584-015-1417-z) contains supplementary material, which is available to authorized users.
* Ram Devi Tachamo Shah
[email protected] * Steffen U. Pauls
[email protected] Subodh Sharma
[email protected] Peter Haase
[email protected] Sonja C. Jähnig
[email protected] 1
Senckenberg Biodiversity and Climate Research Centre (BiK-F), Senckenberganlage 25, Frankfurt am Main 60325, Germany
2
Department of River Ecology and Conservation, Senckenberg Research Institute and Natural History Museum, Clamecystrasse 12, 63571 Gelnhausen, Germany
3
Department of Environmental Science & Engineering, Kathmandu University, P.O. Box 6250, Kathmandu, Nepal
4
Department of Ecosystem Research, Leibniz-Institute of Freshwater Ecology and Inland Fisheries (IGB), Müggelseedamm 301, 12587 Berlin, Germany
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community composition along altitudinal gradients that serve as a proxy for climatic gradients. The CSZ characterizes a community of climatically sensitive biota that is likely to react quickly to climate change. We present a framework on how the CSZ can be adapted to and implemented in streams, and demonstrate its applicability for central Himalayan streams of Nepal. We sampled and analyzed benthic invertebrate communities of 58 central Himalayan streams along altitudinal gradients from 1500 to 4500 m asl. A generalized linear model identified altitude as the only significant, albeit indirect, variable explaining benthic invertebrate composition. We applied species turnover scores and threshold indicator taxon analysis (TITAN) to identify the CSZ in central Himalayan streams along the extensive altitudinal gradients. An altitudinal band between 2900 and 3500 m was identified as CSZ and was characterized by 33 indicator taxa. Identifying CSZs in streams can help prioritize resources for monitoring climate change impacts in running waters and help pinpoint stream reaches suitable for testing the efficacy of climate change-directed mitigation practices.
1 Introduction Inland waters cover less than 1 % of the Earth’s surface yet harbour 10 % of all known animal species (Balian 2008). Given their small global surface area compared to species numbers, and high vulnerability to land use, indirect and direct anthropogenic disturbance, as well as climate change, freshwaters are considered to be among the most threatened ecosystems on Earth (Dudgeon et al. 2006). There is a broad basis of information on the hydrological consequences of climate change on river systems from studies in various regions of the globe (e.g. Döll and Zhang 2010; Kernan et al. 2010; Sorg et al. 2012). Among freshwater ecosystems, those occurring in mountains and highlands are particularly sensitive to climate change as their hydrology, morphology, and physico-chemical conditions are strongly and directly affected by changes in precipitation and thermal regime (Jacobsen et al. 2012; Immerzeel et al. 2013). Yet, the biological effects of climate change in these freshwater systems remain poorly understood. While the topographic mosaic of micro-climatic conditions in mountains may provide buffer habitats for cold-adapted species and limit changes on the species pool (Scherrer and Körner 2011), recent studies on high-altitude benthic invertebrate communities indicate climate change-associated losses in species (Jacobsen et al. 2012) and intraspecific genetic diversity (Finn et al. 2014). These studies show that biological impacts of climate change are quite likely. However, data remains limited and concepts for monitoring and mitigating the impacts of climate change on mountain freshwater biota are lacking (e.g. Hering et al. 2009; Kernan et al. 2010), particularly in developing and third world countries. The Himalaya is a particularly good example of this. The region comprises several biodiversity hotspots including Eastern Himalaya which alone accommodates about 40 % of all known freshwater Odonata of continental Southeast Asia (Allen et al. 2010) and is also extremely rich for other stream insects (Wagner et al. 2004; Malicky 2006). The warming trend in the Himalaya is about three times faster than the world average (IPCC 2007; Xu et al. 2009). Regional shifts in monsoon patterns have been observed (Ichiyanagi et al. 2007), and further increases in rainfall frequency and intensity are predicted (Shrestha and Devkota 2010). However, Himalayan freshwater resources are fundamentally important for the population of the surrounding countries
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(Laghari 2013). Nepal, for example, is situated in the central Himalayas, and mountains cover 77 % of its total land area. The country has rich freshwater resources, and a largely poor and natural resource-dependent population. Due to this dependence on natural resources and weak institutional capacity to cope with the range of climate challenges, the country is ranked the fourth most climate-vulnerable country in the world (SPCR 2011). While hydrological monitoring programmes exist, strategies for monitoring the biotic consequences of climate change impacts on rivers and streams are lacking. Dealing with effects of global climate change is difficult. Particularly problematic is managing natural resources and the provisioning of ecosystem services because the relationship among natural resources (e.g. biodiversity or healthy rivers) and ecosystem services (e.g. water power or drinking water) remains poorly understood. Additionally, monitoring climate change impacts in natural systems is costly. Identifying ecosystems or habitats that can either serve as models for climate change impacts at the broader scale or as rapidly responding early warning systems can help focus investments. Such approaches are generally useful, but particularly so in poor countries. A recent approach for identifying areas that are particularly sensitive to climate change is the climate sensitive zone (CSZ) proposed by Bässler et al. (2010). The CSZ approach makes use of increased levels of species turnover associated with elevational ecotones. Ecotones are transition zones between neighbouring areas with different environmental conditions. They are generally characterized by species with narrow environmental tolerances occupying opposite ends of the environmental gradient (e.g. Risser 1993; Yarrow and Marín 2007) and many species reach their upper or lower range limits at the ecotone (e.g. Terborgh 1985; Patterson et al. 1998). The overlap of numerous range limits leads to a situation where the local species community reflects only a small proportion of the regional species pool and species assemblages in different parts of the ecotone differ strongly, i.e. assemblages exhibit high species turnover among sites along the relevant environmental gradients (Jankowski et al. 2009). When environmental conditions change, so does the extent and location of the ecotone, and consequently also the distribution areas of the specialist species at both ends of the environmental gradient (e.g. Risser 1993; Yarrow and Marín 2007; Wasson et al. 2013). Thus, as the ecotone shifts, so do patterns of species turnover. The ecotone community is thus highly responsive to environmental change, and community changes can be recognized early by shifts in species turnover patterns (e.g. Wasson et al. 2013). The CSZ approach explicitly identifies sharp change points in community composition by means of high species turnover along altitudinal gradients, which are used as surrogates of climatic gradients in general, and are strongly correlated with temperature, in particular (Bässler et al. 2010). Other climatically associated environmental parameters of rivers that can be integrated over elevation gradients include patterns of precipitation and resulting flow dynamics. The CSZ approach is thus particularly interesting for running water systems, where ecotones are not as macroscopically evident as in other ecosystems, e.g. between biomes or elevational vegetation zones. While studies of elevational ecotones have been undertaken in various groups of terrestrial and aquatic plants and animals (e.g. Terborgh 1985; Patterson et al. 1998; DeDeckker and Forester 1988), their value for applied climate change monitoring is rarely exploited. The CSZ approach, on the other hand, was explicitly developed to monitor the effects of climate change on biota (Fig. 1). The CSZ concept is based in
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Sampling scheme on tributaries along altitudinal gradient
Community shift present community
future community
ß-Diversity among sites of succesive altitude
High
CSZ
Low
Tributary with sampling site
Indicator taxa (Z+) Indicator taxa (Z-) Other taxa
Future Present
Fig. 1 Hypothetical diagram of the climate sensitive zone (CSZ) and its implementation in streams. Left Hypothetical catchment with tributaries sampled along an altitudinal gradient. Middle Hypothetical altitudinal distribution of the stream taxa and the resulting community composition at different altitudes shown for the present and under projected future climatic conditions. Taxa identified as indicators for low altitudes (z−, green) are likely to expand their range to higher elevations; generalist taxa (grey) are likely to show minimal responses in either direction; taxa identified as indicators for high altitudes (z+, maroon) are likely to shift their ranges to higher elevations. Right Species turnover patterns along the altitudinal gradient are shown for the present (black line) and the expected shift under future climate (dashed grey line). The altitudinal range where community composition changes are greatest (highest levels of species turnover) and where indicator taxa are expected to react first to changing climate conditions reflects the CSZ (grey bar)
vegetation science and was first applied in forest ecosystems in central Europe (Bässler et al. 2010). Our study tests the utility of the CSZ concept in riverine ecosystems using Himalayan streams of Nepal as an example. We focus our approach on benthic macroinvertebrates as these are prevalent in streams around the globe and are the primary indicator organisms in stream and river monitoring because they are known to integrate environmental conditions and respond to environmental shifts or stress (Rosenberg and Resh 1993). Benthic macroinvertebrates are also relatively easy to identify because they are relatively large, spend most (or all) of their life cycles in water, are less mobile than fish, and occur in high abundances. Furthermore, many stream benthic invertebrates are climate sensitive (e.g. Hering et al. 2009; Tierno de Figueroa et al. 2010; Domisch et al. 2011) making their community a useful indicator for monitoring the effects of climate change. In the present research, the CSZ concept is applied to river ecosystems for the first time using benthic invertebrate communities. We believe that the identification of a benthic invertebrate-based CSZ can serve as an early warning tool for climate change and/or help to efficiently prioritize efforts to monitor climate change effects in mountain streams and rivers. Explicitly, we aim to (1) assess whether altitude is a major environmental factor for variation in invertebrate community composition and a useful proxy for a climatic gradient in the central Himalaya that can be used to develop a CSZ, (2) determine a potential CSZ for central
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Himalayan streams along a large altitudinal, and (3) assess if sensitive indicator taxa associated with the CSZ can be identified.
2 Materials and methods 2.1 Study sites The study sites are located in Makalu-Barun, Indrawati, Shivapuri, Gosaikunda, and Langtang valley in the Central Himalaya, Nepal (85° 51′–87° 36′ E and 27° 51′–28° 23′ N). The climatic zone of the study sites ranges from subtropical to alpine. Benthic invertebrates and environmental variables were sampled in 58 streams in eastern and central Nepal between April and June in 2012 and 2013 (Online Resource 1). Sampling sites were selected at approximately 200 m asl intervals along altitudinal gradients between 1500 and 4500 m asl. All the sampling sites are in near-pristine to semi-pristine headwater streams and could only be reached on foot after several days of walking along trekking routes.
2.2 Environmental parameters Prior to collecting benthic samples, we documented catchment characteristics, hydromorphological characteristics, and physico-chemical parameters at each site. We also estimated shading (percentage canopy coverage), flow pattern (proportion of riffles, runs, and pools), velocity (measured with a CP-1 Flow Probe, WTW, Weilheim, Germany), width, depth, and substrate composition (% boulders, cobbles, gravels, and sands), and measured water temperature (°C), conductivity (μS/cm), pH, oxygen content (mg/l), and saturation (%) using a Multi340i (WTW, Weilheim, Germany) at the time of sampling. We set up water temperature loggers (Hobo Pendant; Onset, Bourne, MA, USA) at many of the sampling sites in 2012 to record water temperature for ∼1 year in 2-h intervals. For each site, we extracted mean annual air temperature, mean annual precipitation at 1km2 resolution from the WorldClim data set (http://www.worldclim.org/bioclim), as well as aspect and distance from the spring to the sampling site, i.e. distance from source (dfs) from a 30-m resolution digital elevation model (DEM, NASA, http://reverb.echo.nasa.gov). We plotted annual mean air temperature and mean water temperature (derived from temperature loggers by successively aggregating 2-h data to daily means, daily means to monthly means, and monthly means to annual means) against altitudes of sampling sites to assess the relationship of temperature variables with altitudes (Online Resource 1).
2.3 Benthic macroinvertebrates We applied a multi-habitat sampling approach (Moog 2007) to collect benthic samples. We assessed microhabitat coverage in 10 % intervals over a 100-m river stretch and distributed ten subsamples accordingly among the occurring microhabitats. We considered both mineral (bedrock, megalithal, macrolithal, microlithal, akal, psammal) and organic (periphyton, mosses, macrophytes, coarse woody debris, coarse particulate organic matter, and fine particulate organic matter) microhabitats in the assessment. For each microhabitat-specific subsample, we collected benthic samples by kick sampling, i.e. disrupting the stream bottom over an area of ∼25×25 cm2 whereby organic material and benthic organisms are dislodged and
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transported by the current into a standard 25×25 cm2 frame hand net with a mesh size of 500 μm. We used the procedure from Haase et al. (2004) to reduce sample volume and separate animals from most of the substrate in the field: First, we transferred the aggregated sample from all ten subsamples from the net into a plastic bucket filled halfway with water. We carefully checked and removed coarse organic matter, e.g. twigs, branches, and leaves. We then stirred the remaining sample by hand and passed it through a 500-μm-mesh hand net. We repeated the process until only mineral substrates remained in the bucket. These were discarded. We then transferred the organic material and animals retained in the hand net into a plastic container and preserved the sample in 96 % ethanol in the field. We quantitatively sorted and identified the entire samples without any subsampling in the laboratory to the highest possible taxonomic resolution based on available keys (Morse et al. 1994; Nesemann et al. 2007, 2011; unpublished keys of ASSESS-HKH project (www.assess-hkh.at)). This was genus level for Ephemeroptera, Plecoptera, Trichoptera, and Tricladida; genus or family level for Odonata; species or family level for Oligochaeta; and species level for Mollusca.
2.4 Data analysis All the analyses were performed in R version 3.0.2 (R core team 2013). Prior to analysis, invertebrate taxa occurring in less than 5 % of the samples (≤3 occurrences) were deleted to remove outliers that may represent stochastic occurrences and to minimize the effects of a potential operator bias (Arscott et al. 2006). We analyzed the invertebrate community data without any transformation as the data comprise discrete counts only and only contain numbers ≥0 (O’Hara and Kotze 2010).
Multivariate generalized linear model (GLM) We used GLM to identify which environmental predictors significantly influence the invertebrate community composition, as well as individual taxa. Prior to GLM, we removed highly correlated parameters (r>0.6) and performed independent principal components analyses (PCAs) on groups of environmental parameters related to flow, substrate, and flow patterns, respectively. We ran the final GLM on seven environmental parameters and three PCA axes in the R package mvabund (Wang et al. 2012). A detailed description of the analysis is given in Online Resource 2. Species turnover We assessed species turnover to specifically determine those altitudes that exhibit greatest species turnover as one indicator of the CSZ. We used the Simpson dissimilarity index (beta.sim) following Koleff et al. (2003) to determine changes in species composition along the altitudinal gradient. beta.sim calculates species spatial turnover corrected for influence of richness gradients (see Baselga 2010). To assess species turnover, presence records of each taxon were assembled from replicates of sampling sites of each respective altitude. beta.sim describes species turnover between two consecutive altitudinal sites of 200 m asl and was calculated for each pair of altitudinal band as follows: beta:sim ¼
minðb; cÞ a þ minðb; cÞ
where, a is the number of species shared among both samples, and b and c are the number of species occurring in only one or the other sample. Species turnover ranges from 0 (complete overlap, no dissimilarity) to 1 (no overlap, completely separated species composition).
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Local regression smoothing (LOESS) was used to visualize the trend between species turnover and altitude. We used quadratic polynomial function to examine species turnover changes along the altitudinal gradient.
Threshold indicator taxa analysis (TITAN) We used TITAN (Baker and King 2010) to identify potential change points in both the relative frequency and abundance of individual taxa along an environmental gradient, and assess possible synchrony among taxa change points as evidence for changes in the community. These results can serve to identify the CSZ as well as diagnose taxa that are particularly responsive to the altitudinal gradient and may be used to monitor the CSZ. Additional background and analytical details on TITAN are given in Online Resource 2.
3 Results Following removal of taxa occurring in less than 5 % of samples (≤3 sites), we included 78 taxa (out of 116) from the 58 sites in the analyses (see Appendix S1 in Supporting Information). The taxa included in the analysis occurred in 4 to 37 sites (mean±SD=18.8± 8.6). We observed a rise in taxon richness with an altitude to around 2500 m asl, followed by a slow decrease to around 3100 m asl. A further distinct reduction in richness was associated with altitudes above 3300 m (Online Resource 4). The multivariate GLM showed that altitude (Res.df=46, Dev=561.2, P