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Idiosyncratic responses of meiofaunal assemblages to hippo dung inputs in an estuarine lake
Estuarine, Coastal and Shelf Science 239 (2020) 106745
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Estuarine, Coastal and Shelf Science journal homepage: http://www.elsevier.com/locate/ecss
Idiosyncratic responses of meiofaunal assemblages to hippo dung inputs in an estuarine lake Jessica Dawson a, Deena Pillay a, *, Renzo Perissinotto b a b
Marine Research Institute, University of Cape Town, Biological Sciences Department, Cape Town, 7701, South Africa Institute for Coastal and Marine Research (CMR), Nelson Mandela University, Port Elizabeth, 6031, South Africa
A R T I C L E I N F O
A B S T R A C T
Keywords: Benthos Community structure Connectivity Trophic transfers Hippopotamus amphibious
Animal-mediated trophic resource transfers are important determinants of ecosystem functioning but are influenced by anthropogenic activities. In Africa, hippo defecation can influence aquatic processes at multiple scales, yet little is known about this phenomenon, with repercussions for estuarine benthic ecosystems being a particularly important knowledge gap. Here, we use in situ experiments to test responses of benthic meiofauna to dung loading in the St Lucia Estuary, which is Africa’s largest estuarine ecosystem and home to one of South Africa’s largest hippo populations. Findings indicate that high dung-loading levels negligibly affect meiofaunal community structure, with few community and individual metrics responding significantly. Richness and di versity displayed differential responses at the two experimental sites, with increasing trends occurring at the first site following dung addition but with a reversal at the second site. Similar findings were recorded for abundances of juvenile Assiminea cf. capensis (gastropod) and sizes of Nemata. In relation to prior findings for macrofauna from the same experiment, meiofaunal responses appeared weak and spatially idiosyncratic. We conclude that meiofauna are more robust and opportunistic than macrofauna in responding to dung-loading and suggest that high input rates may shift benthic communities from larger macrofaunal groups to smaller meiofaunal assem blages. We advocate that understanding traits of recipient assemblages that determine their susceptibility to hippo dung is necessary to develop a predictive understanding of this phenomenon. This would be especially important in protected areas that experience freshwater deprivation and support large and expanding hippo populations.
1. Introduction Cross-system connectivity is a major determinant of ecosystem dy namics and functioning (Cadenasso et al., 2003; Marczak et al., 2007; Polis et al., 1997; Strayer et al., 2003). The movement of resources across ecosystem boundaries is a particularly important mediator of connectivity, having key ramifications for trophic interactions and abiotic conditions in receiving environments (Holt, 2008; Huxel et al., 2004; Polis et al., 1997; Richardson et al., 2010). Studies have shown that such transfers are diverse, pervasive across several ecosystem types and span multiple spatial and temporal scales (Marczak et al., 2007; Polis et al., 2004). While research has highlighted the potential for trophic transfers to strengthen bottom-up interactions and facilitate consumer growth and productivity (Cadenasso et al., 2003; Marczak et al., 2007; Richardson et al., 2010), the strength and direction of transfer effects are ultimately dependent on (1) transfer traits (lability,
quantity and quality), (2) the pathway of incorporation into food webs (active or passive, trophic position), (3) consumer functional traits and (4) ecosystem productivity (Marcarelli et al., 2011; Marczak et al., 2007). Transient consumers that migrate across ecosystem boundaries are highly effective in mediating connectivity and resource transfers be tween ecosystems. Such consumers typically increase boundary permeability (Cadenasso et al., 2003; Polis et al., 1997; Vanni, 2002; Vanni and Headworth, 2004), by (1) functioning as trophic resources for higher consumers, (2) physically creating ecosystem corridors that facilitate resource transfers, and/or (3) defecating allochthonous ma terial into recipient systems. In aquatic systems with limited water ex change and minimal discharge, as in semi-arid regions, or those facing freshwater deprivation through abstraction, transient consumers are likely to be key determinants of ecosystem functioning through effects on connectivity and trophic transfers (Abrantes and Sheaves, 2008;
* Corresponding author. E-mail address: [email protected] (D. Pillay). https://doi.org/10.1016/j.ecss.2020.106745 Received 8 December 2019; Received in revised form 25 March 2020; Accepted 28 March 2020 Available online 1 April 2020 0272-7714/© 2020 Elsevier Ltd. All rights reserved.
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Howe and Simenstad, 2015). However, human-mediated changes in the abundance and distribution of such consumers have the potential to alter the strength of connectivity and transfer effects. In Africa, hippos (Hippopotamus amphibius) occupy a distinctive po sition as mediators of terrestrial-aquatic connectivity and resource transfers. This stems predominantly from their amphibious lifestyles and long-distance travel between aquatic and terrestrial feeding grounds (Eltringham, 1999; Owen-Smith, 1988). While hippos are known to in fluence connectivity and resource flows through multiple mechanisms, the direct transfer of basal trophic resources through defecation is arguably the most significant mechanism by which they mediate ma terial flows into aquatic ecosystems. This effect is unique, in that unlike most other forms of cross-system transfers that are temporally pulsed (Naiman et al., 2002; Nakano and Murakami, 2001; Polis et al., 1997; Richardson et al., 2010; Subalusky et al., 2017), defecation by hippos occurs daily, likely over decadal timescales (Subalusky et al., 2015; Taylor, 2013a). Thus, at great population sizes, terrestrial inputs into aquatic ecosystems via hippo defecation can be significant. It has been estimated that hippos of the Mara River (Kenya) transfer roughly 36 tonnes of grasses into the river system daily, based on defecation of roughly 8.7 kg of grass (wet weight) per hippo, per day (Subalusky et al., 2015). An annual input of approximately 5840 tonnes of grass by hippos has been estimated for Lake Naivasha, Kenya (Grey and Harper, 2002). In light of these values, it is questionable whether other natural pro cesses could replicate the degree to which hippo defecation influences resource transfers from terrestrial to aquatic ecosystems. While the importance of hippo dung for the functioning of aquatic systems has been alluded to in prior research (McCarthy et al., 1998; Naiman and Rogers, 1997; Taylor, 2013a), it is only recently that at tempts to rigorously understand such effects have been initiated. The majority of research in this area has focused on biochemical ramifica tions of dung loading on water quality (Dutton et al., 2018; Gereta and Wolanski, 1998; Stears et al., 2018; Subalusky et al., 2015; Wolanski and Gereta, 1999), with a smaller portion dealing with repercussions for particular species or groups at low organisation levels in aquatic eco systems (McCauley et al., 2015; Stears et al., 2018; Subalusky et al., 2018). In contrast, little is known about community level consequences (Masese et al., 2018, 2015), particularly from the perspective of benthic ecosystems. This is an important knowledge gap that needs addressing, given that once voided, hippo dung sinks to the bottom of aquatic habitats and likely interacts with several processes that drive ecological functioning in benthic ecosystems. Additionally, much is known about hippos as vectors of allochthonous transfers in freshwater lakes or riverine ecosystems, but little equivalent knowledge exits in estuaries. Lastly, limited research on hippo defecation constrains understanding of broader ecological effects of hippo declines through much of Africa, as well as their increases in conservation areas. In this paper, we present results from an in situ experiment aimed at quantifying the ecological ramifications of hippo dung inputs for benthic meiofaunal assemblages in the St Lucia Estuary, which is the largest estuarine lake in Africa (Cyrus et al., 2011). The system supports a population of roughly a thousand hippos, which is estimated to be growing at 2–3% per year (Taylor, 2013a). This study was conducted during the tail-end of a protracted and particularly severe dry phase of the system, which was brought on by a combination of drought, water abstraction and long-term mouth-manipulation (Cyrus et al., 2011; Humphries et al., 2016; Taylor, 2013b). During this period, mats of hippo dung were observed over the benthic habitats in areas of the es tuary, particularly where hippos were common (Dawson et al., 2016). This observation provided the central rationale for our study. Our findings were intended not only to shed light on the impacts of hippo dung on benthic meiofauna, but to also understand whether dung can impose additional layers of stress onto benthic ecosystems or ameliorate stress during dry phases. Specifically, we aimed to determine whether meiofaunal responses, from the level of whole communities to individ ual taxa, were positively or negatively influenced by experimental
enrichment of benthic plots with hippo dung. Findings presented in this paper originate from the exact experiment from which previous findings for macrofauna were reported (Dawson et al., 2016). This allows direct comparisons to be made between these groups regarding their toler ances to hippo dung, which in turn facilitates a deeper understanding of benthic responses to dung-loading. 2. Methods The St Lucia Estuary (27� 520 S & 28� 240 S and 32� 210 E & 32� 340 E) is located in the sub-tropical north-east coast of South Africa and forms part of the iSimangaliso Wetland Park, which is a UNESCO World Her itage Site (Perissinotto et al., 2013b). The system comprises three interconnected lakes that discharge into the Indian Ocean via a channel referred to as the Narrows (Fig. 1). The estuary is governed by cyclical, quasi-decadal dry and wet phases that mirror local climatic regimes (Begg, 1978), with the system at the time of this study undergoing a dry-phase between 2002 and 2016. Manipulation of freshwater inflow from the Mfolozi River, combined with increasing abstraction from the system’s four tributaries (Mkhuze, Mzinene, Hluhluwe and Nyalazi rivers; Fig. 1) had stressed the estuary, forcing it into an extreme state over the period in question (Perissinotto et al., 2013b). This dry phase has been described as the most severe in recorded history, with water levels in the system dropping to 10% of the total surface area (Cyrus et al., 2011; Humphries et al., 2016; Whitfield and Taylor, 2009) causing extreme salinities as high as 200 ppt (Cyrus et al., 2011; Perissinotto et al., 2013a). An in situ mesocosm experiment was conducted at two sites located on the Western Shores of South Lake (150 m apart; water depth 40–50 cm; sediment ¼ muddy sand at both sites) within Charter’s Creek to achieve our aims. Ten randomly interspersed (2–3 m apart) inclusion/ exclusion cages (height ¼ 1 m, width and length ¼ 50 cm) were deployed at each of the two experimental sites between October and November 2014 (two treatments: dung inclusion, dung exclusion; n ¼ 5 each per site). Cages were composed of a frame made of four wooden stakes (2 cm diameter, height ¼ 1 m), which were hammered 30 cm into the sediment and surrounded by 3 mm shade mesh. Cage tops were uncovered and had a clearance of 10 cm above the water. Cages were left unmanipulated for two days post-installation, allowing the sediment to resettle and to ensure that cages remained fixed in the sediment. Fresh hippo dung, voided within 24 h, was collected weekly from hippo paths adjacent to Lake Bhangazi South under the supervision of a park ranger (Fig. 1). Dung samples from 3 to 5 individual middens were pooled and homogenised and a sub-sample (300 ml) was added to dung inclusion cages, once per week for a period of six weeks. Inspection of cages prior to weekly dung additions showed that previously added dung did not accumulate – possibly indicating rapid disintegration by microorganism activity and wind mixing (Dawson et al., 2016). The amount of dung added to inclusion cages was determined from prior sampling of sites within the Narrows where hippos were abundant. This involved quantifying mean volumes of dung recorded in benthic grab samples (n ¼ 2 per site, area ¼ 0.026 m2, depth ¼ 20 cm) collected at nine sites along a 2–3 km section and then scaling up to the area of each experimental cage. For this component, grab samples were collected no further than 150 m from three resident hippo pods ranging in size from 15 to 30 individuals per pod. Within 8 h of collection, replicate grabs (n ¼ 3) from each site were combined in buckets, sieved (2 mm) and the volume of remaining dung measured. Exclusion cages were left unma nipulated, with no dung added. Site location, replication level and fre quency of dung addition were determined by a number of factors including accessibility to sites, safe exit routes in cases of danger from wildlife (the site is frequented by Zambezi sharks, Nile crocodiles and small groups of hippos) and the availability of park rangers to supervise dung collection (Dawson et al., 2016). At the termination of the experiment, sediment cores for assessing responses of benthic meiofaunal assemblages (n ¼ 3 per cage, diameter 2
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Fig. 1. Map showing (a) the geographical location within South Africa of the St Lucia System, (b) positions of Charter’s Creek (in situ experimental site) and Lake Bhangazi South (site where dung was collected) and (c) dung accumulation due to excretion by resident hippos. NB: (b) shows system boundaries and not water levels at the time of the study.
¼ 2 cm, depth ¼ 1 cm) were collected following established methods used in South African estuaries, including the St Lucia Estuary (Bownes and Perissinotto, 2012; Nozais et al., 2005; Pillay and Perissinotto, 2009). Samples were collected from central portions of cages to avoid edge effects, sieved in the laboratory through a 400 μm mesh to remove macrofauna and then again over a 40 μm mesh, followed by preservation in an ethanol-Rose Bengal solution. Meiofaunal organisms were identi fied to the lowest possible taxonomic level and enumerated. The size of discriminating meiofaunal taxa, identified by SIMPER to cumulatively account for 90% of the community dissimilarity between treatments at each site, was determined using photographs input into ImageJ (htt
ps://imagej.nih.gov). Meiofauna were photographed using a Leica DM 500 compound microscope, fitted with a Leica ICC50 camera. Size was determined in the following way for dominant taxa: total length (head to tail) was measured for Nemata, the width of the 5th setigerous segment was measured for Polydora sp. and total width for foraminiferans, while for Assiminea cf. capensis, distance from the tip of the spire to the base of the aperture was used. With the exception of Polydora sp., size mea surements were made on whole organisms. All multivariate analyses were carried out using PRIMER v6.1 (un standardized and transformed Log (x þ 1) data). Spatial variability in meiofaunal community structure (based on abundance data) was 3
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visually assessed using non-metric multidimensional scaling ordinations (nMDS), with PERMANOVA (permutational analysis of variance) providing quantitative support for groupings, based on Bray-Curtis similarity matrices. For PERMANOVA analyses, dung treatments (dung exclusion/inclusion) were nested within site (the highest spatial factor within the nested hierarchical design). SIMPER (similarity percentages) was used to identify the discriminating taxa that cumulatively contrib uted 90% to community dissimilarity between dung treatments within sites. Meiofaunal community descriptors (total abundance, richness, evenness and diversity) were calculated using the DIVERSE function. Nested ANOVA (analysis of variance) was employed to determine the influence of site and dung enrichment on meiofaunal community de scriptors (dung treatment nested within site). The effects of site and dung treatment on the abundance and size of individual taxa (identified by SIMPER) were also determined using Nested AVOVA. Tests for normality (Q-Q plots) and homogeneity of variances (Bartlett Tests) were conducted prior to parametric testing. Where necessary, data were transformed (Log (x þ 1), square root or 4th root) before parametric testing. The statistical programming language, R was used to conduct all univariate statistical tests (R Core Team, 2016). 3. Results Meiofaunal community structure was statistically indistinguishable between sites (PERMANOVA pseudo F1,59 ¼ 0.726; p ¼ 0.684) and dung treatments (PERMANOVA pseudo F2,59 ¼ 1.717; p ¼ 0.136). This was visually supported by nMDS ordinations, showing overlap of samples between different sites and dung treatments (Fig. 2; See Supplementary Table 1 for list of taxa collected between the two experimental sites). Meiofaunal abundance visually decreased following hippo dung enrichment, with abundance decreasing by 26.8% at Site 1 and 37.5% at Site 2. However, neither dung treatment nor site significantly affected meiofaunal abundance (Table 1, Fig. 3, Nested ANOVA, Site: F1,52 ¼ 1.235, p ¼ 0.271, Dung Treatment: F2,52 ¼ 1.832, p ¼ 0.170). Meio faunal richness was not significantly affected by site (Table 1, Fig. 3; Nested ANOVA, F1,52 ¼ 0.012, p ¼ 0.913), but was affected by dung treatment (Nested ANOVA, F2,52 ¼ 5.083, p ¼ 0.010). At Site 1, richness increased with the addition of dung, whereas the reverse was evident at Site 2. Meiofaunal evenness was statistically distinguishable between sites, with values being lower at Site 1 than at Site 2 (Table 1, Fig. 3, Nested ANOVA, F1,52 ¼ 8.384, p ¼ 0.006). Evenness was not signifi cantly different between dung treatments (Table 1, Fig. 3, Nested ANOVA, F2,52 ¼ 2.202, p ¼ 0.121). Conversely, meiofaunal diversity did not differ between experiment sites (Table 1, Fig. 3, Nested ANOVA, F1,52 ¼ 1.628, p ¼ 0.208) but was significantly affected by dung treat ment (Table 1, Fig. 3, Nested ANOVA, F2,52 ¼ 6.238, p ¼ 0.004). At Site 1, diversity increased with dung enrichment but decreased with dung addition at Site 2. This pattern mirrored that observed for meiofaunal richness. At an individual taxon level, SIMPER analyses identified four meio faunal taxa that accounted for 90% of the dissimilarity between dung treatments at Sites 1 and 2 (Table 2). Meiofaunal taxa exhibited spatially idiosyncratic responses to dung, with increasing and decreasing trends occurring within taxa depending on the site at which the experiment was conducted. At Site 1, the abundance of one taxon decreased and 3 taxa increased to varying degrees, whereas the abundance of all four domi nant taxa at Site 2 were depressed following dung enrichment. Of the four taxa identified by SIMPER to account for 90% of the dissimilarity between dung treatments, only one taxon (Assiminea cf. capensis) was significantly affected by both site and dung treatment (Table 3, Fig. 4; Nested ANOVA, Site: F1,52 ¼ 10.467, p ¼ 0.002; Dung Treatment: F2,52 ¼ 3.478, p ¼ 0.038). At Site 1, dung enrichment resulted in increases in abundance of A. cf. capensis, whereas at Site 2, abundance decreased in dung treatment plots compared to un-enriched plots. The abundance of one taxon, Foraminifera, differed marginally non-significantly between sites (Table 3, Fig. 4; Nested ANOVA, Site: F1,52 ¼ 3.554 p ¼ 0.065). Both
Fig. 2. Non-metric multidimensional scaling ordination (nMDS) showing spatial variation in meiofaunal community structure (abundance data) between sites and dung treatments. A. shows samples from dung inclusion (filled sym bols) and exclusion (unfilled symbols) treatments at Sites 1 (black) & 2 (grey symbols). B. shows dung inclusion and exclusion treatments at Site 1, while C. shows dung inclusion and exclusion treatments at Sites 2.
Nemata and Polydora sp. displayed marginally non-significant dung treatment responses (Nested ANOVA p ¼ 0.072 and p ¼ 0.067 respec tively). However, responses were erratic, as abundance of Nemata decreased at Site 2 with dung addition, but at Site 1, abundance of Polydora sp. increased (Fig. 4). In terms of sizes of dominant taxa, only Nemata displayed significant responses to site and dung treatment (Table 3, Fig. 5; Nested ANOVA, Site: F1,46 ¼ 5.361, p ¼ 0.025; Dung Treatment: F2,46 ¼ 16.316, p < 0.001). At Site 1, Nemata were larger in dung enrichment plots, but were 4
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4. Discussion
Table 1 Results of Nested ANOVA testing for differences in meiofaunal community de scriptors between sites and dung treatments. Bold p-values indicate statistically significant differences. F ¼ F-statistic, p ¼ significance level, DF ¼ degrees of freedom.
Our study was motivated by a need to understand responses of meiofaunal assemblages to hippo dung inputs in the St Lucia Estuary, given that meiofauna are key components of benthic ecosystems by virtue of critical functions they provide (Pillay et al., 2013; Schratz berger and Ingels, 2017). Our study additionally sought to understand the role played by dung as a potential stressor in a system afflicted by long-term stress through drought, mouth closure and water abstraction. The broader goal of the study was to understand ramifications of dung inputs for benthic assemblages and ecosystems more broadly, which is a significant knowledge gap currently. Our findings indicate that meio faunal responses were not always detectable, and when evident, were complex and idiosyncratic, mainly due to differences in the direction of responses spatially. Based on levels of dung used and environmental contexts under which the experiment was conducted, our data show (1) neutral responses at the community level and for total abundance and evenness, and (2) site-specific idiosyncratic (positive and negative) re sponses of meiofaunal richness, diversity and individual taxa. Sizes of meiofaunal taxa also responded idiosyncratically to dung, with both
Nested ANOVA Site Meiofaunal Meiofaunal Richness Meiofaunal Meiofaunal
Treatment
F
DF
p
F
DF
p
Abundance Species
1.235 0.012
(1,52) (1,52)
0.271 0.913
1.832 5.083
(2,52) (2,52)
0.170 0.010
Evenness Diversity
8.384 1.628
(1,52) (1,52)
0.006 0.208
2.202 6.238
(2,52) (2,52)
0.121 0.004
smaller in enriched plots at Site 2. Foraminifera, A. cf. capensis and Polydora sp. all showed non-significant responses to both site and treatment (Table 3, Fig. 5; Nested ANOVA p > 0.05 for all).
Fig. 3. Spatial variation in mean (�1 SE) meiofaunal community metrics at the two experimental sites in response to dung addition (D - black) and exclusion (N grey). Numbers in treatment name ¼ site number. Results of Nested ANOVA are superimposed on graphs. 5
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enrichment, given that the St Lucia Estuary had been undergoing a se vere drought over a 10-year period, which resulted in decadal mouth closure, hyper-salinity (200) and desiccation of 90% of the lakes at the peak of the drought (Cyrus et al., 2011; Humphries et al., 2016; Peri ssinotto et al., 2013a, b; Whitfield and Taylor, 2009). It could also be argued that low sample sizes and high data variability may have been responsible for the lack of dung effects detected. However, data vari ability was not always large in our experiment (Figs. 3–5), even in cases where non-significant treatment effects were detected (e.g. Fig. 5). Nevertheless, the study may have benefited from increased sample sizes in order for marginal outcomes to be clarified. Responses of meiofaunal richness and diversity to enrichment by dung were particularly interesting, with increases in these metrics recorded at Site 1, but with reductions occurring at Site 2. This would suggest that abiotic contexts in which dung inputs occur determine the direction of these community metric responses to dung. While we lack quantitative data on abiotic conditions at experimental sites, observa tions during experimental set-up and weekly monitoring indicate greater wind-driven wave action at Site 1 than at Site 2 (Dawson et al., 2016). This would imply that stagnating conditions, as observed at Site 2, may negatively impact community metrics leading to declines, while flowing conditions may induce stimulatory effects. This suggestion is consistent with contemporary ideas regarding biotic responses to hippo dung, with studies hypothesising that non-linear effects of dung may be associated with flow and dung residence times, with low flow and high dung residence leading to deteriorating water quality and hypoxia (Dawson et al., 2016; Dutton et al., 2018; Gereta and Wolanski, 1998; Stears et al., 2018; Subalusky et al., 2018). This idea can also account for responses of individual taxa that we observed, given that at Site 1 all but one dominant taxon increased in abundance following enrichment, while at Site 2 decreasing trends were observed for all dominant taxa. Similarly, sizes of Nemata were greater in dung inclusion plots at Site 1 but this trend was reversed at Site 2. In these cases, stagnation and deteriorating water quality can explain declining trends at Site 2, whereas increasing trends may be related to positive effects induced by dung, probably in the form of increased trophic resource either directly or indirectly (e.g. POM, bacteria). Our previous published work from this experiment showed that microalgal biomass declined at Sites 1 and 2 by roughly 50 and 70% following enrichment with hippo dung, likely due to dung shading the benthos and reducing primary productivity (Dawson et al., 2016). The declining trends that we recorded in meiofaunal metrics (richness and diversity) and abundance of individual taxa and their sizes at Site 2 can thus be explained by dung-induced declines in microalgal biomass (resource limitation). However, this mechanism does not entirely explain the trends recorded in our experiment, given that at Site 1 a decrease in microalgal biomass by 50% with the addition of dung resulted in increasing trends in the above-mentioned meiofaunal vari ables. This finding is suggestive of meiobenthic assemblages in our experiment not being affected completely by bottom-up effects associ ated with resource limitation, as suggested by Coull (1999). This idea is supported by previous work showing weak grazing pressure exerted by meiofauna on microalgae due to limited reliance on microphytobenthos as a trophic resource, because of the availability of alternative trophic resources such as bacteria and other meiofauna (Nozais et al., 2005). Although dung inputs evidently reduce microalgal abundance (Dawson et al., 2016), inputs may also potentially increase benthic bacterial biomass; firstly, through the addition of hippo gut bacteria, and sec ondly, by providing a substrate for aquatic bacterial decomposers to colonise (Jones, 1992). In addition, meiofauna are known to stimulate bacterial abundance as grazing of these microbiota keeps the population in the active growth phase, and their production of nitrogen rich mucus stimulates and traps additional microbes (Riemann and Helmke, 2002; Schratzberger and Ingels, 2017). This mechanism could explain the mismatch between microalgal biomass and meiofaunal metrics and abundance of individual taxa, particularly at Site 1.
Table 2 Meiofaunal taxa identified by SIMPER to cumulatively account for 90% of the community dissimilarity between dung exclusion and inclusion treatments at Site 1 and 2, based on abundance data. Bold text highlights taxa showing an increase in abundance with the addition of hippo dung. Letters in parentheses next to taxon names denote broad taxonomic grouping: (F) ¼ Foraminifera, (N) ¼ Nemata, (G) ¼ Gastropoda, (P) ¼ Polychaeta. Site 1 Dung
Site 2 No Dung
Dung
No Dung
Dominant Taxa (Abundance data)
Average abundance
Dominant Taxa (Abundance data)
Average abundance
Foraminifera (F)
24.53
44.80
8.13
13.33
Nemata (N) Assiminea cf. capensis (G) Polydora sp. (P)
8.00 5.93
7.53 3.47
Assiminea cf. capensis (G) Nemata (N) Foraminifera (F)
8.20 6.87
14.00 11.07
2.53
1.20
Polydora sp. (P)
1.20
1.33
Table 3 Results of Nested ANOVA testing for differences in individual meiofaunal taxa abundance and size between sites and dung treatments. Bold p-values indicate statistically significant differences. Letters in parentheses next to taxon names denote broad taxonomic grouping: (F) ¼ Foraminifera, (N) ¼ Nemata, (G) ¼ Gastropoda, (P) ¼ Polychaeta. Nested ANOVA Individual taxa abundance Site
Treatment
Taxa
F
DF
p
F
DF
p
Foraminifera (F) Nemata (N) Assiminea cf. capensis (G) Polydora sp. (P)
3.554 2.246 10.467
(1,52) (1,52) (1,52)
0.065 0.140 0.002
1.364 2.754 3.478
(2,52) (2,52) (2,52)
0.265 0.072 0.038
2.282
(1,52)
0.137
2.846
(2,52)
0.067
Individual taxa size Site
Treatment
Taxa
F
DF
p
F
DF
p
Foraminifera (F) Nemata (N) Assiminea cf. capensis (G) Polydora sp. (P)
0.473 5.361 1.186
(1,44) (1,46) (1,45)
0.495 0.025 0.282
1.171 16.316 0.554
(2,44) (2,46) (2,45)
0.192 < 0.001 0.578
0.816
(1,11)
0.386
0.300
(2,11)
0.746
positive and negative effects recorded within taxa spatially. The lack of significant dung effects at the community level for meiofauna, either visually or statistically, suggests that dung had limited impacts on species composition and distribution. However, detectable effects on community metrics and individual taxa and their sizes indi cate that effects of dung did occur, but subtly. Here, it could be argued that the lack of statistically significant effects at the community level could be due to low taxonomic resolution used in our study. However, the fact that significant dung effects were noted for meiofaunal richness suggests that resolution may not have been an issue and that there was ample variability for dung effects to be detected. Subtle communitylevel effects of dung may relate to the fact that under stressful condi tions, communities may comprise a subset of assemblages that are highly tolerant to changing conditions (MacKay et al., 2010). This idea has been proposed for benthic macrofauna in the St Lucia Estuary, to account for the lack of significant compositional shifts in assemblages in space and time under drought conditions, despite changes in abundance of core species (MacKay et al., 2010; Pillay et al., 2013). This mechanism can explain the lack of community-level responses of meiofauna to dung 6
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Fig. 4. Spatial variation in mean abundance (�1 SE) of dominant meiofauna taxa at the two experimental sites in response to dung addition (D – black) and exclusion (N – grey). Numbers in treatment name ¼ site number. Results of Nested ANOVA are superimposed on graphs.
The fact that the meiofauna data used in this paper originate from the exact experiment used in previously reported findings for macrofauna (Dawson et al., 2016), allows direct comparisons to be made between these benthic faunistic groups so that an understanding of their sensi tivities to dung could be assessed. Community-level differences were obvious for macrofauna in response to dung addition at both experi mental sites (Dawson et al., 2016), but this did not manifest for meio fauna (Fig. 2). Macrofaunal abundance, richness and biomass declined following dung addition, but metrics for meiofauna showed contrasting responses, with both positive and negative effects emerging depending on spatial location (Fig. 3). Lastly, the majority of macrofaunal taxa displayed declining trends following dung addition, whereas meiofaunal taxa displayed both positive and negative responses. Overall, our com bined findings suggest that benthic macrofauna are more sensitive to dung inputs, with meiofauna appearing to be more robust and resilient. This conclusion aligns with previous research demonstrating a greater tolerance of meiofauna to ecological stressors than macrofauna (e.g. Josefson and Widbom, 1988; Warwick et al., 1990; Somerfield et al., 2006).
The differential responses of macro- and meiofauna to hippo dung recorded in this experiment are likely a product of the unique morphological and life-history traits exhibited by these groups (Loreau et al., 2001). Macrofaunal life-cycles typically incorporate planktonic larval stages, implying that hippo dung can influence colonisation and recruitment by (1) forming a physical barrier that restricts larval set tlement, and/or (2) generating negative settlement cues as a result of altered water and sediment biogeochemistry through decomposition (Dawson et al., 2016). In contrast, the majority of meiofaunal taxa do not have larval stages, but instead undergo direct development within sediments (Dahms and Qian, 2004). Therefore, dung may not function as a barrier to meiofaunal recruitment at the sediment surface. Meiofauna may additionally be positively affected by the abrasive effects of hippo dung, as their lack of a mobile larval phase makes them partially dependant on recolonization through resuspension of sediment into the water column (Josefson and Widbom, 1988). Given that low oxygen states are known to select against large-bodied benthic organisms (Pearson and Rosenberg, 1978), the greater size of macrofauna is also a trait that negatively predisposes them to low oxygen levels associated 7
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Fig. 5. Spatial variation in mean size (�1 SE) of dominant individual meiofauna taxa at the two experimental sites in response to dung addition (D - black) and dung exclusion (N - grey). Numbers in treatment name ¼ site number. Results of Nested ANOVA are superimposed on graphs.
with decomposition of dung. Lastly, resilience and opportunistic re sponses of meiofauna to dung inputs may be linked to their rapid turnover rates (Schratzberger and Ingels, 2017). Overall, our combined work quantifying responses of macrofaunal and meiofaunal assemblages has shed light on potential responses of benthic ecosystems to dung loading by hippos. Given the largely declining trends observed for macrofauna, but neutral and spatially idiosyncratic patterns recorded for meiofauna, we suggest that high dung inputs may induce size shifts in benthic assemblages, from larger, macrofauna groups to smaller meiofaunal assemblages. If this is the case, then it is possible that functions provided by larger organismal groups, such as bioturbation, sediment oxygenation and nutrient fluxes (Pillay et al., 2013) would be at risk from high dung inputs, but those provided by meiofauna (nutrient cycling, organic matter decomposi tion) may be more robust, thus potentially offering some resilience to high dung loading. We suggest that future studies could focus on un derstanding (1) the susceptibilities of different benthic organismal groups to dung loading, (2) the functional consequences arising from potential community shifts and (3) traits and/or life history strategies that positively or negatively predispose organism groupings to dung
loading. Further research in these areas would be useful in developing a mechanistic and predictive understanding of dung-loading on benthic ecosystems more broadly. This would be particularly important in conservation areas that are threatened by freshwater deprivation and in which hippo population sizes are large and increasing. However, it would also be important to find innovative solutions to minimise safety risks posed by hippos (and other wildlife) to humans, for appropriate experimental controls and adequate sample sizes to be obtained. We also advocate for appropriate abiotic data to be collected from similar studies to develop a mechanistic understanding of pathways by which dung effects are propagated across the entire food web. Lastly, assessing changes in depth distributions of benthic organisms will allow for an expansion in understanding of how hippo dung inputs affect benthic ecosystems. Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. 8
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CRediT authorship contribution statement
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Jessica Dawson: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Writing - original draft, Writing - review & editing. Deena Pillay: Conceptualization, Funding acquisition, Project administration, Resources, Supervision, Writing - original draft, Writing - review & editing. Renzo Perissinotto: Conceptualization, Funding acquisition, Writing - review & editing. Acknowledgements We are thankful to iSimangaliso Wetlands Park Authority, Ezemvelo KZN Wildlife, Geoffrey Clinning and students from Hluhluwe-Imfolozi Park (HiP) Research facility for general assistance. Funding was gran ted by the National Research Foundation (NRF), German Academic Exchange Service (DAAD), Carnegie and Andrew Mellon Foundations and The University of Cape Town (UCT). Appendix A. Supplementary data Supplementary data to this article can be found online at https://doi. org/10.1016/j.ecss.2020.106745. References Cadenasso, M.L., Pickett, S.T.A., Weathers, K.C., Jones, C.G., 2003. A framework for a theory of ecological boundaries. Bioscience 53, 750–758. https://doi.org/10.1641/ 0006-3568(2003)053[0750:AFFATO]2.0.CO;2. Strayer, D.L., Power, M.E., Fagan, W.F., Pickett, S.T.A., Belnap, J., 2003. A classification of ecological boundaries. Bioscience 53 (723). https://doi.org/10.1641/0006-3568 (2003)053[0723:ACOEB]2.0.CO;2. Abrantes, K., Sheaves, M., 2008. Incorporation of terrestrial wetland material into aquatic food webs in a tropical estuarine wetland. Estuar. Coast Shelf Sci. 80, 401–412. https://doi.org/10.1016/j.ecss.2008.09.009. Begg, G., 1978. The Estuaries of Natal. Natal Town and Regional Planning Report 41. Pietermaritzburg, South Africa. Bownes, S.J., Perissinotto, R., 2012. Community structure and composition of meiofauna over a sea-induced mouth-breaching event in St Lucia Estuary, South Africa. Mar. Ecol. Prog. Ser. 463, 105–126. https://doi.org/10.3354/meps09870. Coull, B.C., 1999. Role of meiofauna in estuarine soft-bottom habitats. Aust. J. Ecol. 24, 327–343. https://doi.org/10.1046/j.1442-9993.1999.00979.x. Cyrus, D., Jerling, H., MacKay, F., Vivier, L., 2011. Lake St Lucia, Africa’s largest estuarine lake in crisis: combined effects of mouth closure, low levels and hypersalinity. South Afr. J. Sci. 107, 1–13. https://doi.org/10.4102/sajs.v107i5/ 6.291. Dahms, H.-U., Qian, P.-Y., 2004. Life histories of the Harpacticoida (Copepoda, Crustacea): a comparison with meiofauna and macrofauna. J. Nat. Hist. 38, 1725–1734. https://doi.org/10.1080/0022293031000156321. Dawson, J., Pillay, D., Roberts, P.J., Perissinotto, R., 2016. Declines in benthic macroinvertebrate community metrics and microphytobenthic biomass in an estuarine lake following enrichment by hippo dung. Sci. Rep. 6, 37359. https://doi. org/10.1038/srep37359. Dutton, C.L., Subalusky, A.L., Hamilton, S.K., Rosi, E.J., Post, D.M., 2018. Organic matter loading by hippopotami causes subsidy overload resulting in downstream hypoxia and fish kills. Nat. Commun. 9, 1–10. https://doi.org/10.1038/s41467-018-043916. Eltringham, S.K., 1999. The Hippos: Natural History and Conservation. Acedemic Press. Gereta, E., Wolanski, E., 1998. Wildlife-water quality interactions in the serengeti national park, Tanzania. Afr. J. Ecol. 36, 1–14. https://doi.org/10.1046/j.13652028.1998.102-89102.x. Grey, J., Harper, D., 2002. Using stable isotope analyses to identify allochthonous inputs to Lake Naivasha mediated via the hippopotamus gut. Isot. Environ. Health Stud. 38, 245–250. https://doi.org/10.1080/10256010208033269. Holt, R.D., 2008. Theoretical perspectives on resource pulses. Ecology 89, 671–681. https://doi.org/10.1890/07-0348.1. Howe, E.R., Simenstad, C.A., 2015. Using stable isotopes to discern mechanisms of connectivity in estuarine detritus-based food webs. Mar. Ecol. Prog. Ser. 518, 13–29. https://doi.org/10.3354/meps11066. Humphries, M.S., Green, A.N., Finch, J.M., 2016. Evidence of El Ni~ no driven desiccation cycles in a shallow estuarine lake: the evolution and fate of Africa’s largest estuarine system, Lake St Lucia. Global Planet. Change 147, 97–105. https://doi.org/10.1016/ j.gloplacha.2016.11.002. Huxel, G.R., Polis, G.A., Holt, R.D., 2004. At the frontier of the integration of food web ecology and landscape ecology. In: Polis, G.A., Power, M.E., Huxel, G.R. (Eds.), Food Webs at the Landscape Level. University of Chicago Press, pp. 434–451. Jones, R.I., 1992. The influence of humic substances on lacustrine planktonic food chains. Hydrobiologia 229, 73–91.
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Estuarine, Coastal and Shelf Science journal homepage: http://www.elsevier.com/locate/ecss
Idiosyncratic responses of meiofaunal assemblages to hippo dung inputs in an estuarine lake Jessica Dawson a, Deena Pillay a, *, Renzo Perissinotto b a b
Marine Research Institute, University of Cape Town, Biological Sciences Department, Cape Town, 7701, South Africa Institute for Coastal and Marine Research (CMR), Nelson Mandela University, Port Elizabeth, 6031, South Africa
A R T I C L E I N F O
A B S T R A C T
Keywords: Benthos Community structure Connectivity Trophic transfers Hippopotamus amphibious
Animal-mediated trophic resource transfers are important determinants of ecosystem functioning but are influenced by anthropogenic activities. In Africa, hippo defecation can influence aquatic processes at multiple scales, yet little is known about this phenomenon, with repercussions for estuarine benthic ecosystems being a particularly important knowledge gap. Here, we use in situ experiments to test responses of benthic meiofauna to dung loading in the St Lucia Estuary, which is Africa’s largest estuarine ecosystem and home to one of South Africa’s largest hippo populations. Findings indicate that high dung-loading levels negligibly affect meiofaunal community structure, with few community and individual metrics responding significantly. Richness and di versity displayed differential responses at the two experimental sites, with increasing trends occurring at the first site following dung addition but with a reversal at the second site. Similar findings were recorded for abundances of juvenile Assiminea cf. capensis (gastropod) and sizes of Nemata. In relation to prior findings for macrofauna from the same experiment, meiofaunal responses appeared weak and spatially idiosyncratic. We conclude that meiofauna are more robust and opportunistic than macrofauna in responding to dung-loading and suggest that high input rates may shift benthic communities from larger macrofaunal groups to smaller meiofaunal assem blages. We advocate that understanding traits of recipient assemblages that determine their susceptibility to hippo dung is necessary to develop a predictive understanding of this phenomenon. This would be especially important in protected areas that experience freshwater deprivation and support large and expanding hippo populations.
1. Introduction Cross-system connectivity is a major determinant of ecosystem dy namics and functioning (Cadenasso et al., 2003; Marczak et al., 2007; Polis et al., 1997; Strayer et al., 2003). The movement of resources across ecosystem boundaries is a particularly important mediator of connectivity, having key ramifications for trophic interactions and abiotic conditions in receiving environments (Holt, 2008; Huxel et al., 2004; Polis et al., 1997; Richardson et al., 2010). Studies have shown that such transfers are diverse, pervasive across several ecosystem types and span multiple spatial and temporal scales (Marczak et al., 2007; Polis et al., 2004). While research has highlighted the potential for trophic transfers to strengthen bottom-up interactions and facilitate consumer growth and productivity (Cadenasso et al., 2003; Marczak et al., 2007; Richardson et al., 2010), the strength and direction of transfer effects are ultimately dependent on (1) transfer traits (lability,
quantity and quality), (2) the pathway of incorporation into food webs (active or passive, trophic position), (3) consumer functional traits and (4) ecosystem productivity (Marcarelli et al., 2011; Marczak et al., 2007). Transient consumers that migrate across ecosystem boundaries are highly effective in mediating connectivity and resource transfers be tween ecosystems. Such consumers typically increase boundary permeability (Cadenasso et al., 2003; Polis et al., 1997; Vanni, 2002; Vanni and Headworth, 2004), by (1) functioning as trophic resources for higher consumers, (2) physically creating ecosystem corridors that facilitate resource transfers, and/or (3) defecating allochthonous ma terial into recipient systems. In aquatic systems with limited water ex change and minimal discharge, as in semi-arid regions, or those facing freshwater deprivation through abstraction, transient consumers are likely to be key determinants of ecosystem functioning through effects on connectivity and trophic transfers (Abrantes and Sheaves, 2008;
* Corresponding author. E-mail address: [email protected] (D. Pillay). https://doi.org/10.1016/j.ecss.2020.106745 Received 8 December 2019; Received in revised form 25 March 2020; Accepted 28 March 2020 Available online 1 April 2020 0272-7714/© 2020 Elsevier Ltd. All rights reserved.
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Howe and Simenstad, 2015). However, human-mediated changes in the abundance and distribution of such consumers have the potential to alter the strength of connectivity and transfer effects. In Africa, hippos (Hippopotamus amphibius) occupy a distinctive po sition as mediators of terrestrial-aquatic connectivity and resource transfers. This stems predominantly from their amphibious lifestyles and long-distance travel between aquatic and terrestrial feeding grounds (Eltringham, 1999; Owen-Smith, 1988). While hippos are known to in fluence connectivity and resource flows through multiple mechanisms, the direct transfer of basal trophic resources through defecation is arguably the most significant mechanism by which they mediate ma terial flows into aquatic ecosystems. This effect is unique, in that unlike most other forms of cross-system transfers that are temporally pulsed (Naiman et al., 2002; Nakano and Murakami, 2001; Polis et al., 1997; Richardson et al., 2010; Subalusky et al., 2017), defecation by hippos occurs daily, likely over decadal timescales (Subalusky et al., 2015; Taylor, 2013a). Thus, at great population sizes, terrestrial inputs into aquatic ecosystems via hippo defecation can be significant. It has been estimated that hippos of the Mara River (Kenya) transfer roughly 36 tonnes of grasses into the river system daily, based on defecation of roughly 8.7 kg of grass (wet weight) per hippo, per day (Subalusky et al., 2015). An annual input of approximately 5840 tonnes of grass by hippos has been estimated for Lake Naivasha, Kenya (Grey and Harper, 2002). In light of these values, it is questionable whether other natural pro cesses could replicate the degree to which hippo defecation influences resource transfers from terrestrial to aquatic ecosystems. While the importance of hippo dung for the functioning of aquatic systems has been alluded to in prior research (McCarthy et al., 1998; Naiman and Rogers, 1997; Taylor, 2013a), it is only recently that at tempts to rigorously understand such effects have been initiated. The majority of research in this area has focused on biochemical ramifica tions of dung loading on water quality (Dutton et al., 2018; Gereta and Wolanski, 1998; Stears et al., 2018; Subalusky et al., 2015; Wolanski and Gereta, 1999), with a smaller portion dealing with repercussions for particular species or groups at low organisation levels in aquatic eco systems (McCauley et al., 2015; Stears et al., 2018; Subalusky et al., 2018). In contrast, little is known about community level consequences (Masese et al., 2018, 2015), particularly from the perspective of benthic ecosystems. This is an important knowledge gap that needs addressing, given that once voided, hippo dung sinks to the bottom of aquatic habitats and likely interacts with several processes that drive ecological functioning in benthic ecosystems. Additionally, much is known about hippos as vectors of allochthonous transfers in freshwater lakes or riverine ecosystems, but little equivalent knowledge exits in estuaries. Lastly, limited research on hippo defecation constrains understanding of broader ecological effects of hippo declines through much of Africa, as well as their increases in conservation areas. In this paper, we present results from an in situ experiment aimed at quantifying the ecological ramifications of hippo dung inputs for benthic meiofaunal assemblages in the St Lucia Estuary, which is the largest estuarine lake in Africa (Cyrus et al., 2011). The system supports a population of roughly a thousand hippos, which is estimated to be growing at 2–3% per year (Taylor, 2013a). This study was conducted during the tail-end of a protracted and particularly severe dry phase of the system, which was brought on by a combination of drought, water abstraction and long-term mouth-manipulation (Cyrus et al., 2011; Humphries et al., 2016; Taylor, 2013b). During this period, mats of hippo dung were observed over the benthic habitats in areas of the es tuary, particularly where hippos were common (Dawson et al., 2016). This observation provided the central rationale for our study. Our findings were intended not only to shed light on the impacts of hippo dung on benthic meiofauna, but to also understand whether dung can impose additional layers of stress onto benthic ecosystems or ameliorate stress during dry phases. Specifically, we aimed to determine whether meiofaunal responses, from the level of whole communities to individ ual taxa, were positively or negatively influenced by experimental
enrichment of benthic plots with hippo dung. Findings presented in this paper originate from the exact experiment from which previous findings for macrofauna were reported (Dawson et al., 2016). This allows direct comparisons to be made between these groups regarding their toler ances to hippo dung, which in turn facilitates a deeper understanding of benthic responses to dung-loading. 2. Methods The St Lucia Estuary (27� 520 S & 28� 240 S and 32� 210 E & 32� 340 E) is located in the sub-tropical north-east coast of South Africa and forms part of the iSimangaliso Wetland Park, which is a UNESCO World Her itage Site (Perissinotto et al., 2013b). The system comprises three interconnected lakes that discharge into the Indian Ocean via a channel referred to as the Narrows (Fig. 1). The estuary is governed by cyclical, quasi-decadal dry and wet phases that mirror local climatic regimes (Begg, 1978), with the system at the time of this study undergoing a dry-phase between 2002 and 2016. Manipulation of freshwater inflow from the Mfolozi River, combined with increasing abstraction from the system’s four tributaries (Mkhuze, Mzinene, Hluhluwe and Nyalazi rivers; Fig. 1) had stressed the estuary, forcing it into an extreme state over the period in question (Perissinotto et al., 2013b). This dry phase has been described as the most severe in recorded history, with water levels in the system dropping to 10% of the total surface area (Cyrus et al., 2011; Humphries et al., 2016; Whitfield and Taylor, 2009) causing extreme salinities as high as 200 ppt (Cyrus et al., 2011; Perissinotto et al., 2013a). An in situ mesocosm experiment was conducted at two sites located on the Western Shores of South Lake (150 m apart; water depth 40–50 cm; sediment ¼ muddy sand at both sites) within Charter’s Creek to achieve our aims. Ten randomly interspersed (2–3 m apart) inclusion/ exclusion cages (height ¼ 1 m, width and length ¼ 50 cm) were deployed at each of the two experimental sites between October and November 2014 (two treatments: dung inclusion, dung exclusion; n ¼ 5 each per site). Cages were composed of a frame made of four wooden stakes (2 cm diameter, height ¼ 1 m), which were hammered 30 cm into the sediment and surrounded by 3 mm shade mesh. Cage tops were uncovered and had a clearance of 10 cm above the water. Cages were left unmanipulated for two days post-installation, allowing the sediment to resettle and to ensure that cages remained fixed in the sediment. Fresh hippo dung, voided within 24 h, was collected weekly from hippo paths adjacent to Lake Bhangazi South under the supervision of a park ranger (Fig. 1). Dung samples from 3 to 5 individual middens were pooled and homogenised and a sub-sample (300 ml) was added to dung inclusion cages, once per week for a period of six weeks. Inspection of cages prior to weekly dung additions showed that previously added dung did not accumulate – possibly indicating rapid disintegration by microorganism activity and wind mixing (Dawson et al., 2016). The amount of dung added to inclusion cages was determined from prior sampling of sites within the Narrows where hippos were abundant. This involved quantifying mean volumes of dung recorded in benthic grab samples (n ¼ 2 per site, area ¼ 0.026 m2, depth ¼ 20 cm) collected at nine sites along a 2–3 km section and then scaling up to the area of each experimental cage. For this component, grab samples were collected no further than 150 m from three resident hippo pods ranging in size from 15 to 30 individuals per pod. Within 8 h of collection, replicate grabs (n ¼ 3) from each site were combined in buckets, sieved (2 mm) and the volume of remaining dung measured. Exclusion cages were left unma nipulated, with no dung added. Site location, replication level and fre quency of dung addition were determined by a number of factors including accessibility to sites, safe exit routes in cases of danger from wildlife (the site is frequented by Zambezi sharks, Nile crocodiles and small groups of hippos) and the availability of park rangers to supervise dung collection (Dawson et al., 2016). At the termination of the experiment, sediment cores for assessing responses of benthic meiofaunal assemblages (n ¼ 3 per cage, diameter 2
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Fig. 1. Map showing (a) the geographical location within South Africa of the St Lucia System, (b) positions of Charter’s Creek (in situ experimental site) and Lake Bhangazi South (site where dung was collected) and (c) dung accumulation due to excretion by resident hippos. NB: (b) shows system boundaries and not water levels at the time of the study.
¼ 2 cm, depth ¼ 1 cm) were collected following established methods used in South African estuaries, including the St Lucia Estuary (Bownes and Perissinotto, 2012; Nozais et al., 2005; Pillay and Perissinotto, 2009). Samples were collected from central portions of cages to avoid edge effects, sieved in the laboratory through a 400 μm mesh to remove macrofauna and then again over a 40 μm mesh, followed by preservation in an ethanol-Rose Bengal solution. Meiofaunal organisms were identi fied to the lowest possible taxonomic level and enumerated. The size of discriminating meiofaunal taxa, identified by SIMPER to cumulatively account for 90% of the community dissimilarity between treatments at each site, was determined using photographs input into ImageJ (htt
ps://imagej.nih.gov). Meiofauna were photographed using a Leica DM 500 compound microscope, fitted with a Leica ICC50 camera. Size was determined in the following way for dominant taxa: total length (head to tail) was measured for Nemata, the width of the 5th setigerous segment was measured for Polydora sp. and total width for foraminiferans, while for Assiminea cf. capensis, distance from the tip of the spire to the base of the aperture was used. With the exception of Polydora sp., size mea surements were made on whole organisms. All multivariate analyses were carried out using PRIMER v6.1 (un standardized and transformed Log (x þ 1) data). Spatial variability in meiofaunal community structure (based on abundance data) was 3
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visually assessed using non-metric multidimensional scaling ordinations (nMDS), with PERMANOVA (permutational analysis of variance) providing quantitative support for groupings, based on Bray-Curtis similarity matrices. For PERMANOVA analyses, dung treatments (dung exclusion/inclusion) were nested within site (the highest spatial factor within the nested hierarchical design). SIMPER (similarity percentages) was used to identify the discriminating taxa that cumulatively contrib uted 90% to community dissimilarity between dung treatments within sites. Meiofaunal community descriptors (total abundance, richness, evenness and diversity) were calculated using the DIVERSE function. Nested ANOVA (analysis of variance) was employed to determine the influence of site and dung enrichment on meiofaunal community de scriptors (dung treatment nested within site). The effects of site and dung treatment on the abundance and size of individual taxa (identified by SIMPER) were also determined using Nested AVOVA. Tests for normality (Q-Q plots) and homogeneity of variances (Bartlett Tests) were conducted prior to parametric testing. Where necessary, data were transformed (Log (x þ 1), square root or 4th root) before parametric testing. The statistical programming language, R was used to conduct all univariate statistical tests (R Core Team, 2016). 3. Results Meiofaunal community structure was statistically indistinguishable between sites (PERMANOVA pseudo F1,59 ¼ 0.726; p ¼ 0.684) and dung treatments (PERMANOVA pseudo F2,59 ¼ 1.717; p ¼ 0.136). This was visually supported by nMDS ordinations, showing overlap of samples between different sites and dung treatments (Fig. 2; See Supplementary Table 1 for list of taxa collected between the two experimental sites). Meiofaunal abundance visually decreased following hippo dung enrichment, with abundance decreasing by 26.8% at Site 1 and 37.5% at Site 2. However, neither dung treatment nor site significantly affected meiofaunal abundance (Table 1, Fig. 3, Nested ANOVA, Site: F1,52 ¼ 1.235, p ¼ 0.271, Dung Treatment: F2,52 ¼ 1.832, p ¼ 0.170). Meio faunal richness was not significantly affected by site (Table 1, Fig. 3; Nested ANOVA, F1,52 ¼ 0.012, p ¼ 0.913), but was affected by dung treatment (Nested ANOVA, F2,52 ¼ 5.083, p ¼ 0.010). At Site 1, richness increased with the addition of dung, whereas the reverse was evident at Site 2. Meiofaunal evenness was statistically distinguishable between sites, with values being lower at Site 1 than at Site 2 (Table 1, Fig. 3, Nested ANOVA, F1,52 ¼ 8.384, p ¼ 0.006). Evenness was not signifi cantly different between dung treatments (Table 1, Fig. 3, Nested ANOVA, F2,52 ¼ 2.202, p ¼ 0.121). Conversely, meiofaunal diversity did not differ between experiment sites (Table 1, Fig. 3, Nested ANOVA, F1,52 ¼ 1.628, p ¼ 0.208) but was significantly affected by dung treat ment (Table 1, Fig. 3, Nested ANOVA, F2,52 ¼ 6.238, p ¼ 0.004). At Site 1, diversity increased with dung enrichment but decreased with dung addition at Site 2. This pattern mirrored that observed for meiofaunal richness. At an individual taxon level, SIMPER analyses identified four meio faunal taxa that accounted for 90% of the dissimilarity between dung treatments at Sites 1 and 2 (Table 2). Meiofaunal taxa exhibited spatially idiosyncratic responses to dung, with increasing and decreasing trends occurring within taxa depending on the site at which the experiment was conducted. At Site 1, the abundance of one taxon decreased and 3 taxa increased to varying degrees, whereas the abundance of all four domi nant taxa at Site 2 were depressed following dung enrichment. Of the four taxa identified by SIMPER to account for 90% of the dissimilarity between dung treatments, only one taxon (Assiminea cf. capensis) was significantly affected by both site and dung treatment (Table 3, Fig. 4; Nested ANOVA, Site: F1,52 ¼ 10.467, p ¼ 0.002; Dung Treatment: F2,52 ¼ 3.478, p ¼ 0.038). At Site 1, dung enrichment resulted in increases in abundance of A. cf. capensis, whereas at Site 2, abundance decreased in dung treatment plots compared to un-enriched plots. The abundance of one taxon, Foraminifera, differed marginally non-significantly between sites (Table 3, Fig. 4; Nested ANOVA, Site: F1,52 ¼ 3.554 p ¼ 0.065). Both
Fig. 2. Non-metric multidimensional scaling ordination (nMDS) showing spatial variation in meiofaunal community structure (abundance data) between sites and dung treatments. A. shows samples from dung inclusion (filled sym bols) and exclusion (unfilled symbols) treatments at Sites 1 (black) & 2 (grey symbols). B. shows dung inclusion and exclusion treatments at Site 1, while C. shows dung inclusion and exclusion treatments at Sites 2.
Nemata and Polydora sp. displayed marginally non-significant dung treatment responses (Nested ANOVA p ¼ 0.072 and p ¼ 0.067 respec tively). However, responses were erratic, as abundance of Nemata decreased at Site 2 with dung addition, but at Site 1, abundance of Polydora sp. increased (Fig. 4). In terms of sizes of dominant taxa, only Nemata displayed significant responses to site and dung treatment (Table 3, Fig. 5; Nested ANOVA, Site: F1,46 ¼ 5.361, p ¼ 0.025; Dung Treatment: F2,46 ¼ 16.316, p < 0.001). At Site 1, Nemata were larger in dung enrichment plots, but were 4
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4. Discussion
Table 1 Results of Nested ANOVA testing for differences in meiofaunal community de scriptors between sites and dung treatments. Bold p-values indicate statistically significant differences. F ¼ F-statistic, p ¼ significance level, DF ¼ degrees of freedom.
Our study was motivated by a need to understand responses of meiofaunal assemblages to hippo dung inputs in the St Lucia Estuary, given that meiofauna are key components of benthic ecosystems by virtue of critical functions they provide (Pillay et al., 2013; Schratz berger and Ingels, 2017). Our study additionally sought to understand the role played by dung as a potential stressor in a system afflicted by long-term stress through drought, mouth closure and water abstraction. The broader goal of the study was to understand ramifications of dung inputs for benthic assemblages and ecosystems more broadly, which is a significant knowledge gap currently. Our findings indicate that meio faunal responses were not always detectable, and when evident, were complex and idiosyncratic, mainly due to differences in the direction of responses spatially. Based on levels of dung used and environmental contexts under which the experiment was conducted, our data show (1) neutral responses at the community level and for total abundance and evenness, and (2) site-specific idiosyncratic (positive and negative) re sponses of meiofaunal richness, diversity and individual taxa. Sizes of meiofaunal taxa also responded idiosyncratically to dung, with both
Nested ANOVA Site Meiofaunal Meiofaunal Richness Meiofaunal Meiofaunal
Treatment
F
DF
p
F
DF
p
Abundance Species
1.235 0.012
(1,52) (1,52)
0.271 0.913
1.832 5.083
(2,52) (2,52)
0.170 0.010
Evenness Diversity
8.384 1.628
(1,52) (1,52)
0.006 0.208
2.202 6.238
(2,52) (2,52)
0.121 0.004
smaller in enriched plots at Site 2. Foraminifera, A. cf. capensis and Polydora sp. all showed non-significant responses to both site and treatment (Table 3, Fig. 5; Nested ANOVA p > 0.05 for all).
Fig. 3. Spatial variation in mean (�1 SE) meiofaunal community metrics at the two experimental sites in response to dung addition (D - black) and exclusion (N grey). Numbers in treatment name ¼ site number. Results of Nested ANOVA are superimposed on graphs. 5
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enrichment, given that the St Lucia Estuary had been undergoing a se vere drought over a 10-year period, which resulted in decadal mouth closure, hyper-salinity (200) and desiccation of 90% of the lakes at the peak of the drought (Cyrus et al., 2011; Humphries et al., 2016; Peri ssinotto et al., 2013a, b; Whitfield and Taylor, 2009). It could also be argued that low sample sizes and high data variability may have been responsible for the lack of dung effects detected. However, data vari ability was not always large in our experiment (Figs. 3–5), even in cases where non-significant treatment effects were detected (e.g. Fig. 5). Nevertheless, the study may have benefited from increased sample sizes in order for marginal outcomes to be clarified. Responses of meiofaunal richness and diversity to enrichment by dung were particularly interesting, with increases in these metrics recorded at Site 1, but with reductions occurring at Site 2. This would suggest that abiotic contexts in which dung inputs occur determine the direction of these community metric responses to dung. While we lack quantitative data on abiotic conditions at experimental sites, observa tions during experimental set-up and weekly monitoring indicate greater wind-driven wave action at Site 1 than at Site 2 (Dawson et al., 2016). This would imply that stagnating conditions, as observed at Site 2, may negatively impact community metrics leading to declines, while flowing conditions may induce stimulatory effects. This suggestion is consistent with contemporary ideas regarding biotic responses to hippo dung, with studies hypothesising that non-linear effects of dung may be associated with flow and dung residence times, with low flow and high dung residence leading to deteriorating water quality and hypoxia (Dawson et al., 2016; Dutton et al., 2018; Gereta and Wolanski, 1998; Stears et al., 2018; Subalusky et al., 2018). This idea can also account for responses of individual taxa that we observed, given that at Site 1 all but one dominant taxon increased in abundance following enrichment, while at Site 2 decreasing trends were observed for all dominant taxa. Similarly, sizes of Nemata were greater in dung inclusion plots at Site 1 but this trend was reversed at Site 2. In these cases, stagnation and deteriorating water quality can explain declining trends at Site 2, whereas increasing trends may be related to positive effects induced by dung, probably in the form of increased trophic resource either directly or indirectly (e.g. POM, bacteria). Our previous published work from this experiment showed that microalgal biomass declined at Sites 1 and 2 by roughly 50 and 70% following enrichment with hippo dung, likely due to dung shading the benthos and reducing primary productivity (Dawson et al., 2016). The declining trends that we recorded in meiofaunal metrics (richness and diversity) and abundance of individual taxa and their sizes at Site 2 can thus be explained by dung-induced declines in microalgal biomass (resource limitation). However, this mechanism does not entirely explain the trends recorded in our experiment, given that at Site 1 a decrease in microalgal biomass by 50% with the addition of dung resulted in increasing trends in the above-mentioned meiofaunal vari ables. This finding is suggestive of meiobenthic assemblages in our experiment not being affected completely by bottom-up effects associ ated with resource limitation, as suggested by Coull (1999). This idea is supported by previous work showing weak grazing pressure exerted by meiofauna on microalgae due to limited reliance on microphytobenthos as a trophic resource, because of the availability of alternative trophic resources such as bacteria and other meiofauna (Nozais et al., 2005). Although dung inputs evidently reduce microalgal abundance (Dawson et al., 2016), inputs may also potentially increase benthic bacterial biomass; firstly, through the addition of hippo gut bacteria, and sec ondly, by providing a substrate for aquatic bacterial decomposers to colonise (Jones, 1992). In addition, meiofauna are known to stimulate bacterial abundance as grazing of these microbiota keeps the population in the active growth phase, and their production of nitrogen rich mucus stimulates and traps additional microbes (Riemann and Helmke, 2002; Schratzberger and Ingels, 2017). This mechanism could explain the mismatch between microalgal biomass and meiofaunal metrics and abundance of individual taxa, particularly at Site 1.
Table 2 Meiofaunal taxa identified by SIMPER to cumulatively account for 90% of the community dissimilarity between dung exclusion and inclusion treatments at Site 1 and 2, based on abundance data. Bold text highlights taxa showing an increase in abundance with the addition of hippo dung. Letters in parentheses next to taxon names denote broad taxonomic grouping: (F) ¼ Foraminifera, (N) ¼ Nemata, (G) ¼ Gastropoda, (P) ¼ Polychaeta. Site 1 Dung
Site 2 No Dung
Dung
No Dung
Dominant Taxa (Abundance data)
Average abundance
Dominant Taxa (Abundance data)
Average abundance
Foraminifera (F)
24.53
44.80
8.13
13.33
Nemata (N) Assiminea cf. capensis (G) Polydora sp. (P)
8.00 5.93
7.53 3.47
Assiminea cf. capensis (G) Nemata (N) Foraminifera (F)
8.20 6.87
14.00 11.07
2.53
1.20
Polydora sp. (P)
1.20
1.33
Table 3 Results of Nested ANOVA testing for differences in individual meiofaunal taxa abundance and size between sites and dung treatments. Bold p-values indicate statistically significant differences. Letters in parentheses next to taxon names denote broad taxonomic grouping: (F) ¼ Foraminifera, (N) ¼ Nemata, (G) ¼ Gastropoda, (P) ¼ Polychaeta. Nested ANOVA Individual taxa abundance Site
Treatment
Taxa
F
DF
p
F
DF
p
Foraminifera (F) Nemata (N) Assiminea cf. capensis (G) Polydora sp. (P)
3.554 2.246 10.467
(1,52) (1,52) (1,52)
0.065 0.140 0.002
1.364 2.754 3.478
(2,52) (2,52) (2,52)
0.265 0.072 0.038
2.282
(1,52)
0.137
2.846
(2,52)
0.067
Individual taxa size Site
Treatment
Taxa
F
DF
p
F
DF
p
Foraminifera (F) Nemata (N) Assiminea cf. capensis (G) Polydora sp. (P)
0.473 5.361 1.186
(1,44) (1,46) (1,45)
0.495 0.025 0.282
1.171 16.316 0.554
(2,44) (2,46) (2,45)
0.192 < 0.001 0.578
0.816
(1,11)
0.386
0.300
(2,11)
0.746
positive and negative effects recorded within taxa spatially. The lack of significant dung effects at the community level for meiofauna, either visually or statistically, suggests that dung had limited impacts on species composition and distribution. However, detectable effects on community metrics and individual taxa and their sizes indi cate that effects of dung did occur, but subtly. Here, it could be argued that the lack of statistically significant effects at the community level could be due to low taxonomic resolution used in our study. However, the fact that significant dung effects were noted for meiofaunal richness suggests that resolution may not have been an issue and that there was ample variability for dung effects to be detected. Subtle communitylevel effects of dung may relate to the fact that under stressful condi tions, communities may comprise a subset of assemblages that are highly tolerant to changing conditions (MacKay et al., 2010). This idea has been proposed for benthic macrofauna in the St Lucia Estuary, to account for the lack of significant compositional shifts in assemblages in space and time under drought conditions, despite changes in abundance of core species (MacKay et al., 2010; Pillay et al., 2013). This mechanism can explain the lack of community-level responses of meiofauna to dung 6
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Fig. 4. Spatial variation in mean abundance (�1 SE) of dominant meiofauna taxa at the two experimental sites in response to dung addition (D – black) and exclusion (N – grey). Numbers in treatment name ¼ site number. Results of Nested ANOVA are superimposed on graphs.
The fact that the meiofauna data used in this paper originate from the exact experiment used in previously reported findings for macrofauna (Dawson et al., 2016), allows direct comparisons to be made between these benthic faunistic groups so that an understanding of their sensi tivities to dung could be assessed. Community-level differences were obvious for macrofauna in response to dung addition at both experi mental sites (Dawson et al., 2016), but this did not manifest for meio fauna (Fig. 2). Macrofaunal abundance, richness and biomass declined following dung addition, but metrics for meiofauna showed contrasting responses, with both positive and negative effects emerging depending on spatial location (Fig. 3). Lastly, the majority of macrofaunal taxa displayed declining trends following dung addition, whereas meiofaunal taxa displayed both positive and negative responses. Overall, our com bined findings suggest that benthic macrofauna are more sensitive to dung inputs, with meiofauna appearing to be more robust and resilient. This conclusion aligns with previous research demonstrating a greater tolerance of meiofauna to ecological stressors than macrofauna (e.g. Josefson and Widbom, 1988; Warwick et al., 1990; Somerfield et al., 2006).
The differential responses of macro- and meiofauna to hippo dung recorded in this experiment are likely a product of the unique morphological and life-history traits exhibited by these groups (Loreau et al., 2001). Macrofaunal life-cycles typically incorporate planktonic larval stages, implying that hippo dung can influence colonisation and recruitment by (1) forming a physical barrier that restricts larval set tlement, and/or (2) generating negative settlement cues as a result of altered water and sediment biogeochemistry through decomposition (Dawson et al., 2016). In contrast, the majority of meiofaunal taxa do not have larval stages, but instead undergo direct development within sediments (Dahms and Qian, 2004). Therefore, dung may not function as a barrier to meiofaunal recruitment at the sediment surface. Meiofauna may additionally be positively affected by the abrasive effects of hippo dung, as their lack of a mobile larval phase makes them partially dependant on recolonization through resuspension of sediment into the water column (Josefson and Widbom, 1988). Given that low oxygen states are known to select against large-bodied benthic organisms (Pearson and Rosenberg, 1978), the greater size of macrofauna is also a trait that negatively predisposes them to low oxygen levels associated 7
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Fig. 5. Spatial variation in mean size (�1 SE) of dominant individual meiofauna taxa at the two experimental sites in response to dung addition (D - black) and dung exclusion (N - grey). Numbers in treatment name ¼ site number. Results of Nested ANOVA are superimposed on graphs.
with decomposition of dung. Lastly, resilience and opportunistic re sponses of meiofauna to dung inputs may be linked to their rapid turnover rates (Schratzberger and Ingels, 2017). Overall, our combined work quantifying responses of macrofaunal and meiofaunal assemblages has shed light on potential responses of benthic ecosystems to dung loading by hippos. Given the largely declining trends observed for macrofauna, but neutral and spatially idiosyncratic patterns recorded for meiofauna, we suggest that high dung inputs may induce size shifts in benthic assemblages, from larger, macrofauna groups to smaller meiofaunal assemblages. If this is the case, then it is possible that functions provided by larger organismal groups, such as bioturbation, sediment oxygenation and nutrient fluxes (Pillay et al., 2013) would be at risk from high dung inputs, but those provided by meiofauna (nutrient cycling, organic matter decomposi tion) may be more robust, thus potentially offering some resilience to high dung loading. We suggest that future studies could focus on un derstanding (1) the susceptibilities of different benthic organismal groups to dung loading, (2) the functional consequences arising from potential community shifts and (3) traits and/or life history strategies that positively or negatively predispose organism groupings to dung
loading. Further research in these areas would be useful in developing a mechanistic and predictive understanding of dung-loading on benthic ecosystems more broadly. This would be particularly important in conservation areas that are threatened by freshwater deprivation and in which hippo population sizes are large and increasing. However, it would also be important to find innovative solutions to minimise safety risks posed by hippos (and other wildlife) to humans, for appropriate experimental controls and adequate sample sizes to be obtained. We also advocate for appropriate abiotic data to be collected from similar studies to develop a mechanistic understanding of pathways by which dung effects are propagated across the entire food web. Lastly, assessing changes in depth distributions of benthic organisms will allow for an expansion in understanding of how hippo dung inputs affect benthic ecosystems. Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. 8
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CRediT authorship contribution statement
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Jessica Dawson: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Writing - original draft, Writing - review & editing. Deena Pillay: Conceptualization, Funding acquisition, Project administration, Resources, Supervision, Writing - original draft, Writing - review & editing. Renzo Perissinotto: Conceptualization, Funding acquisition, Writing - review & editing. Acknowledgements We are thankful to iSimangaliso Wetlands Park Authority, Ezemvelo KZN Wildlife, Geoffrey Clinning and students from Hluhluwe-Imfolozi Park (HiP) Research facility for general assistance. Funding was gran ted by the National Research Foundation (NRF), German Academic Exchange Service (DAAD), Carnegie and Andrew Mellon Foundations and The University of Cape Town (UCT). Appendix A. Supplementary data Supplementary data to this article can be found online at https://doi. org/10.1016/j.ecss.2020.106745. References Cadenasso, M.L., Pickett, S.T.A., Weathers, K.C., Jones, C.G., 2003. A framework for a theory of ecological boundaries. Bioscience 53, 750–758. https://doi.org/10.1641/ 0006-3568(2003)053[0750:AFFATO]2.0.CO;2. Strayer, D.L., Power, M.E., Fagan, W.F., Pickett, S.T.A., Belnap, J., 2003. A classification of ecological boundaries. Bioscience 53 (723). https://doi.org/10.1641/0006-3568 (2003)053[0723:ACOEB]2.0.CO;2. Abrantes, K., Sheaves, M., 2008. Incorporation of terrestrial wetland material into aquatic food webs in a tropical estuarine wetland. Estuar. Coast Shelf Sci. 80, 401–412. https://doi.org/10.1016/j.ecss.2008.09.009. Begg, G., 1978. The Estuaries of Natal. Natal Town and Regional Planning Report 41. Pietermaritzburg, South Africa. Bownes, S.J., Perissinotto, R., 2012. Community structure and composition of meiofauna over a sea-induced mouth-breaching event in St Lucia Estuary, South Africa. Mar. Ecol. Prog. Ser. 463, 105–126. https://doi.org/10.3354/meps09870. Coull, B.C., 1999. Role of meiofauna in estuarine soft-bottom habitats. Aust. J. Ecol. 24, 327–343. https://doi.org/10.1046/j.1442-9993.1999.00979.x. Cyrus, D., Jerling, H., MacKay, F., Vivier, L., 2011. Lake St Lucia, Africa’s largest estuarine lake in crisis: combined effects of mouth closure, low levels and hypersalinity. South Afr. J. Sci. 107, 1–13. https://doi.org/10.4102/sajs.v107i5/ 6.291. Dahms, H.-U., Qian, P.-Y., 2004. Life histories of the Harpacticoida (Copepoda, Crustacea): a comparison with meiofauna and macrofauna. J. Nat. Hist. 38, 1725–1734. https://doi.org/10.1080/0022293031000156321. Dawson, J., Pillay, D., Roberts, P.J., Perissinotto, R., 2016. Declines in benthic macroinvertebrate community metrics and microphytobenthic biomass in an estuarine lake following enrichment by hippo dung. Sci. Rep. 6, 37359. https://doi. org/10.1038/srep37359. Dutton, C.L., Subalusky, A.L., Hamilton, S.K., Rosi, E.J., Post, D.M., 2018. Organic matter loading by hippopotami causes subsidy overload resulting in downstream hypoxia and fish kills. Nat. Commun. 9, 1–10. https://doi.org/10.1038/s41467-018-043916. Eltringham, S.K., 1999. The Hippos: Natural History and Conservation. Acedemic Press. Gereta, E., Wolanski, E., 1998. Wildlife-water quality interactions in the serengeti national park, Tanzania. Afr. J. Ecol. 36, 1–14. https://doi.org/10.1046/j.13652028.1998.102-89102.x. Grey, J., Harper, D., 2002. Using stable isotope analyses to identify allochthonous inputs to Lake Naivasha mediated via the hippopotamus gut. Isot. Environ. Health Stud. 38, 245–250. https://doi.org/10.1080/10256010208033269. Holt, R.D., 2008. Theoretical perspectives on resource pulses. Ecology 89, 671–681. https://doi.org/10.1890/07-0348.1. Howe, E.R., Simenstad, C.A., 2015. Using stable isotopes to discern mechanisms of connectivity in estuarine detritus-based food webs. Mar. Ecol. Prog. Ser. 518, 13–29. https://doi.org/10.3354/meps11066. Humphries, M.S., Green, A.N., Finch, J.M., 2016. Evidence of El Ni~ no driven desiccation cycles in a shallow estuarine lake: the evolution and fate of Africa’s largest estuarine system, Lake St Lucia. Global Planet. Change 147, 97–105. https://doi.org/10.1016/ j.gloplacha.2016.11.002. Huxel, G.R., Polis, G.A., Holt, R.D., 2004. At the frontier of the integration of food web ecology and landscape ecology. In: Polis, G.A., Power, M.E., Huxel, G.R. (Eds.), Food Webs at the Landscape Level. University of Chicago Press, pp. 434–451. Jones, R.I., 1992. The influence of humic substances on lacustrine planktonic food chains. Hydrobiologia 229, 73–91.
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