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Seasonal release of propagules in mangroves – Assessment of current data
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Research Paper
Seasonal release of propagules in mangroves – Assessment of current data Tom Van der Stocken a,∗ , Jorge López-Portillo b , Nico Koedam a a b
Ecology and Biodiversity, Vrije Universiteit Brussel, Pleinlaan 2, B-1050 Brussels, Belgium Red de Ecología Funcional, Instituto de Ecología, A.C., Apartado Postal 63, Xalapa, 91700 Veracruz, Mexico
a r t i c l e
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Article history: Received 17 November 2015 Received in revised form 19 January 2017 Accepted 5 February 2017 Available online xxx Keywords: Climate change Dispersal Phenology Propagule abscission Rainfall Temperature
a b s t r a c t Phenology is often neglected in dispersal research, in spite of its potential effects on the patterns of propagule deposition. Based on peer-reviewed literature, we collated data on propagule release timing for mangroves and aimed at understanding the relation between mangrove propagule release timing and monthly average rainfall and temperature. There were data on 47 species of 25 genera, accounting for 67% of mangrove species, but most (35%) of the available data are related to Avicennia marina, Avicennia germinans and Rhizophora mangle. We found significant correlations (r > 0.8, P < 0.001) between mangrove propagule release and rainfall, with 72% of data reporting propagule release during the wet season, except in the southernmost latitudes. In the equatorial zone (10◦ N–10◦ S), propagules fall from parent trees throughout most of the year with no pronounced production peaks. At latitudes higher than the equatorial zone, propagule release was also significantly correlated with temperature (r > 0.6, P < 0.05). Our results show phenological complementarity between the northern and southern hemisphere, with a peak in propagule release corresponding to the boreal and austral summer, respectively. We encourage mangrove researchers to report data on propagule release and availability to render an increasingly accurate and precise interpretation of geographic patterns as the current dataset increases, both in terms of geographic and species coverage. © 2017 Elsevier B.V. All rights reserved.
1. Introduction Over the last years, the phenology of plant species has received increasing attention in ecology (Kramer et al., 2000; Cleland et al., 2007; Körner and Basler, 2010). Most studies have focused on species in temperate zones, where plant phenologies have been correlated with photoperiod and temperature (Huang et al., 2001; Menzel et al., 2005; Vitasse and Basler, 2013), although plant phenologies are very likely controlled by complex interactions among biotic and abiotic factors (Wolkovich et al., 2014). In tropical areas, on the other hand, where photoperiod and temperature show less seasonal variability, phenology was reported to be mainly controlled by precipitation and soil water availability (Singh and Kushwaha, 2005; Couralet et al., 2013). Since anthropogenic activities will increasingly influence these factors, insight into the environmental cues that underlie plant phenology is important for predicting the survival and growth of individuals, the reproductive success of populations and species interactions under shifting climatic conditions (Cleland et al., 2007). Furthermore, phenological
∗ Corresponding author. E-mail address: [email protected] (T. Van der Stocken).
data, particularly on the timing of propagule release, are important in dispersal studies, since in combination with temporal variations in the characteristics of the main dispersal vectors, it determines dispersal and deposition patterns (Greene, 2005; Savage et al., 2010; Savage et al., 2012), and hence the potential of individuals to colonize suitable habitats. In mangrove ecosystems, which have been strongly reduced and fragmented over the last decades due to excessive exploitation and development (Alongi, 2002; Duke et al., 2007; Giri et al., 2011; Mukherjee et al., 2014; Hamilton and Casey, 2016), dispersal is an important determinant of community structure and biogeographic range shifts under changing environmental conditions. Additionally, it can help spread beneficial alleles among populations, fuelling local adaptation (Levine and Murrell, 2003). Hence, there is a strong need for empirical data and models to reconstruct and predict the frequency and the likely trajectories of natural dispersal events (cf. Ngeve et al., 2016) to assess the vulnerability of populations to anthropogenic pressure, extinction, and the likelihood of successful range expansion. However, while the dispersal behaviour of individual mangrove propagules (i.e. dispersal units) and the interaction of the dispersal vectors at play have been studied recently (Van der Stocken et al., 2013; Van der Stocken et al., 2015b), relatively little is known about the temporal dynamics of propagule
http://dx.doi.org/10.1016/j.aquabot.2017.02.001 0304-3770/© 2017 Elsevier B.V. All rights reserved.
Please cite this article in press as: Van der Stocken, T., et al., Seasonal release of propagules in mangroves – Assessment of current data. Aquat. Bot. (2017), http://dx.doi.org/10.1016/j.aquabot.2017.02.001
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Fig. 1. Number of publications from 1980 through 2013 extracted from the Web of ScienceTM database with ‘phenology’ (light grey), ‘mangrove’ (dark grey), and ‘mangrove phenology’ (black bars) in the title, keywords or abstract. There is a rapid increase in the number of publications (left y-axis) on phenology and mangroves; but the number of publications on mangrove phenology; though increasing (right y-axis) is still limited.
release and its environmental drivers, hampering the biological realism of model predictions. Such knowledge is important given the temporal variation of dispersal vector properties (magnitude and direction) that may condition the sites of propagule arrival. Mangrove phenology has received increasing attention (Fig. 1) since these ecosystems represent an important component of primary production in many tropical, subtropical and warm temperate coastal regions (Bouillon et al., 2008). Their role in providing valuable nutrients that support coastal and marine systems has been frequently reported (e.g. Odum and Heald, 1975; Aburto-Oropeza et al., 2008). However, phenological data are mostly restricted to a species and cover time periods that are too short to detect long-term phenological patterns and responses to changes in environmental factors such as rainfall and temperature. Additionally, the drivers mentioned earlier for tropical plant seed phenology (such as soil water availability) are not expected to be merely transposable to mangroves in their waterlogged marine environment. Mangroves present an important research subject for phenology in view of the wide latitudinal range of many species. Therefore, long-term records of mangrove phenology are needed, as well as a quantitative knowledge of their interaction with potential environmental drivers. Here, we assembled most available data on mangrove propagule release timing to assess current knowledge, intending to encourage data gathering on this phenological variable by mangrove researchers worldwide. We recognize that the present dataset on propagule release timing is incomplete, both in terms of species and spatial coverage. However, we do compile data to investigate the presence of latitudinal trends and can explore basic correlations with climatological variables such as monthly average rainfall and temperature. Although correlation does not imply causation, we explore the most straightforward explanations that should be further scrutinized as more data become available. 2. Materials and methods 2.1. Data sources Peer-reviewed journal articles on mangrove phenology were searched for using the Web of ScienceTM database. As a keyword, ‘phenology’ was used and on the outcome of this search, ‘mangrove’
was used as an additional search operator. The remaining articles were screened for information on the timing of propagule release. Additionally, to ensure that our study includes most of the relevant publications that mention the timing of propagule release, we intensively screened the reference lists of the manuscripts found and searched for missing literature. We continued this procedure until no new data on propagule release was found. We highlight that the list of mangrove plants is a best professional combination of several sources defining which species can be qualified as a ‘mangrove’, including the original list published by Tomlinson (1986), the World Register of Marine Species (WoRMS) at www. marinespecies.org (Appeltans et al., 2012), as well as selected species published in between (Duke, 2006; Giesen et al., 2007). We recorded information on the timing of propagule release, the study area, its latitude and longitude, and the season (dry or wet) in which the propagules were released. The information on propagule release was drawn from the text, figures or tables. Data on propagules per se (e.g. dry weight) are not considered in this study because the way in which data were presented often did not allow for such detailed information. We used a binary scale (0–1), marking the months when most propagules were reported (1) and the other months (0). We used the reporting of mature propagules as a proxy for release, when release was not mentioned explicitly. If geographical coordinates were not reported, the study site was located using Google Earth, based on the source publication. Although a special effort was done to retrieve data for West Africa, we found none in peer-reviewed literature. For correlation with timing of propagule release, data on three environmental variables – monthly average rainfall (MAR), monthly average low temperature (MALT) and monthly average high temperature (MAHT) – were extracted from the World Weather Online database (http://www.worldweatheronline.com). Data on the global distribution of mangroves were taken from the Mangrove Reference Database and Herbarium (Massó i Alemán et al., 2010). To investigate whether global latitudinal patterns in the timing of propagule release exist, monthly binarized data (i.e. presence-absence of propagules) were summed per latitudinal range group (20–37◦ S, 10–20◦ S, 10◦ S–10◦ N, 10–20◦ N, 20–28◦ N) and normalized by dividing by the total number of reported propagule release data per latitudinal range group. The 37◦ S latitude is 1.45◦ from the absolute mangrove southern latitudinal range limit (38.45◦ S, East-Australia); the northern latitudinal limit of mangrove forests is at 32.28◦ N (Bermuda) (Spalding et al., 2010). 2.2. Data analysis We calculated the percentage of data per latitudinal range group, the relative abundance of the various mangrove species studies, and the percentage of reported data per country. This allowed us to track knowledge gaps at the level of species and study site. We computed coefficients and corresponding P-values of Pearson correlations between climatological variables and propagule release data (normalized and expressed as a percentage of reports per latitudinal range group), using MATLAB R2014a (MathWorks, Inc.Natick, Mass, USA). We tested for correlation among climatological variables using STATISTICA 8 (Statsoft, Inc., Tulsa, OK, USA). Multiple regression analysis was not considered after we found there was significant multicollinearity among environmental variables. To illustrate and discuss the importance of phenological data in the study of propagule dispersal and deposition patterns, release locations were plotted for the Indian Ocean area relative to ocean surface current circulation in the Southwest and Northeast monsoon season. Ocean surface circulation patterns were taken from Shankar et al. (2002) and for the Mozambique Channel from Ternon
Please cite this article in press as: Van der Stocken, T., et al., Seasonal release of propagules in mangroves – Assessment of current data. Aquat. Bot. (2017), http://dx.doi.org/10.1016/j.aquabot.2017.02.001
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Fig. 2. Geographic locations (green circles) from which phenological data is included in this study. Global mangrove distribution (Massó i Alemán et al., 2010) is shown in blue. Most data come from study sites in Australia and Central America. Map. Source: ESRI, WorldPlateCarree.mdx (ArcGIS 10).
et al. (2014). The respective maps were created using ArcGIS 10 (Esri, Redlands, CA, USA).
3. Results Our literature search yielded 61 peer-reviewed manuscripts published in the period 1971–2013 containing relevant data on propagule release timing, covering more than 170 data lines (Table S1 in the Supplementary Material). Altogether, 47 species of 25 genera were covered by these references, i.e. 67% of known mangrove species (Polidoro et al., 2010). Geographical locations of mangrove propagule fall studies are shown in Fig. 2. Most data correspond to Avicennia marina (14.1%), Avicennia germinans (10.6%), Rhizophora mangle (10.6%), Laguncularia racemosa (6.5%), and Rhizophora mucronata (5.3%). Considering genera, most data are from Avicennia (27.6%), followed by Rhizophora (25.9%), Bruguiera (9.4%), Laguncularia (6.5%), Sonneratia (6.5%) and Ceriops (5.9%). These genera cover 43% of 70 mangrove species and are most widespread, comprising the predominant elements in mangrove communities as well. Most data come from mangrove sites in Australia (31.2%), Mexico (18.8%) and Brazil (7.1%), i.e. three countries that together with Indonesia and Nigeria account for 48% of the global mangrove area (FAO, 2007). To our knowledge no peer reviewed or published data are available for West-Africa (Fig. 2). Overall, for the northern latitudes (>10◦ N, 32.9% of all data) propagule fall peaks during the boreal summer and is reduced during the boreal winter (Fig. 3A). For southern latitudes (>10◦ S, 39.4% of all data), the pattern is complementary, with abundant propagule fall in the austral summer (i.e. boreal winter) and lower amounts during the austral winter (i.e. boreal summer). Close to the equator (10◦ N–10◦ S, 27.6% of all data), propagule release is reported for the whole year. In the southern hemisphere, the peak in propagule fall shifts with decreasing latitude, with propagules released about a month later in the extreme southern latitudes (20–37◦ S, 11.2% of all data) compared to lower latitudes (10–20◦ S, 28.2% of all data). Though less clear, this one-month shift is present in the northern latitudes as well. For all data, 72% of the propagules were released during the wet season, 16% in the dry season and 12% showed no clear seasonality. Latitudinal propagule release patterns seem to correlate with MAR data (Fig. 3A and B, Table 1), with highly significant positive correlations in the northern latitudes and between 10◦ S and 20◦ S. In the
southernmost latitudes (20◦ S–37◦ S) this correlation was not significant. Positive correlations were found as well between propagule release and MALT and MAHT (Fig. 3C and D, Table 1). In the equatorial latitudinal range (10◦ N–10◦ S) the correlation with temperature was not significant. Pearson coefficients are slightly higher for the correlation with MALT compared to MAHT (). Significant correlations were found between MALT and MAHT (r = 0.72, P < 0.001), MALT and MAR (r = 0.64, P < 0.001), and MAHT and MAR (r = 0.45, P < 0.001). These latitudinal patterns and correlations with rainfall and temperature also apply within and between (and possibly among) genera (Fig. 4, Tables 2 and 3). There were significant correlations between propagule release and rainfall for both Avicennia (Table 2) and Rhizophora (Table 3), except in the southernmost latitudes where only the correlation with temperature was significant. In the equatorial zone (10◦ N–10◦ S) correlations between propagule release and these climatic variables were not significant (Tables 2 and 3). The biogeographical distribution of mangroves relative to the ocean surface currents in the Indian Ocean and the geographical locations of the reported propagule release during the winter (northeast monsoon, November-February) and summer (southwest monsoon, May-September) is depicted in Fig. 5. Clear differences in ocean surface current circulation patterns can be seen between these seasons, some currents showing a complete reversal of direction, such as for example the Somali Current (Fig. 5). Pronounced changes in current direction can be seen in the waters surrounding India. Also, notice the complex configuration and dynamics of ocean surface currents in the Mozambique Channel (see Ternon et al., 2014).
4. Discussion The data here encompass several species and an ample range in longitudinal and latitudinal variation. Not all species have been studied along their biogeographical range, which would be optimal to study the timing of propagule release. However, the published data do show clear latitudinal patterns and correlations with climatological variables. Effects of observation or reporting errors are probably limited because of the coverage of data. New data must further increase validity of patterns.
Please cite this article in press as: Van der Stocken, T., et al., Seasonal release of propagules in mangroves – Assessment of current data. Aquat. Bot. (2017), http://dx.doi.org/10.1016/j.aquabot.2017.02.001
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Fig. 3. Latitudinal pattern in (A) propagule release timing (percentage of reports), (B) monthly average rainfall, (C) monthly average high temperature, and (D) monthly average low temperature. Climatological data from World Weather Online (http://www.worldweatheronline.com) for each reported study site and averaged per latitudinal range group.
Table 1 Pearson correlation coefficients and P-values between mangrove species propagule release (% of reports) and monthly averages of rainfall (MAR), high temperature (MAHT) and low temperature (MALT), for each latitudinal range group. Latitudinal range group
n
28◦ N–20◦ N 20◦ N–10◦ N 10◦ N–10◦ S 10◦ S–20◦ S 20◦ S–37◦ S
25 31 47 48 19
Monthly average rainfall (mm)
Monthly average high T (◦ C)
Monthly average low T (◦ C)
r
P
r
P
r
P
0.73 0.83 −0.62 0.94 −0.41
** *** * *** n.s.
0.91 0.43 0.11 0.58 0.78
*** n.s. n.s. * **
0.92 0.72 −0.35 0.70 0.63
*** ** n.s. * *
Significance levels: *P < 0.05, **P < 0.01, ***P < 0.001, n.s. – not significant.
Table 2 Pearson correlation coefficients and P-values between Avicennia propagule release (% of reports) and monthly averages of rainfall (MAR), high temperature (MAHT) and low temperature (MALT), for each latitudinal range group. Latitudinal range group
◦
◦
28 N–20 N 20◦ N–10◦ N 10◦ N–10◦ S 10◦ S–20◦ S 20◦ S–37◦ S
n
7 10 15 4 11
Monthly average rainfall (mm)
Monthly average high T (◦ C)
Monthly average low T (◦ C)
r
P
r
P
r
P
0.84 0.64 −0.30 0.92 0.15
*** * n.s. *** n.s.
0.63 −0.06 0.49 0.62 0.58
* n.s. n.s. * *
0.73 0.40 0.03 0.79 0.66
** n.s. n.s. ** *
Significance levels: *P < 0.05, **P < 0.01, ***P < 0.001, n.s. – not significant.
4.1. Latitudinal patterns and correlations with rainfall and temperature Our data revealed clear latitudinal patterns in the timing of propagule fall, in spite of the complexity due to latitudinal range
asymmetry on continental east versus west coasts (Quisthoudt et al., 2012). Higher latitudinal range limits are found on continental east coasts and the global pattern we discerned is a complex combination of various range types. While propagules seem to be released throughout the year in the equatorial zone, there is
Please cite this article in press as: Van der Stocken, T., et al., Seasonal release of propagules in mangroves – Assessment of current data. Aquat. Bot. (2017), http://dx.doi.org/10.1016/j.aquabot.2017.02.001
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Table 3 Pearson correlation coefficients and P-values between Rhizophora propagule release (% of reports) and monthly averages of rainfall (MAR), high temperature (MAHT) and low temperature (MALT), for each latitudinal range group. Latitudinal range group
◦
◦
28 N–20 N 20◦ N–10◦ N 10◦ N–10◦ S 10◦ S–20◦ S 20◦ S–37◦ S
n
6 11 14 9 3
Monthly average rainfall (mm)
Monthly average high T (◦ C)
Monthly average low T (◦ C)
r
P
r
P
r
P
0.89 0.86 −0.04 0.83 0.19
*** *** n.s. *** n.s.
0.83 0.63 0.47 0.47 0.69
*** * n.s. n.s. *
0.88 0.83 0.09 0.57 0.50
*** *** n.s. n.s. n.s.
Significance levels: *P < 0.05, **P < 0.01, ***P < 0.001, n.s. – not significant.
Fig. 4. Propagule release timing (percentage of reports) for each latitudinal range group in as a function of the month of year for (A) Avicennia and (B) Rhizophora. Symbols for each latitudinal group are shown in Fig. 4A.
a clear alignment between propagule fall and boreal and austral summers as northern and southern latitudes increase, respectively. This is in accordance with the hypothesis that light (day length) and temperature are important seasonal cues for plant growth and development. In mangroves, day length and air temperature have been proposed as cues for the start of phenological events such as leafing and flowering (Leach and Burgin, 1985; Saifullah et al., 1989; Duke, 1990; Navarrete and Oliva-Rivera, 2002), but it is yet unclear to what extent these variables dictate the timing of lifehistory events and phenology altogether. Also, different species may have different responses to changes in the same environmental variable, and spatio-temporal variations in resource availability may result in different timing in phenology (Wilczek et al., 2010). This may explain why, in contrast to the findings of Sharma et al. (2012), Bernini and Rezende (2010) found no significant correla-
Fig. 5. Surface currents in the Indian Ocean during (A) the northeast (NovemberFebruary) and (B) the southwest (May-September) monsoon (modified from Shankar et al. 2002, circulation in the Mozambique Channel after Ternon et al., 2014), locations where propagule release has been reported during these respective seasons (colored circles), and the distribution of mangroves (blue areas, after Massó i Alemán et al., 2010). Seasonally variable currents (black arrows) are distinguished from stable circulation (grey arrows). SC, Somali Current, EC, Equatorial Current, SMC, Summer Monsoon Current, WMC, Winter Monsoon Current, EICC, East India Coastal Current, WICC, West India Coastal Current, SECC, South Equatorial Counter Current, EACC, East African Coastal Current, SEC, South Equatorial Current, LH, Lakshadweep high, LL, Lakshadweep low, and GW, Great Whirl. Map. Source: ESRI, WorldPlateCarree.mdx (ArcGIS 10).
tion between seasonal litter fall and rainfall, mean air temperature or wind speed. At the genus level, patterns of monthly propagule release are largely comparable for Avicennia and Rhizophora (Fig. 4), except for the southernmost latitudinal data (20◦ S–37◦ S). The latter may be because the least data were available for this latitudinal range.
Please cite this article in press as: Van der Stocken, T., et al., Seasonal release of propagules in mangroves – Assessment of current data. Aquat. Bot. (2017), http://dx.doi.org/10.1016/j.aquabot.2017.02.001
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Our database shows that for 72% of reported data, propagules are released during the wet season, regardless of the hemisphere. Arreola-Lizárraga et al. (2004) found that 86% of the seasonal variability in litterfall was explained by rainfall, sea level and the rainfall/evaporation ratio. It is unclear, however, in which way these environmental factors influence the timing of propagule release. Pronounced increases in propagule fall have been reported during strong winds and typhoons (Kamruzzaman et al., 2013a,2013b), but since strong rains and high wind speeds often occur together, it is difficult to distinguish the potential effect of each of these environmental variables and underlying mechanisms. On the other hand, as mangroves thrive in the intertidal zone along tropical, subtropical, and warm temperate coasts, rainfall can strongly regulate phenology via changes in substrate salinity. For example, litterfall, productivity and structure of mangrove forests have been linked with ground water salinity (López-Portillo and Ezcurra, 1989; Agraz Hernández et al., 2011). Latitudinal propagule release patterns also suggest a positive correlation with MALT and MAHT, which supports earlier findings on interdependence with monthly mean air temperature (Lu and Lin, 1990). Interestingly, the correlation with MALT and MAHT becomes more pronounced and significant towards higher northern and southern latitudes, compared to latitudes closer to the equator. This aligns with increasing seasonality with increasing latitude. Hence, while propagule release patterns are increasingly linked with MALT and MAHT towards mangrove latitudinal range limits, they seem to be more related to rainfall between 20◦ N and 20◦ S. Our data suggest that propagule release is more connected to temperature than rainfall in the southernmost latitudes of the mangrove range. While large-scale studies found no clear latitudinal patterns in propagule release and correlations with climatic factors (Duke, 1990), our results demonstrate strong interconnectedness with latitude, rainfall and temperature. It has been suggested that propagules are released during periods when environmental factors are optimal for the growth and development of seedlings (Duke et al., 1984), which may be species- and site-specific. While factors such as rainfall, temperature, wind and soil salinity have received some attention separately, it is most likely that phenological patterns are regulated by two or more factors. For example, by using principal component analysis López-Portillo and Ezcurra (1985) found that water level, evaporation, temperature and insolation were highly intercorrelated, and synthesized them in a principal component axis accounting for 82% of environmental variability. This axis was directly correlated with leaf fall and inversely correlated with propagule fall. However, there was no correlation between litterfall and local rainfall, suggesting that continental runoff (i.e. rainfall accumulation along the geographical basin) is more important than local rainfall.
buoyancy, morphology, and longevity, has been provided by various authors (Tomlinson, 1986; Clarke and Myerscough, 1991; Clarke et al., 2001; Drexler, 2001; Allen and Krauss, 2006; Tonné et al., 2016), and studies on dispersal vectors and establishment processes have also been carried out (Balke et al., 2011; Balke et al., 2013; Van der Stocken et al., 2013; Van der Stocken et al., 2015b). Nevertheless, the timing of propagule release determines when the propagules undergo the vector conditions and can embark on LDD. In mangroves, the interaction between the timing of propagule release and the changes in the direction and strength of key dispersal vectors define their traveling course, rendering knowledge on these aspects important to predict propagule deposition and connectivity patterns. Wind strength and direction vary on short time scales, and, depending on the propagule morphology and floating orientation, determine the fate of a propagule (Van der Stocken et al., 2013; Van der Stocken et al., 2015b). Flood and ebb currents alternate daily with monthly changes in tidal amplitude. At high tide, propagules will migrate away from the source while at low tide they may accumulate in the locality, thus increasing the possibility of local establishment (Van der Stocken et al., 2015a). Finally, seasonal variation in ocean currents (Ffield et al., 1997; Sengupta et al., 2005), such as the alignment with seasonal monsoons (Shankar et al., 2002; Heron et al., 2006) may also condition dispersal direction and distance, and hence sites of propagule arrival. Our findings suggest that the effect on phenological shifts of altered rainfall patterns under climate change (Thornton et al., 2014) may have more effect on forest structure than previously thought. This is especially important when considering the shifts in the seasonal magnitude, timing and duration of tropical rainfall under global climate change models (Feng et al., 2013) and projected changes in climatic events such as monsoons due to perturbations in the radiative budget (Collins et al., 2013). Changes in rainfall and temperature patterns may shift the timing of mangrove propagule release, while changes in monsoonal variation may control ocean surface circulation. The shifts in timing of phenological events and in the strength and direction of dispersal vectors could affect propagule dispersal and deposition patterns with consequences for long-term population dynamics and biogeographical signals. Hence, we stress the need for more data to test the causal nature of these environmental variables in the phenological processes of the many mangrove forest species and localities. We conclude that: (1) There are clear latitudinal patterns in the timing of mangrove propagule release; (2) Existing phenological data for mangroves indicate existing positive correlations with climate data on rainfall and temperature; (3) The timing of propagule release may interact differently with water and ocean currents that seasonally change;
4.2. Climate change and implications for dispersal Further the above observations entail that: Over the last decades, long distance dispersal (LDD) has received major attention as a mechanism for the survival of plant populations under changing climatic and environmental conditions (Higgins and Richardson, 1999; Johst et al., 2002; Corlett and Westcott, 2013). In mangroves, understanding the mechanisms of dispersal and predicting dispersal patterns is important given the increasing fragmentation and encroachment by non-mangrove landcover (Fahrig, 2003; Duke et al., 2007) which threaten the biodiversity that mangroves sustain. Obtaining data on dispersal patterns and connectivity is an important challenge in LDD research (Nathan, 2001) that could be partly tackled by combining genetic and modelling studies to obtain reliable estimations of actual patterns and to predict the potential effects of future scenarios. Species-specific characteristics such as propagule size, density,
(4) Phenological shifts under changing climatic conditions, and their relation to temporal changes in dispersal vector properties may influence propagule dispersal and deposition patterns in the future, with consequences for long-term population dynamics and biogeographical ranges. (5) Phenological datasets may enable the construction of mixed models to include the drivers that may best account for the observed patterns and for increasingly reliable predictions in response to climate change (Wolkovich et al., 2014). Long-term information could be gathered through global monitoring programs in which local communities in collaboration with mangrove scientists regularly collect data to share it in a global
Please cite this article in press as: Van der Stocken, T., et al., Seasonal release of propagules in mangroves – Assessment of current data. Aquat. Bot. (2017), http://dx.doi.org/10.1016/j.aquabot.2017.02.001
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database, similar to Project BudBurst (budburst.org), even when taking place in a number of well selected representative areas (Datta et al., 2012). Additionally, a global dataset of long-term phenological events would aid in assessing species abilities to shift with climate change (Cleland et al., 2012). Author contributions TVdS originally formulated the idea along with NK. TVdS collected and analyzed the data along with JLP. TVdS wrote the manuscript with paragraphs from JLP and NK. All authors reviewed the manuscript and have approved the final article. Acknowledgments This research was funded by the Flemish Interuniversity Council (VLIR-UOS), the Vrije Universiteit Brussel (VUB), and the Université Libre de Bruxelles (ULB). For this research, Tom Van der Stocken has been supported with a VLIR PhD Scholarship (VLADOC). Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.aquabot.2017.02. 001. References Aburto-Oropeza, O., Ezcurra, E., Danemann, G., Valdez, V., Murray, J., Sala, E., 2008. Mangroves in the Gulf of California increase fishery yields. PNAS 105, 10456–10459. Agraz Hernández, C.M., Zaragoza, C.G., Iriarte-Vivar, S., Flores-Verdugo, F.J., Casasola, P.M., 2011. Forest structure, productivity and species phenology of mangroves in the La Mancha lagoon in the Atlantic coast of Mexico. Wetlands Ecol. Manage. 19, 273–293. Allen, J.A., Krauss, K.W., 2006. Influence of propagule flotation longevity and light availability on establishment of introduced mangrove species in Hawaii. Pacific Sci. 60, 367–376. Alongi, D.M., 2002. Present state and future of the world’s mangrove forests. Environ. Conserv. 29, 331–349. Appeltans, W., Ahyong, S.T., Anderson, G., Angel, M.V., Artois, T., Bailly, N., Bamber, R., Barber, A., Bartsch, I., Berta, A., Blazewick-Paszkowycz, M., NBock, P., Boxhall, G., Boyko, C.B., Nunes Brandão, S., Bray, R.A., Bruce, N.L., Cairns, S.D., Chan, T.-Y., Cheng, L., Collins, A.G., Cribb, T., Curini-Galletti, M., Dahdouh-Guebas, F., Davie, P.J.F., Dawson, M.N., De Clerck, O., Decock, W., De Grave, S., De Voogd, N.J., Domning, D.P., Emig, C.C., Erséus, C., Eschmeyer, W., Fauchald, K., Fautin, D.G., Feist, S.W., Fransen, C.H.J.M., Furuya, H., Garcia-Alvarez, O., Gerken, S., Gibson, D., Gittenberger, A., Gofas, S., Gómez-Daglio, L., Gordon, D.P., Guiry, M.D., Hernandez, F., Hoeksema, B.W., Hopcroft, R., Jaume, D., Kirk, P., Koedam, N., Koenemann, S., Kolb, J.B., Kristensen, R.M., Kroh, A., Lambert, G., Lazarus, D.B., Lemaitre, R., Longshaw, M., Lowry, J., Macpherson, E., Madin, L.P., Mah, C., Mapstone, G., McLaughlin, P., Mees, J., Meland, K., Messing, C.G., Mills, C.E., Molodtsova, T.N., Mooi, R., Neuhaus, B., NG, P.K.L., Nielsen, C., Norenburg, J., Opresko, D.M., Owsawa, M., Paulay, G., Perrin, W., Pilger, J.F., Poore, G.C.B., Pugh, P., Read, G.B., Reimer, J.D., Rius, M., Rocha, R.M., Saiz-Salinas, J.I., Scarabino, V., Schierwater, B., Schmidt-Rhaesa, A., Schnabel, K.E., Schotte, M., Schubert, P., Schwabe, E., Segers, H., Self-Sullivan, C., Shenkar, N., Siegel, V., Sterrer, W., Stöhr, S., Swalla, B., Tasker, M.L., Theusen, E.V., Timm, T., Todaro, A., Turon, X., Tylor, S., Uetz, P., Van der Land, J., Vanhoorne, B., Van Ofwegen, L.P., Van Soest, R.W.M., Vanaverbeke, J., Walker-Smith, G., Walter, T.C., Warren, A., Williams, G., Wilson, S.P., Costello, M.J., 2012. The magnitude of global marine species diversity. Curr. Biol. 22, 2189–2202. Arreola-Lizárraga, J.A., Flores-Verdugo, F.J., Ortega-Rubio, A., 2004. Structure and litterfall of an arid mangrove stand on the Gulf of California, Mexico. Aquat. Bot. 79, 137–143. Balke, T., Bouma, T.J., Horstman, E.M., Webb, E.L., Erftemeijer, P.L.A., Herman, P.M.J., 2011. Windows of opportunity: thresholds to mangrove seedling establishment on tidal flats. Mar. Ecol. Prog. Ser. 440, 1–9. Balke, T., Webb, E.L., van den Elzen, E., Galli, D., Herman, P.M.J., Bouma, T.J., Frid, C., 2013. Seedling establishment in a dynamic sedimentary environment: a conceptual framework using mangroves. J. Appl. Ecol. 50 (3), 740–747. Bernini, E., Rezende, C.E., 2010. Litterfall in a mangrove in Southeast Brazil. Pan-Am. J. Aquat. Sci. 5, 508–519. ˜ Bouillon, S., Borges, A.V., Castaneda-Moya, E., Diele, K., Dittmar, T., Duke, N.C., Kirstensen, E., Lee, S.Y., Marchand, C., Middelburg, J., Rivera-Monroy, V.H., Smith III, T.J., Twilley, R.R., 2008. Mangrove production and carbon sinks: a
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Research Paper
Seasonal release of propagules in mangroves – Assessment of current data Tom Van der Stocken a,∗ , Jorge López-Portillo b , Nico Koedam a a b
Ecology and Biodiversity, Vrije Universiteit Brussel, Pleinlaan 2, B-1050 Brussels, Belgium Red de Ecología Funcional, Instituto de Ecología, A.C., Apartado Postal 63, Xalapa, 91700 Veracruz, Mexico
a r t i c l e
i n f o
Article history: Received 17 November 2015 Received in revised form 19 January 2017 Accepted 5 February 2017 Available online xxx Keywords: Climate change Dispersal Phenology Propagule abscission Rainfall Temperature
a b s t r a c t Phenology is often neglected in dispersal research, in spite of its potential effects on the patterns of propagule deposition. Based on peer-reviewed literature, we collated data on propagule release timing for mangroves and aimed at understanding the relation between mangrove propagule release timing and monthly average rainfall and temperature. There were data on 47 species of 25 genera, accounting for 67% of mangrove species, but most (35%) of the available data are related to Avicennia marina, Avicennia germinans and Rhizophora mangle. We found significant correlations (r > 0.8, P < 0.001) between mangrove propagule release and rainfall, with 72% of data reporting propagule release during the wet season, except in the southernmost latitudes. In the equatorial zone (10◦ N–10◦ S), propagules fall from parent trees throughout most of the year with no pronounced production peaks. At latitudes higher than the equatorial zone, propagule release was also significantly correlated with temperature (r > 0.6, P < 0.05). Our results show phenological complementarity between the northern and southern hemisphere, with a peak in propagule release corresponding to the boreal and austral summer, respectively. We encourage mangrove researchers to report data on propagule release and availability to render an increasingly accurate and precise interpretation of geographic patterns as the current dataset increases, both in terms of geographic and species coverage. © 2017 Elsevier B.V. All rights reserved.
1. Introduction Over the last years, the phenology of plant species has received increasing attention in ecology (Kramer et al., 2000; Cleland et al., 2007; Körner and Basler, 2010). Most studies have focused on species in temperate zones, where plant phenologies have been correlated with photoperiod and temperature (Huang et al., 2001; Menzel et al., 2005; Vitasse and Basler, 2013), although plant phenologies are very likely controlled by complex interactions among biotic and abiotic factors (Wolkovich et al., 2014). In tropical areas, on the other hand, where photoperiod and temperature show less seasonal variability, phenology was reported to be mainly controlled by precipitation and soil water availability (Singh and Kushwaha, 2005; Couralet et al., 2013). Since anthropogenic activities will increasingly influence these factors, insight into the environmental cues that underlie plant phenology is important for predicting the survival and growth of individuals, the reproductive success of populations and species interactions under shifting climatic conditions (Cleland et al., 2007). Furthermore, phenological
∗ Corresponding author. E-mail address: [email protected] (T. Van der Stocken).
data, particularly on the timing of propagule release, are important in dispersal studies, since in combination with temporal variations in the characteristics of the main dispersal vectors, it determines dispersal and deposition patterns (Greene, 2005; Savage et al., 2010; Savage et al., 2012), and hence the potential of individuals to colonize suitable habitats. In mangrove ecosystems, which have been strongly reduced and fragmented over the last decades due to excessive exploitation and development (Alongi, 2002; Duke et al., 2007; Giri et al., 2011; Mukherjee et al., 2014; Hamilton and Casey, 2016), dispersal is an important determinant of community structure and biogeographic range shifts under changing environmental conditions. Additionally, it can help spread beneficial alleles among populations, fuelling local adaptation (Levine and Murrell, 2003). Hence, there is a strong need for empirical data and models to reconstruct and predict the frequency and the likely trajectories of natural dispersal events (cf. Ngeve et al., 2016) to assess the vulnerability of populations to anthropogenic pressure, extinction, and the likelihood of successful range expansion. However, while the dispersal behaviour of individual mangrove propagules (i.e. dispersal units) and the interaction of the dispersal vectors at play have been studied recently (Van der Stocken et al., 2013; Van der Stocken et al., 2015b), relatively little is known about the temporal dynamics of propagule
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Fig. 1. Number of publications from 1980 through 2013 extracted from the Web of ScienceTM database with ‘phenology’ (light grey), ‘mangrove’ (dark grey), and ‘mangrove phenology’ (black bars) in the title, keywords or abstract. There is a rapid increase in the number of publications (left y-axis) on phenology and mangroves; but the number of publications on mangrove phenology; though increasing (right y-axis) is still limited.
release and its environmental drivers, hampering the biological realism of model predictions. Such knowledge is important given the temporal variation of dispersal vector properties (magnitude and direction) that may condition the sites of propagule arrival. Mangrove phenology has received increasing attention (Fig. 1) since these ecosystems represent an important component of primary production in many tropical, subtropical and warm temperate coastal regions (Bouillon et al., 2008). Their role in providing valuable nutrients that support coastal and marine systems has been frequently reported (e.g. Odum and Heald, 1975; Aburto-Oropeza et al., 2008). However, phenological data are mostly restricted to a species and cover time periods that are too short to detect long-term phenological patterns and responses to changes in environmental factors such as rainfall and temperature. Additionally, the drivers mentioned earlier for tropical plant seed phenology (such as soil water availability) are not expected to be merely transposable to mangroves in their waterlogged marine environment. Mangroves present an important research subject for phenology in view of the wide latitudinal range of many species. Therefore, long-term records of mangrove phenology are needed, as well as a quantitative knowledge of their interaction with potential environmental drivers. Here, we assembled most available data on mangrove propagule release timing to assess current knowledge, intending to encourage data gathering on this phenological variable by mangrove researchers worldwide. We recognize that the present dataset on propagule release timing is incomplete, both in terms of species and spatial coverage. However, we do compile data to investigate the presence of latitudinal trends and can explore basic correlations with climatological variables such as monthly average rainfall and temperature. Although correlation does not imply causation, we explore the most straightforward explanations that should be further scrutinized as more data become available. 2. Materials and methods 2.1. Data sources Peer-reviewed journal articles on mangrove phenology were searched for using the Web of ScienceTM database. As a keyword, ‘phenology’ was used and on the outcome of this search, ‘mangrove’
was used as an additional search operator. The remaining articles were screened for information on the timing of propagule release. Additionally, to ensure that our study includes most of the relevant publications that mention the timing of propagule release, we intensively screened the reference lists of the manuscripts found and searched for missing literature. We continued this procedure until no new data on propagule release was found. We highlight that the list of mangrove plants is a best professional combination of several sources defining which species can be qualified as a ‘mangrove’, including the original list published by Tomlinson (1986), the World Register of Marine Species (WoRMS) at www. marinespecies.org (Appeltans et al., 2012), as well as selected species published in between (Duke, 2006; Giesen et al., 2007). We recorded information on the timing of propagule release, the study area, its latitude and longitude, and the season (dry or wet) in which the propagules were released. The information on propagule release was drawn from the text, figures or tables. Data on propagules per se (e.g. dry weight) are not considered in this study because the way in which data were presented often did not allow for such detailed information. We used a binary scale (0–1), marking the months when most propagules were reported (1) and the other months (0). We used the reporting of mature propagules as a proxy for release, when release was not mentioned explicitly. If geographical coordinates were not reported, the study site was located using Google Earth, based on the source publication. Although a special effort was done to retrieve data for West Africa, we found none in peer-reviewed literature. For correlation with timing of propagule release, data on three environmental variables – monthly average rainfall (MAR), monthly average low temperature (MALT) and monthly average high temperature (MAHT) – were extracted from the World Weather Online database (http://www.worldweatheronline.com). Data on the global distribution of mangroves were taken from the Mangrove Reference Database and Herbarium (Massó i Alemán et al., 2010). To investigate whether global latitudinal patterns in the timing of propagule release exist, monthly binarized data (i.e. presence-absence of propagules) were summed per latitudinal range group (20–37◦ S, 10–20◦ S, 10◦ S–10◦ N, 10–20◦ N, 20–28◦ N) and normalized by dividing by the total number of reported propagule release data per latitudinal range group. The 37◦ S latitude is 1.45◦ from the absolute mangrove southern latitudinal range limit (38.45◦ S, East-Australia); the northern latitudinal limit of mangrove forests is at 32.28◦ N (Bermuda) (Spalding et al., 2010). 2.2. Data analysis We calculated the percentage of data per latitudinal range group, the relative abundance of the various mangrove species studies, and the percentage of reported data per country. This allowed us to track knowledge gaps at the level of species and study site. We computed coefficients and corresponding P-values of Pearson correlations between climatological variables and propagule release data (normalized and expressed as a percentage of reports per latitudinal range group), using MATLAB R2014a (MathWorks, Inc.Natick, Mass, USA). We tested for correlation among climatological variables using STATISTICA 8 (Statsoft, Inc., Tulsa, OK, USA). Multiple regression analysis was not considered after we found there was significant multicollinearity among environmental variables. To illustrate and discuss the importance of phenological data in the study of propagule dispersal and deposition patterns, release locations were plotted for the Indian Ocean area relative to ocean surface current circulation in the Southwest and Northeast monsoon season. Ocean surface circulation patterns were taken from Shankar et al. (2002) and for the Mozambique Channel from Ternon
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Fig. 2. Geographic locations (green circles) from which phenological data is included in this study. Global mangrove distribution (Massó i Alemán et al., 2010) is shown in blue. Most data come from study sites in Australia and Central America. Map. Source: ESRI, WorldPlateCarree.mdx (ArcGIS 10).
et al. (2014). The respective maps were created using ArcGIS 10 (Esri, Redlands, CA, USA).
3. Results Our literature search yielded 61 peer-reviewed manuscripts published in the period 1971–2013 containing relevant data on propagule release timing, covering more than 170 data lines (Table S1 in the Supplementary Material). Altogether, 47 species of 25 genera were covered by these references, i.e. 67% of known mangrove species (Polidoro et al., 2010). Geographical locations of mangrove propagule fall studies are shown in Fig. 2. Most data correspond to Avicennia marina (14.1%), Avicennia germinans (10.6%), Rhizophora mangle (10.6%), Laguncularia racemosa (6.5%), and Rhizophora mucronata (5.3%). Considering genera, most data are from Avicennia (27.6%), followed by Rhizophora (25.9%), Bruguiera (9.4%), Laguncularia (6.5%), Sonneratia (6.5%) and Ceriops (5.9%). These genera cover 43% of 70 mangrove species and are most widespread, comprising the predominant elements in mangrove communities as well. Most data come from mangrove sites in Australia (31.2%), Mexico (18.8%) and Brazil (7.1%), i.e. three countries that together with Indonesia and Nigeria account for 48% of the global mangrove area (FAO, 2007). To our knowledge no peer reviewed or published data are available for West-Africa (Fig. 2). Overall, for the northern latitudes (>10◦ N, 32.9% of all data) propagule fall peaks during the boreal summer and is reduced during the boreal winter (Fig. 3A). For southern latitudes (>10◦ S, 39.4% of all data), the pattern is complementary, with abundant propagule fall in the austral summer (i.e. boreal winter) and lower amounts during the austral winter (i.e. boreal summer). Close to the equator (10◦ N–10◦ S, 27.6% of all data), propagule release is reported for the whole year. In the southern hemisphere, the peak in propagule fall shifts with decreasing latitude, with propagules released about a month later in the extreme southern latitudes (20–37◦ S, 11.2% of all data) compared to lower latitudes (10–20◦ S, 28.2% of all data). Though less clear, this one-month shift is present in the northern latitudes as well. For all data, 72% of the propagules were released during the wet season, 16% in the dry season and 12% showed no clear seasonality. Latitudinal propagule release patterns seem to correlate with MAR data (Fig. 3A and B, Table 1), with highly significant positive correlations in the northern latitudes and between 10◦ S and 20◦ S. In the
southernmost latitudes (20◦ S–37◦ S) this correlation was not significant. Positive correlations were found as well between propagule release and MALT and MAHT (Fig. 3C and D, Table 1). In the equatorial latitudinal range (10◦ N–10◦ S) the correlation with temperature was not significant. Pearson coefficients are slightly higher for the correlation with MALT compared to MAHT (). Significant correlations were found between MALT and MAHT (r = 0.72, P < 0.001), MALT and MAR (r = 0.64, P < 0.001), and MAHT and MAR (r = 0.45, P < 0.001). These latitudinal patterns and correlations with rainfall and temperature also apply within and between (and possibly among) genera (Fig. 4, Tables 2 and 3). There were significant correlations between propagule release and rainfall for both Avicennia (Table 2) and Rhizophora (Table 3), except in the southernmost latitudes where only the correlation with temperature was significant. In the equatorial zone (10◦ N–10◦ S) correlations between propagule release and these climatic variables were not significant (Tables 2 and 3). The biogeographical distribution of mangroves relative to the ocean surface currents in the Indian Ocean and the geographical locations of the reported propagule release during the winter (northeast monsoon, November-February) and summer (southwest monsoon, May-September) is depicted in Fig. 5. Clear differences in ocean surface current circulation patterns can be seen between these seasons, some currents showing a complete reversal of direction, such as for example the Somali Current (Fig. 5). Pronounced changes in current direction can be seen in the waters surrounding India. Also, notice the complex configuration and dynamics of ocean surface currents in the Mozambique Channel (see Ternon et al., 2014).
4. Discussion The data here encompass several species and an ample range in longitudinal and latitudinal variation. Not all species have been studied along their biogeographical range, which would be optimal to study the timing of propagule release. However, the published data do show clear latitudinal patterns and correlations with climatological variables. Effects of observation or reporting errors are probably limited because of the coverage of data. New data must further increase validity of patterns.
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Fig. 3. Latitudinal pattern in (A) propagule release timing (percentage of reports), (B) monthly average rainfall, (C) monthly average high temperature, and (D) monthly average low temperature. Climatological data from World Weather Online (http://www.worldweatheronline.com) for each reported study site and averaged per latitudinal range group.
Table 1 Pearson correlation coefficients and P-values between mangrove species propagule release (% of reports) and monthly averages of rainfall (MAR), high temperature (MAHT) and low temperature (MALT), for each latitudinal range group. Latitudinal range group
n
28◦ N–20◦ N 20◦ N–10◦ N 10◦ N–10◦ S 10◦ S–20◦ S 20◦ S–37◦ S
25 31 47 48 19
Monthly average rainfall (mm)
Monthly average high T (◦ C)
Monthly average low T (◦ C)
r
P
r
P
r
P
0.73 0.83 −0.62 0.94 −0.41
** *** * *** n.s.
0.91 0.43 0.11 0.58 0.78
*** n.s. n.s. * **
0.92 0.72 −0.35 0.70 0.63
*** ** n.s. * *
Significance levels: *P < 0.05, **P < 0.01, ***P < 0.001, n.s. – not significant.
Table 2 Pearson correlation coefficients and P-values between Avicennia propagule release (% of reports) and monthly averages of rainfall (MAR), high temperature (MAHT) and low temperature (MALT), for each latitudinal range group. Latitudinal range group
◦
◦
28 N–20 N 20◦ N–10◦ N 10◦ N–10◦ S 10◦ S–20◦ S 20◦ S–37◦ S
n
7 10 15 4 11
Monthly average rainfall (mm)
Monthly average high T (◦ C)
Monthly average low T (◦ C)
r
P
r
P
r
P
0.84 0.64 −0.30 0.92 0.15
*** * n.s. *** n.s.
0.63 −0.06 0.49 0.62 0.58
* n.s. n.s. * *
0.73 0.40 0.03 0.79 0.66
** n.s. n.s. ** *
Significance levels: *P < 0.05, **P < 0.01, ***P < 0.001, n.s. – not significant.
4.1. Latitudinal patterns and correlations with rainfall and temperature Our data revealed clear latitudinal patterns in the timing of propagule fall, in spite of the complexity due to latitudinal range
asymmetry on continental east versus west coasts (Quisthoudt et al., 2012). Higher latitudinal range limits are found on continental east coasts and the global pattern we discerned is a complex combination of various range types. While propagules seem to be released throughout the year in the equatorial zone, there is
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Table 3 Pearson correlation coefficients and P-values between Rhizophora propagule release (% of reports) and monthly averages of rainfall (MAR), high temperature (MAHT) and low temperature (MALT), for each latitudinal range group. Latitudinal range group
◦
◦
28 N–20 N 20◦ N–10◦ N 10◦ N–10◦ S 10◦ S–20◦ S 20◦ S–37◦ S
n
6 11 14 9 3
Monthly average rainfall (mm)
Monthly average high T (◦ C)
Monthly average low T (◦ C)
r
P
r
P
r
P
0.89 0.86 −0.04 0.83 0.19
*** *** n.s. *** n.s.
0.83 0.63 0.47 0.47 0.69
*** * n.s. n.s. *
0.88 0.83 0.09 0.57 0.50
*** *** n.s. n.s. n.s.
Significance levels: *P < 0.05, **P < 0.01, ***P < 0.001, n.s. – not significant.
Fig. 4. Propagule release timing (percentage of reports) for each latitudinal range group in as a function of the month of year for (A) Avicennia and (B) Rhizophora. Symbols for each latitudinal group are shown in Fig. 4A.
a clear alignment between propagule fall and boreal and austral summers as northern and southern latitudes increase, respectively. This is in accordance with the hypothesis that light (day length) and temperature are important seasonal cues for plant growth and development. In mangroves, day length and air temperature have been proposed as cues for the start of phenological events such as leafing and flowering (Leach and Burgin, 1985; Saifullah et al., 1989; Duke, 1990; Navarrete and Oliva-Rivera, 2002), but it is yet unclear to what extent these variables dictate the timing of lifehistory events and phenology altogether. Also, different species may have different responses to changes in the same environmental variable, and spatio-temporal variations in resource availability may result in different timing in phenology (Wilczek et al., 2010). This may explain why, in contrast to the findings of Sharma et al. (2012), Bernini and Rezende (2010) found no significant correla-
Fig. 5. Surface currents in the Indian Ocean during (A) the northeast (NovemberFebruary) and (B) the southwest (May-September) monsoon (modified from Shankar et al. 2002, circulation in the Mozambique Channel after Ternon et al., 2014), locations where propagule release has been reported during these respective seasons (colored circles), and the distribution of mangroves (blue areas, after Massó i Alemán et al., 2010). Seasonally variable currents (black arrows) are distinguished from stable circulation (grey arrows). SC, Somali Current, EC, Equatorial Current, SMC, Summer Monsoon Current, WMC, Winter Monsoon Current, EICC, East India Coastal Current, WICC, West India Coastal Current, SECC, South Equatorial Counter Current, EACC, East African Coastal Current, SEC, South Equatorial Current, LH, Lakshadweep high, LL, Lakshadweep low, and GW, Great Whirl. Map. Source: ESRI, WorldPlateCarree.mdx (ArcGIS 10).
tion between seasonal litter fall and rainfall, mean air temperature or wind speed. At the genus level, patterns of monthly propagule release are largely comparable for Avicennia and Rhizophora (Fig. 4), except for the southernmost latitudinal data (20◦ S–37◦ S). The latter may be because the least data were available for this latitudinal range.
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Our database shows that for 72% of reported data, propagules are released during the wet season, regardless of the hemisphere. Arreola-Lizárraga et al. (2004) found that 86% of the seasonal variability in litterfall was explained by rainfall, sea level and the rainfall/evaporation ratio. It is unclear, however, in which way these environmental factors influence the timing of propagule release. Pronounced increases in propagule fall have been reported during strong winds and typhoons (Kamruzzaman et al., 2013a,2013b), but since strong rains and high wind speeds often occur together, it is difficult to distinguish the potential effect of each of these environmental variables and underlying mechanisms. On the other hand, as mangroves thrive in the intertidal zone along tropical, subtropical, and warm temperate coasts, rainfall can strongly regulate phenology via changes in substrate salinity. For example, litterfall, productivity and structure of mangrove forests have been linked with ground water salinity (López-Portillo and Ezcurra, 1989; Agraz Hernández et al., 2011). Latitudinal propagule release patterns also suggest a positive correlation with MALT and MAHT, which supports earlier findings on interdependence with monthly mean air temperature (Lu and Lin, 1990). Interestingly, the correlation with MALT and MAHT becomes more pronounced and significant towards higher northern and southern latitudes, compared to latitudes closer to the equator. This aligns with increasing seasonality with increasing latitude. Hence, while propagule release patterns are increasingly linked with MALT and MAHT towards mangrove latitudinal range limits, they seem to be more related to rainfall between 20◦ N and 20◦ S. Our data suggest that propagule release is more connected to temperature than rainfall in the southernmost latitudes of the mangrove range. While large-scale studies found no clear latitudinal patterns in propagule release and correlations with climatic factors (Duke, 1990), our results demonstrate strong interconnectedness with latitude, rainfall and temperature. It has been suggested that propagules are released during periods when environmental factors are optimal for the growth and development of seedlings (Duke et al., 1984), which may be species- and site-specific. While factors such as rainfall, temperature, wind and soil salinity have received some attention separately, it is most likely that phenological patterns are regulated by two or more factors. For example, by using principal component analysis López-Portillo and Ezcurra (1985) found that water level, evaporation, temperature and insolation were highly intercorrelated, and synthesized them in a principal component axis accounting for 82% of environmental variability. This axis was directly correlated with leaf fall and inversely correlated with propagule fall. However, there was no correlation between litterfall and local rainfall, suggesting that continental runoff (i.e. rainfall accumulation along the geographical basin) is more important than local rainfall.
buoyancy, morphology, and longevity, has been provided by various authors (Tomlinson, 1986; Clarke and Myerscough, 1991; Clarke et al., 2001; Drexler, 2001; Allen and Krauss, 2006; Tonné et al., 2016), and studies on dispersal vectors and establishment processes have also been carried out (Balke et al., 2011; Balke et al., 2013; Van der Stocken et al., 2013; Van der Stocken et al., 2015b). Nevertheless, the timing of propagule release determines when the propagules undergo the vector conditions and can embark on LDD. In mangroves, the interaction between the timing of propagule release and the changes in the direction and strength of key dispersal vectors define their traveling course, rendering knowledge on these aspects important to predict propagule deposition and connectivity patterns. Wind strength and direction vary on short time scales, and, depending on the propagule morphology and floating orientation, determine the fate of a propagule (Van der Stocken et al., 2013; Van der Stocken et al., 2015b). Flood and ebb currents alternate daily with monthly changes in tidal amplitude. At high tide, propagules will migrate away from the source while at low tide they may accumulate in the locality, thus increasing the possibility of local establishment (Van der Stocken et al., 2015a). Finally, seasonal variation in ocean currents (Ffield et al., 1997; Sengupta et al., 2005), such as the alignment with seasonal monsoons (Shankar et al., 2002; Heron et al., 2006) may also condition dispersal direction and distance, and hence sites of propagule arrival. Our findings suggest that the effect on phenological shifts of altered rainfall patterns under climate change (Thornton et al., 2014) may have more effect on forest structure than previously thought. This is especially important when considering the shifts in the seasonal magnitude, timing and duration of tropical rainfall under global climate change models (Feng et al., 2013) and projected changes in climatic events such as monsoons due to perturbations in the radiative budget (Collins et al., 2013). Changes in rainfall and temperature patterns may shift the timing of mangrove propagule release, while changes in monsoonal variation may control ocean surface circulation. The shifts in timing of phenological events and in the strength and direction of dispersal vectors could affect propagule dispersal and deposition patterns with consequences for long-term population dynamics and biogeographical signals. Hence, we stress the need for more data to test the causal nature of these environmental variables in the phenological processes of the many mangrove forest species and localities. We conclude that: (1) There are clear latitudinal patterns in the timing of mangrove propagule release; (2) Existing phenological data for mangroves indicate existing positive correlations with climate data on rainfall and temperature; (3) The timing of propagule release may interact differently with water and ocean currents that seasonally change;
4.2. Climate change and implications for dispersal Further the above observations entail that: Over the last decades, long distance dispersal (LDD) has received major attention as a mechanism for the survival of plant populations under changing climatic and environmental conditions (Higgins and Richardson, 1999; Johst et al., 2002; Corlett and Westcott, 2013). In mangroves, understanding the mechanisms of dispersal and predicting dispersal patterns is important given the increasing fragmentation and encroachment by non-mangrove landcover (Fahrig, 2003; Duke et al., 2007) which threaten the biodiversity that mangroves sustain. Obtaining data on dispersal patterns and connectivity is an important challenge in LDD research (Nathan, 2001) that could be partly tackled by combining genetic and modelling studies to obtain reliable estimations of actual patterns and to predict the potential effects of future scenarios. Species-specific characteristics such as propagule size, density,
(4) Phenological shifts under changing climatic conditions, and their relation to temporal changes in dispersal vector properties may influence propagule dispersal and deposition patterns in the future, with consequences for long-term population dynamics and biogeographical ranges. (5) Phenological datasets may enable the construction of mixed models to include the drivers that may best account for the observed patterns and for increasingly reliable predictions in response to climate change (Wolkovich et al., 2014). Long-term information could be gathered through global monitoring programs in which local communities in collaboration with mangrove scientists regularly collect data to share it in a global
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database, similar to Project BudBurst (budburst.org), even when taking place in a number of well selected representative areas (Datta et al., 2012). Additionally, a global dataset of long-term phenological events would aid in assessing species abilities to shift with climate change (Cleland et al., 2012). Author contributions TVdS originally formulated the idea along with NK. TVdS collected and analyzed the data along with JLP. TVdS wrote the manuscript with paragraphs from JLP and NK. All authors reviewed the manuscript and have approved the final article. Acknowledgments This research was funded by the Flemish Interuniversity Council (VLIR-UOS), the Vrije Universiteit Brussel (VUB), and the Université Libre de Bruxelles (ULB). For this research, Tom Van der Stocken has been supported with a VLIR PhD Scholarship (VLADOC). Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.aquabot.2017.02. 001. References Aburto-Oropeza, O., Ezcurra, E., Danemann, G., Valdez, V., Murray, J., Sala, E., 2008. Mangroves in the Gulf of California increase fishery yields. PNAS 105, 10456–10459. Agraz Hernández, C.M., Zaragoza, C.G., Iriarte-Vivar, S., Flores-Verdugo, F.J., Casasola, P.M., 2011. Forest structure, productivity and species phenology of mangroves in the La Mancha lagoon in the Atlantic coast of Mexico. Wetlands Ecol. Manage. 19, 273–293. Allen, J.A., Krauss, K.W., 2006. Influence of propagule flotation longevity and light availability on establishment of introduced mangrove species in Hawaii. Pacific Sci. 60, 367–376. Alongi, D.M., 2002. Present state and future of the world’s mangrove forests. Environ. Conserv. 29, 331–349. Appeltans, W., Ahyong, S.T., Anderson, G., Angel, M.V., Artois, T., Bailly, N., Bamber, R., Barber, A., Bartsch, I., Berta, A., Blazewick-Paszkowycz, M., NBock, P., Boxhall, G., Boyko, C.B., Nunes Brandão, S., Bray, R.A., Bruce, N.L., Cairns, S.D., Chan, T.-Y., Cheng, L., Collins, A.G., Cribb, T., Curini-Galletti, M., Dahdouh-Guebas, F., Davie, P.J.F., Dawson, M.N., De Clerck, O., Decock, W., De Grave, S., De Voogd, N.J., Domning, D.P., Emig, C.C., Erséus, C., Eschmeyer, W., Fauchald, K., Fautin, D.G., Feist, S.W., Fransen, C.H.J.M., Furuya, H., Garcia-Alvarez, O., Gerken, S., Gibson, D., Gittenberger, A., Gofas, S., Gómez-Daglio, L., Gordon, D.P., Guiry, M.D., Hernandez, F., Hoeksema, B.W., Hopcroft, R., Jaume, D., Kirk, P., Koedam, N., Koenemann, S., Kolb, J.B., Kristensen, R.M., Kroh, A., Lambert, G., Lazarus, D.B., Lemaitre, R., Longshaw, M., Lowry, J., Macpherson, E., Madin, L.P., Mah, C., Mapstone, G., McLaughlin, P., Mees, J., Meland, K., Messing, C.G., Mills, C.E., Molodtsova, T.N., Mooi, R., Neuhaus, B., NG, P.K.L., Nielsen, C., Norenburg, J., Opresko, D.M., Owsawa, M., Paulay, G., Perrin, W., Pilger, J.F., Poore, G.C.B., Pugh, P., Read, G.B., Reimer, J.D., Rius, M., Rocha, R.M., Saiz-Salinas, J.I., Scarabino, V., Schierwater, B., Schmidt-Rhaesa, A., Schnabel, K.E., Schotte, M., Schubert, P., Schwabe, E., Segers, H., Self-Sullivan, C., Shenkar, N., Siegel, V., Sterrer, W., Stöhr, S., Swalla, B., Tasker, M.L., Theusen, E.V., Timm, T., Todaro, A., Turon, X., Tylor, S., Uetz, P., Van der Land, J., Vanhoorne, B., Van Ofwegen, L.P., Van Soest, R.W.M., Vanaverbeke, J., Walker-Smith, G., Walter, T.C., Warren, A., Williams, G., Wilson, S.P., Costello, M.J., 2012. The magnitude of global marine species diversity. Curr. Biol. 22, 2189–2202. Arreola-Lizárraga, J.A., Flores-Verdugo, F.J., Ortega-Rubio, A., 2004. Structure and litterfall of an arid mangrove stand on the Gulf of California, Mexico. Aquat. Bot. 79, 137–143. Balke, T., Bouma, T.J., Horstman, E.M., Webb, E.L., Erftemeijer, P.L.A., Herman, P.M.J., 2011. Windows of opportunity: thresholds to mangrove seedling establishment on tidal flats. Mar. Ecol. Prog. Ser. 440, 1–9. Balke, T., Webb, E.L., van den Elzen, E., Galli, D., Herman, P.M.J., Bouma, T.J., Frid, C., 2013. Seedling establishment in a dynamic sedimentary environment: a conceptual framework using mangroves. J. Appl. Ecol. 50 (3), 740–747. Bernini, E., Rezende, C.E., 2010. Litterfall in a mangrove in Southeast Brazil. Pan-Am. J. Aquat. Sci. 5, 508–519. ˜ Bouillon, S., Borges, A.V., Castaneda-Moya, E., Diele, K., Dittmar, T., Duke, N.C., Kirstensen, E., Lee, S.Y., Marchand, C., Middelburg, J., Rivera-Monroy, V.H., Smith III, T.J., Twilley, R.R., 2008. Mangrove production and carbon sinks: a
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Please cite this article in press as: Van der Stocken, T., et al., Seasonal release of propagules in mangroves – Assessment of current data. Aquat. Bot. (2017), http://dx.doi.org/10.1016/j.aquabot.2017.02.001