J Paleolimnol (2011) 45:213–222 DOI 10.1007/s10933-010-9493-6
ORIGINAL PAPER
Reflectance spectroscopy: a new approach for reconstructing penguin population size from Antarctic ornithogenic sediments Xiaodong Liu • Jing Sun • Liguang Sun Wenqi Liu • Yuhong Wang
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Received: 21 March 2008 / Accepted: 21 December 2010 / Published online: 14 January 2011 Ó Springer Science+Business Media B.V. 2011
Abstract Reflectance spectroscopy has several advantages compared to traditional chemical methods in paleolimnology. It requires little cost, involves minimal or no sample preparation and is rapid. There has, however, been limited use of reflectance spectroscopy in polar paleolimnological studies. This paper explores the application of reflectance spectroscopy to reconstruct historical changes in penguin population size in the maritime Antarctic. Two ornithogenic sediment cores on Ardley Island, Antarctica were analyzed. Penguin droppings and weathered soils were analyzed as reference materials. Principal component analysis and linear mixing modeling were performed on the spectral data to estimate the proportion of penguin guano in the sediments and these values were used to infer historical penguin population numbers. X. Liu (&) L. Sun Institute of Polar Environment, University of Science and Technology of China, Hefei, Anhui 230026, People’s Republic of China e-mail:
[email protected] J. Sun Lamont-Doherty Earth Observatory, Columbia University, Palisades, NY 10964, USA W. Liu Instruments’ Center for Physical Science, University of Science and Technology of China, Hefei, Anhui 230026, People’s Republic of China Y. Wang National Institutes of Health, Bethesda, MD 20892, USA
Historical penguin population size versus time, reconstructed from reflectance spectra, and population numbers inferred from previous geochemical analysis of bio-elements, were quite similar. Our results illustrate the feasibility of rapidly inferring historical changes in penguin population size using reflectance spectroscopy on Antarctic ornithogenic sediments. Our findings suggest that this technique has potential for reconstructing past population numbers of other seabirds and mammals using lake sediments influenced by animal excrement. Keywords Reflectance spectroscopy Ornithogenic sediments Historical penguin populations Antarctica
Introduction Antarctic lakes have long been considered simple ecosystems compared to lakes on other continents. Sedimentological and geochemical studies of lake sediments in the Antarctic region are therefore exceptionally helpful for reconstructing paleoclimate and paleoecology (Hodgson et al. 2004; Liu et al. 2007). Many geochemical proxies in sediments have been used to extract paleoenvironmental information (Birks and Birks 2006). In general, traditional methods of geochemical analyses are time-consuming and relatively expensive (Foley et al. 1998). Reflectance spectroscopy, however, is a non-destructive technique
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and has been considered an alternative or complementary method for compositional analysis of chemical constituents in soil, sediment, and biological samples, and for assessment of environmental quality (Nilsson et al. 1996; Malley and Williams 1997; Kooistra et al. 2001; Pasquini 2003; Font et al. 2004; Sørensen and Dalsgaard 2005; Wu et al. 2005; Richardson and Reeves 2005; Wolfe et al. 2006; Cohen et al. 2005; Xia et al. 2007; Liu et al. 2010). There is growing interest in using reflectance spectroscopy for paleoenvironmental studies because this method offers several advantages. It is rapid and cost-effective, requires little or no sample preparation, is non-destructive, and involves no consumption of reagents (Korsman et al. 1992, 1999; Foley et al. 1998; Malley et al. 1999, 2000; Rose´n et al. 2000; Das et al. 2005; Chang et al. 2001, 2005; Rose´n 2005; Michelutti et al. 2005). Studies have shown that the remnants of ancient penguin droppings in sediments of lakes near penguin colonies can be identified by their geochemical characteristics. Furthermore, these geochemical characteristics provide information about historical penguin population changes that can improve our understanding of the effects of climate change on penguin ecology (Sun et al. 2000, 2004, 2006; Sun and Xie 2001; Liu et al. 2005, 2007). Nine elements including sulfur (S), phosphorus (as P2O5), calcium (as CaO), copper (Cu), zinc (Zn), selenium (Se), strontium (Sr), barium (Ba) and fluorine (F) were found to be enriched and significantly correlated with each other in sediments amended by penguin guano. The assemblage of these nine elements is an important geochemical signal for the impact of penguin droppings or guano on lacustrine sediments in Antarctica (Sun et al. 2000, 2001). Their concentrations in ornithogenic deposits can reflect the relative input of penguin droppings into the sediments. Generally, the amount of penguin droppings input to lake sediments indicates the size of the penguin population, i.e. greater input of penguin droppings reflects larger penguin populations. Isotopic and organic geochemical proxies have also been used successfully to reconstruct long-term variations in penguin population size (Sun et al. 2005; Liu et al. 2006; Wang et al. 2007). Often, however, these different ‘‘penguin proxies’’ have not been determined on the same sediment aliquot and samples were taken from remote Antarctic areas. We often lack sufficient samples for all analyses. Therefore, we
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need a faster and more economical method to examine Antarctic penguin paleoecology. To our knowledge, reflectance spectroscopy has rarely been used for scientific research in the maritime Antarctic. For this study, we selected two representative sediment cores from Ardley Island, Antarctica that were influenced by penguin droppings and analyzed their reflectance spectroscopy. Our aim was to explore the feasibility of reconstructing Antarctic penguin population size directly from the reflectance spectra of ornithogenic sediments. Study area Ardley Island (62°130 S, 58°560 W) is 2 km long and 1.5 km wide. It is about 500 m east of the Fildes Peninsula, Maxwell Bay, and King George Island, and is connected to the Fildes Peninsula through a sandy dam (Fig. 1). The Great Wall Station of China is located about 0.5 km to the west. The study area has a cold oceanic climate, characteristic of maritime Antarctica. According to meteorological records from the Great Wall Station, the mean annual precipitation is about 630 mm, the annual average relative humidity is about 90%, and the mean annual air temperature is about -2.6°C. The area is free of snow and ice during the summer. Geologically, the island consists mainly of tertiary andesitic and basaltic lavas and tuffs, together with raised beach terraces. The topography of the island is relatively flat, with the highest elevation *70 m. About seventy to eighty percent of the island is covered by vegetation, consisting predominantly of mosses and lichens. Ardley Island is one of the most important penguin colonies in the maritime Antarctic region. In 1991, this island was declared an Antarctic Specially Protected Area by the Protocol on Environmental Protection to the Antarctic Treaty. About ten thousand penguins inhabit this island during the summer breeding period. The major species are Gentoo (Pygoscelis papua), Chinstrap (Pygoscelis antarctica) and Ade´lie (Pygoscelis adeliae) penguins (Trivelpiece et al. 1987). Large amounts of penguin droppings are transferred and deposited in the lakes or depressions by ice or snowmelt water. Ancient penguin waste products were preserved in the sediments and record historical information about penguin population change (Sun et al. 2000; Sun and Xie 2001).
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unpleasant smell. Ancient penguin bones, identified by comparison to modern penguin bones from the Fildes Peninsula on King George Island, are well preserved in the sediments. Detailed lithological descriptions of these sediment cores were provided previously (Sun et al. 2000, 2001, 2004; Liu et al. 2005). These studies showed that the sediment cores are strongly influenced by penguin droppings, and that they are composed predominantly of penguin droppings and weathered soils. Soil samples (N1) proved to be natural products of local bedrock weathering, which were not affected by penguin droppings or other biological influences (Liu et al. 2004). Chronological control for the Y2 and Y4 cores was established using conventional 14C and 210Pb–137Cs radiometric dating, and detailed dating results were reported previously (Sun et al. 2000, 2006; Liu et al. 2005). Average sedimentation rates of 0.0293 and 0.0139 cm/year were calculated for the Y2 sediments, above and below 55 cm depth, respectively. Assuming a constant linear sedimentation rate, sediment ages at each depth in the Y2 profile were calculated (Sun et al. 2000, 2006). For the Y4 sediment core, dating results showed a strong linear relation between dates and sediment depth, with an average sedimentation rate of 0.027 cm/year (Liu et al. 2005). This simple age-depth model was used to establish the chronology for the Y4 sediment profile. Fig. 1 Study area showing sampling Lakes Y2 and Y4. In the top panel, A marks the lakes and B shows the network of meltwater channels. In the bottom panel, the contour interval is 10 m
Materials and methods Sample collection Two sediment cores were collected from Lakes Y2 and Y4 on Ardley Island for spectral analyses. For comparison, five soil samples (N1) and three pure guano samples (AP) were also collected and analyzed for spectral characteristics. Sampling sites of the two sediment cores are shown in Fig. 1. The Y2 and Y4 sediment cores were collected by driving a 12-cmdiameter PVC pipe into the soft substrate of the lake floor during the austral summers of 1998/1999 and 1999/2000, respectively. Cores Y2 and Y4 are 67.5 and 34 cm long, respectively and emitted an
Spectral measurement Prior to spectral analysis, sediment subsamples were ground in a mortar, passed through a 0.074-mm sieve, and dried at 105°C for 2 h. For each sample, approximately 1 g of dried, powdered sample was packed into a measuring cell, and the spectral reflectance data were obtained using a Shimadzu SolidSpec-3700 UV–VIS–NIR Recording Spectrophotometer. Each sample was scanned over 200–2,600 nm, covering the near-ultraviolet, visible, to near-infrared regions at 1-nm intervals. Therefore, 2,401 data points were obtained for a single spectrum. Scanning of each sample took about 10 min. An external, polyethylene (zero absorbance) reference standard was read alternately with the samples. The reference spectrum was subtracted from each sample spectrum and the resulting spectrum was recorded. The resultant reflectance (r) data were transformed to absorbance (log 1/r) data.
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Results Reflectance spectra of representative samples from the Y2 and Y4 ornithogenic sediment cores are given in Fig. 2. These spectral curves are similar in general shape, but their reflectance intensity values are remarkably different. All the ornithogenic sediments have high reflectance intensity in the near-infrared reflectance (NIR) region (800–2,500 nm). Between
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Principal component analysis (PCA) was performed on the spectral data to identify the main changes in sediment composition in the Y2 and Y4 cores. PCA is a multivariate technique and is capable of reducing a large number of co-varying variables to fewer independent (orthogonal) variables, i.e. principal components (Richardson et al. 2003; Cozzolino and Moro´n 2006). It can extract the main component from the reflectance spectra, which may record paleoecological information. In the present study, we performed PCA on spectral data from ornithogenic sediments, including 37 samples from core Y2 and 18 samples from core Y4. We ran eight environmental samples including five weathered soils and three penguin droppings. In other words, PCA was conducted on 45 9 2,401 and 26 9 2,401 matrices for Y2 and Y4 samples, respectively. Linear mixing modeling was performed using only the spectral data from penguin guano and weathered soil. It was then used to extract the relative proportion of guano in the ornithogenic sediments and infer paleoecological information on penguin population size. In this study, the mean spectrum from five N1 samples was used to represent the pure soil spectrum, and the spectrum from the penguin droppings in the study area was selected as the pure guano spectrum. These end-member spectrum data (log 1/r) were used to evaluate the spectra from all ornithogenic sediments in the Y2 core. We used an interval of 0.01% and synthesized a total of 10,000 spectra curves, which covers the guano proportion in the range from 0 to 100%. For each spectrum, we chose the percentage value with the lowest standard deviation as the best estimate of the guano proportion for the sample. These computations were undertaken using MATLAB 7.1.
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1,100 and 2,500 nm of the NIR region, which is the range containing most of the interesting NIR reflectance, a major absorption peak at 1,950 nm, and some lower absorption values at 1,400–1,500, 1,700–1,800, 2,000–2,100 and 2,300–2,400 nm, can be identified. The regions around 1,450 and 1,900 nm are related to water and hydroxyl absorption, and the absorption features between 2,000 and 2,500 nm are generally associated with various organic matter components (Butkut_e and Sˇlepetien_e 2004). For example, the features at 1,726, 2,310 and 2,350 nm are related to C–H combination bands of lipids (Murray 1986; Ben-Dor et al. 1997; Moro´n and Cozzolino 2004; Cozzolino and Moro´n 2006), and the one at 2,058 nm is related to the N–H bond of proteins (Osborne et al. 1993). Several studies have identified the spectral properties of pigments in lake sediments and reconstructed historical changes in lake productivity. These
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studies indicate that chlorophylls and their derivatives from higher plants, bryophytes, phytoplankton and macroalgae in marine environments absorb near blue (*450 nm) and red (*675 nm) regions of the spectrum (Das et al. 2005; Michelutti et al. 2005, 2010; Das 2007; Wolfe et al. 2006). For our ornithogenic sediments, there are no remarkable changes in these regions (Fig. 2), suggesting that the spectral characteristics of the Y2 and Y4 lake sediments are not noticeably influenced by plant residues. The spectral changes seem to correlate with the levels of P2O5 in the samples. As P2O5 concentrations increase, the overall reflectance values tend to increase as well (Fig. 2). As confirmed in our previous papers, the element phosphorus is an important bio-element of guano, and its concentration in ornithogenic sediments is controlled mainly by seabird droppings, i.e. by seabird population numbers (Sun et al. 2000; Liu et al. 2005). For this reason, the spectral characteristics of ornithogenic sediments are likely related to the guano input. To better identify the major contributors to the reflectance spectra of these ornithogenic sediments, we need to know the main constituents of the sediments. The Antarctic region is a simple ecological system because of extremely cold climate conditions, so identifying the constituents of the sediments is relatively straightforward. We assumed that the main constituents were weathered soil and guano. We then conducted a study by adding different amounts of penguin droppings to natural, weathered soils to produce 11 ‘‘artificial’’ samples containing proportions of guano ranging from 0 to 100%. Reflectance spectra of the 11 samples are illustrated in Fig. 3. As the level of guano increases, characteristics of the spectra remain the same, but there is a progressive increase in overall reflectance intensity. In addition, as the guano proportion increased, the mixtures displayed spectra that were more like those of the Y2 and Y4 ornithogenic sediments that have higher P2O5 contents (Fig. 2). This indicates that penguin guano is the dominant factor influencing these reflectance spectra. Furthermore, this implies that the reflectance spectra of ornithogenic sediments can provide valuable information on the paleoecology of penguins. Sediment cores Y2 and Y4 were selected to test this hypothesis using PCA. We performed PCA analysis on spectrum data from 37 sediment samples in the Y2 core and eight other environmental samples. The first PCA factor (PC1)
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accounts for 90–92% of the variance in the data, and the second (PC2) accounts for 4–5%. The PC1 scores for the Y2 ornithogenic sediments from all depths, weathered soils and pure penguin droppings are shown in Fig. 4a. Because the lacustrine sediments in the Y2 core are influenced predominantly by penguin guano, PC1 is expected to be a good proxy for penguin dropping input (Sun et al. 2000; Sun and Xie 2001; Liu et al. 2005). Variations in PC1 scores are indeed closely associated with changes in guano input, and therefore, with historical penguin population numbers (Fig. 4a). Samples at 50–60 cm depth have PC1 scores that are considerably less than zero, and their mean PC1 score is close to those of weathered soil samples (N1) that are not influenced by penguin droppings. This shows that negative PC1 scores are indicative of low guano input. This is consistent with previous findings that showed the sediments from 50 to 60 cm depth had the lowest concentrations of nine bio-elements, and that the penguin population reached its lowest level during the period when these sediments were deposited (Sun et al. 2000; Sun and Xie 2001). Samples at depths above 50 cm have the highest scores, close to the values of pure guano samples, indicating high guano input. This observation is also consistent with our previous results (Sun et al. 2000; Sun and Xie 2001).
Discussion The PC1 scores and the historical penguin population from Q-mode factor analysis on the nine bio-elements
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are plotted against time for the past 3,000 years (Fig. 5a, b). They show very similar patterns. The penguin population began to decline 3,000 years before present (yr BP) and was lowest at 2,300–1,800 yr BP, which coincides with a period of reported low temperature and precipitation (Sun et al. 2000). Thereafter, the population increased, peaking between 1,800 and 1,400 yr BP. A similar response of penguin populations to climate change was reported in other studies. Huang et al. (2009) reconstructed historical changes of the penguin population on Gardner Island, Vestfold Hills over the past 8,500 years using geochemical analyses from an ornithogenic sediment core. They reported that a pronounced population peak was evident in the data from about 4,700 to 2,400 yr BP, corresponding closely to a much warmer period at the site. As shown in our study, the spectral signatures of soils and sediments change with increasing amounts of guano (Fig. 3). As a result, spectral mixing modeling can be applied to identify the contribution
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of pure guano spectra to the mixed spectra, allowing calculation of the percent guano in soils and sediments. We performed linear mixing modeling to estimate the guano proportion in the Y2 core samples, and the relative changes in guano proportion are plotted against age in Fig 5c. The changing guano proportion is consistent with variations in the PC1 score (Fig. 5a) and the penguin population change reconstructed from the amounts of bio-elements (Fig. 5b). The above procedures were repeated for the Y4 core. PCA analysis was performed on the spectral data from 18 sediment samples in core Y4 and the eight other environmental samples. The results of PCA analysis showed that PC1 accounts for 89–90% of the variance. The results of PC1 scores for all samples from core Y4, weathered soils and pure penguin droppings are shown in Fig. 4b. Similar to what was seen in the Y2 core, the PC1 score in the Y4 profile is determined by the input of penguin droppings to the sediments, and higher PC1 scores
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Fig. 5 Paleoecological significance of the reflectance spectra from the Y2 core: a PC1 scores at different ages in the Y2 core, and b change of historical penguin population size during the past 3,000 years. The y-axis indicates the variation in loadings of the principle component obtained by the Q-factor analysis on nine bio-elements (Sun et al. 2000), and the number on the y-axis is dimensionless. c Percent guano in the Y2 core inferred from the absorbance spectra data and the linear mixing model
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indicate larger proportions of penguin droppings in the Y4 ornithogenic sediments. Figure 6a shows the change of PCA score against sediment age. Relative penguin population size as reconstructed from concentrations of eight bio-elements (P, Cu, Sr, Zn, Se, Ca, F and S) and guano input proportion as deduced from the two-member linear mixing model are plotted against age in Fig. 6b, c, respectively. Overall, these profiles display similar trends through time, and indicate a decrease in penguin population size in the lake Y4 catchment over the past *1,300 years, especially during *450–200 yr BP, i.e. during the
Little Ice Age (LIA). This finding is fairly consistent with our previous results (Liu et al. 2005, 2006). Carbon and nitrogen isotopic composition in two ornithogenic sediment profiles from the Ardley Island and the Barton Peninsula of Antarctica showed that the penguin population had generally decreased over the past 2,000 years (Liu et al. 2006). During the LIA, Ardley Island was probably covered with more ice due to climatic deterioration, making it harder for penguins to nest, thus leading to a reduction in the population. Other possible causes for the decline of penguin populations include changes in marine food
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Fig. 6 Paleoecological significance of the spectral data from the Y4 core: a PC1 scores at different ages in the Y4 core, and b change of historical penguin population size during the past 1,300 years. The y-axis indicates the variation in loadings of the principle component obtained by the Q-factor analysis on eight bioelements (Liu et al. 2005), and the number on the yaxis is dimensionless. c Percent guano in the Y4 core inferred from the absorbance spectra data and the linear mixing model
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availability and/or sea-ice conditions that may have precluded penguin breeding in the study area, as lower surface air temperature could have increased sea ice extent in the Antarctic Peninsula (Liu et al. 2005). Also, there has been a clear decline in penguin populations in the study area over the past century (Fig. 6). This may have been due to interactions between increased snow deposition, and decreasing egg production and/or chick survival. According to reliable records, recent climate change on the
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Antarctic Peninsula has resulted in warming that is an order of magnitude greater than global mean warming (King 1994; Turner et al. 2002; Vaughan et al. 2003). Warmer air holds more moisture and may cause heavier snowfall, making it harder for penguins to breed. For both the Y2 and Y4 sediment cores, trends in historical penguin population size versus time estimated from principal component analysis and linear mixing modeling of the spectra, and from Q mode
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analysis of chemically analyzed concentrations of bio-elements, are very similar. This suggests that the reflectance spectra of the ornithogenic sediments contain important paleoecological information about penguin numbers. Thus, reflectance spectroscopy on sediment cores from lakes that receive inputs of excrement has the potential to be a rapid, nondestructive and cost-effective paleoecological tool for reconstructing the historical population sizes of penguins, other seabirds and mammals. Acknowledgments We thank the Chinese Antarctic and Arctic Administration of National Oceanic Bureau for logistical support. This study was supported by the National Natural Science Foundation (Grant Nos. 40876096, 41076123, 40730107 and 40606003), open research fund from SOA Key Laboratory for Polar Science (KP2007002), the young fund for strategic research of the Chinese Polar Sciences from CAAA (No. 20070202), and the special fund for excellent PhD theses of CAS. We especially appreciate three anonymous reviewers for their critical reviews and careful corrections of this manuscript.
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