Tashiro et al.
Progress in Earth and Planetary Science(2024) 11:17
https://doi.org/10.1186/s40645-024-00619-w

RESEARCH ARTICLE

Progress in Earth andPlanetary Science

Open Access

Impact of permafrost degradationon the extreme increase of dissolved ironconcentration in the Amur river during 1995–
1997
Yuto Tashiro1* , Tetsuya Hiyama1, Hironari Kanamori1 and Masayuki Kondo1,2Abstract
Primary production in the Sea of Okhotsk is largely supported by dissolved iron (dFe) transported by the Amur river,indicating the importance of dFe discharge from terrestrial environments. However, little is known about the mechanisms of dFe discharge into the Amur river, especially in terms of long-term change in dFe concentration. In the Amur
river, extreme increase in dFe concentration was observed between 1995 and 1997, the cause of which remains
unclear. As a cause of this iron anomaly, we considered the impact of permafrost degradation. To link the permafrost degradation to long-term variation in dFe concentration, we examined the changes in annual air temperature (Ta), accumulated temperature (AT), and net precipitation for three regions (northeast, south, and northwest)of the basin between 1960 and 2006. Ta and AT were relatively high in one out of every few years, and were especially high during 1988–1990 continuously. Net precipitation in late summer (July to September) has increased
since 1977 and has stayed positive until 2006 throughout the basin. Most importantly, we found significant correlations between Ta and late summer dFe concentration with a 7-year lag (r = 0.54–0.69, p < 0.01), which indicate a close
relationship between high Ta in year Y and increased late summer dFe concentration in year Y + 7. This correlation
was the strongest in northeastern Amur basin where permafrost coverage is the highest. Similar 7-year lag correlation was also found between AT in the northeastern basin and late summer dFe concentration (r = 0.51, p < 0.01).
Based on our findings, we propose the following hypothesis as a cause of iron anomaly. (1) Increased net precipitation
since 1977 has increased soil moisture, which created suitable conditions for microbial dFe generation; (2) permafrost
degradation during the warm years of 1988–1990 promoted iron bioavailability and led to the intensive dFe generation in the deeper part of the active layer; and (3) dFe took approximately 7 years to reach the rivers and extremely
increased dFe concentration during 1995–1997. This is the first study to suggest the time-lagged impact of permafrost degradation on iron biogeochemistry in the Amur river basin.
Keywords Amur river, Dissolved iron, Permafrost, Climate change, Pacific decadal oscillation*Correspondence:
Yuto Tashiro
tassy40y@gmail.com
Full list of author information is available at the end of the article© The Author(s) 2024. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which
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Tashiro et al. Progress in Earth and Planetary Science(2024) 11:17

1 Introduction
Iron is an important trace element for living organisms.
It is involved in numerous in vivo metabolic processes,
including photosynthetic electron transport, respiration,and ­N2-fixation (Sunda 2012). The bioavailability of dissolved iron (dFe) often limits biological productivity inworld oceans, especially in high-nutrient low-chlorophyll
regions (Bruland and Lohan 2003; Martin and Fitzwater
1988; Martin et al. 1989, 1990, 1994; Price et al. 1994;
Takeda and Obata 1995). Aeolian dust input was previously considered to be the critical source of iron for theocean (Martin and Fitzwater 1988). However, many studies have indicated that land-derived dFe input by rivers
is also important for primary production in coastal areas
and open sea areas (Krachler et al., 2010, 2016, 2021;
Laglera and Van Den Berg 2009; Matsunaga et al. 1998;
Moore and Braucher 2008; Nishioka et al. 2013, 2014).
Against this background, a considerable number of studies have recently been made on the sources and overlookof dFe in terrestrial environments (Ilina et al. 2013; Ingri
et al. 2018; Kritzberg and Ekström, 2012; Palviainen et al.
2015; Sarkkola et al. 2013).
The Sea of Okhotsk has abundant marine resources,
and its abundance is among the highest in the world(Sorokin and Sorokin 1999). Its high biological productivity is partly a result of the abundant dFe derived fromthe forests and wetlands in the Amur river basin (Nishioka et al. 2013, 2014; Shiraiwa 2012; Suzuki et al. 2014).
According to the previous studies, the extensive wetlandsin the lower Amur basin and the permafrost wetlandsin the middle Amur basin are important sources of dFe
for the Amur river (Nagao et al. 2007; Wang et al. 2012;
Tashiro et al. 2020, 2023). However, little is known about
the mechanisms of dFe discharge into the Amur river,
especially in terms of long-term changes in dFe concentration. The largest increase in dFe concentration in
the Amur river was recorded between 1995 and 1997;
this phenomenon was also observed in the tributaries
and is referred to as the iron anomaly by Shamov et al.
(2014). Because air temperature in the Amur river basin
has increased since the mid-1980s to the early 1990s
and remained high during 1990s (0.75℃ higher than themean of 1960–1990) (Novorotskii 2007), Shamov et al.
(2014) indicated the possibility that permafrost degradation promoted iron bioavailability in the deeper part of
the active layer, which is the soil layer that is subjected
to seasonal freeze–thaw dynamics, leading to microbialiron reduction under anaerobic conditions and subsequent increase in dFe discharge from soil to river. Thishypothesis is partially supported by recent studies, whichhave reported relatively high dFe or aqueous Fe(II) concentrations in the deep part of the active layer in summer(Herndon et al. 2015; Jessen et al. 2014). Tashiro et al.

Page 2 of 13(2020) also observed that seasonal soil thawing changes
the source of dFe to rivers from the surface to deep soil
layer in permafrost watersheds in the Amur river basin.
If permafrost degradation is the main cause of ironanomaly during 1995–1997, increased dFe concentration should have been observed after summer when deep
groundwater (suprapermafrost water) more contributes
to river water. However, Shamov et al. (2014) have overlooked the seasonal variation in dFe concentration in the
Amur river, and moreover, there has been no evidence
supporting the relationship between warming-induced
permafrost degradation and extremely increased dFe
concentration in the Amur river between 1995 and 1997.
Therefore, the mechanisms underlying the iron anomaly
still remain unclear. If permafrost degradation has a large
impact on iron biogeochemistry in the Amur river Basin,dFe concentration in the Amur river might change considerably under a warmer climate in the future and influence the marine ecosystem of the Sea of Okhotsk.
Over the past few decades, impacts of permafrost degradation on Arctic river biogeochemistry have been thesubject of intense controversy (Colombo et al. 2018;
Frey et al. 2009). Many studies have been conducted toreveal the temporal patterns of different aspects of waterchemistry, including carbon, nutrients, and metals in
the Siberian regions (Kawahigashi et al. 2004; Pokrovsky
et al. 2015, 2016; Vorobyev et al. 2017, 2019) and theNorth American Arctic regions (Aiken et al. 2014; Freyet al. 2007; Kokeji and Burn 2005; Olefeldt et al. 2014;
Petrone et al. 2006). Following these studies, it is now
widely accepted that permafrost degradation shifts waterflow paths to greater depths and changes biogeochemical
cycles in watersheds. For example, the decrease in dissolved organic carbon (DOC) flux in the Yukon river inthe past few decades has been attributed to the shiftingof water flow paths from the upper organic-rich layer tothe deeper mineral horizon where DOC can be adsorbed
on soil particles (Striegl et al. 2005). Similarly, some studies have analysed multi-decadal water chemistry monitoring data and reported long-term changes in Arctic
biogeochemistry; these include a decrease in DOC andincreases in Ca, Mg, Na, P, and S­ O4 in the Yukon river(Striegl et al. 2005; Toohey et al. 2016), increases in Ca,
Mg, ­SO4, and ­HCO3 in Central Siberian rivers (Kolosov
et al. 2016), increases in alkalinity in the Ob and Yenisei
rivers (Drake et al. 2018), increase in ­NO3 and decreasein DOC in the Kuparuk river in Alaska (McClelland et al.
2007), and increases in DOC and alkalinity in the Mackenzie river (Tank et al. 2016). These studies demonstrate
the value of long-term river water chemistry monitoring in contributing to our understanding of the multidecadal changes in Arctic biogeochemistry. However,it should be noted that monitoring data are generallyTashiro et al. Progress in Earth and Planetary Science(2024) 11:17

collected near the river mouth and include informationon the total biogeochemical changes of the entire basin.
Therefore, it is difficult to link permafrost degradationin specific regions of the basin to long-term changes inwater chemistry by examining only monitoring data. To
better understand the impact of climate change on biogeochemical cycles using long-term water chemistry
monitoring data, changes in regional (basin) scale climate variables, such as air temperature and precipitation,need to be identified, and the relationship between thesechanges and observed changes in river water chemistry
should also be analysed.
In this study, we analysed long-term monitoring dataof dFe concentration and atmospheric reanalysis datafrom the Amur River basin from 1960 to 2006 to evaluate that warming-induced permafrost degradation was
responsible for the extreme increase in dFe concentration between 1995 and 1997. We (1) examined thecorrelation between the long-term changes in dFe concentration and climate variables (specifically, air temperature and net precipitation); and (2) proposed a detailed
hypothesis about the causes and mechanisms underlying the iron anomaly. The main study focus is the influence of climate change and permafrost degradation on
the biogeochemical iron cycle in the Amur River basin.
Our discussion also includes hydroclimatology and theimportance of integrating climate data analyses into studies of the long-term changes in Arctic and sub-Arctic
river biogeochemistry.

2 Methods

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Fig. 1 Topographic map of the Amur River basin. The northeastern(NE-Amur), northwestern (NW-Amur), and southern (S-Amur) study
regions are enclosed by the red, green, and blue lines, respectively.
Long-term monitoring of dissolved iron (dFe) concentrationand discharge was conducted at Khabarovsk station (yellow dot).
Area enclosed white line shows Sanjiang Plain where large-scale
agricultural developments were conducted in twentieth century (seediscussion 3.3). Shading areas denote different types of permafrost
distribution, which was created by authors with reference to Shamov
et al. (2014)of the region is occupied by agricultural land. The NWAmur includes the uppermost part of the Amur River,and is also the driest of the three regions. The northernand eastern parts of the NW-Amur are in a sporadic
permafrost zone dominated by taiga forests, while thesouthwestern part of the NW-Amur, which forms part of
the Mongolian Plateau, is in a dry steppe zone without
permafrost.

2.1 Study site

The Amur River basin covers a large area (approximately
1.86 million k­ m2) in eastern Eurasia; it includes eastern
Mongolia and forms the border between the Russian Far
East and northeastern China. The Amur River transports
large quantities of freshwater to the Sea of Okhotsk andis responsible for more than half of the total river inflow
to the Sea of Okhotsk.
Climate variability in the Amur River basin largely varies by regions. Annual precipitation ranges from 300 mm
in eastern Mongolia to more than 700 mm in the Russian
Far East and northeastern China. The annual mean of air
temperature also ranges from around 6 °C in the southto − 7 °C in the north. Therefore, we analysed the climate
data for three regions of the Amur River basin: northwestern Amur (NW-Amur), southern Amur (S-Amur),and northeastern (NE-Amur) (Fig. 1). The NE-Amurlies mainly to the north of the Amur River and is dominated by taiga forests and lowland wetlands. Most of theNE-Amur is in isolated (< 10% coverage) and sporadic(10–50%) permafrost zones. In contrast, the S-Amur
has almost no permafrost, and a considerable fraction

2.2 Data from the monitoring of dFe in the Amur River

Concentration of dFe in the Amur River was monitored
at Khabarovsk station of the Federal Service for Hydrometeorology and Environmental Monitoring of Russia(Roshydromet) from 1960 to 2006 (Fig. 1). Water was
sampled once a month between April and October andon a few occasions between November and March. River
discharge on the sampling day was also measured at thesame station. Dissolved iron was measured by the colorimetric method with 1,10-phenantroline, which wasapplied to water filtered through Whatman GF/F filters(0.7 µm) and acidified to pH < 2 with HCl (Hydrochemical Institute 2006).
As described in the introduction, seasonal soil thawing has a great influence on water path and riverine dFe
concentration in permafrost watersheds in the Amur
River basin. To improve our understanding of the mechanisms underlying the iron anomaly, seasonal changes iniron dynamics should be considered; therefore we analysed not only the interannual variations of dFe concentrations, but also the seasonal mean dFe concentrations.

Tashiro et al. Progress in Earth and Planetary Science(2024) 11:17

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We defined April, May, and June (AMJ) as late spring andJuly, August, and September (JAS) as late summer. Rivercharacteristics are dominated by snowmelt in late spring,
especially from late April to June, and by rain in late summer, especially in July and August; active layer thickness
peaks in September (Tashiro et al. 2020).
2.3 Climate data analyses

For the three regions, we investigated the interannual
variations in annual air temperature (Ta) for 1960–2006
using the data from the Climatic Research Unit gridded
Time Series v4.05 (CRU) on a 0.5° latitude/longitude
grid (Harris et al. 2020). In addition, we investigated theinterannual variations in accumulated temperature (AT)using 2-m surface air temperature data from the Japanese 55-year Reanalysis Project (JRA-55), which is on a
1.25° latitude/longitude grid (Kobayashi et al. 2015). We
calculated annual AT, which is the cumulative sum of theregional mean daily average temperature above 0 °C ina year; AT is commonly used as an index of maximum
active layer thickness (Hinkel et al. 2001). Additionally,
we investigated the interannual variations in mean air
temperature in late summer (JAS) using the data fromJRA-55 to evaluate the contribution of air temperature inlate summer to AT. Note that we confirmed good agreement between interannual variations in Ta calculated
from CRU and those calculated from JRA-55 (Additional file 1: Fig. S1), therefore we decided to use Ta from
CRU for the following analyses because CRU reflects
the observation data from meteorological stations more
directly than JRA-55.
We also calculated the interannual variations in net
precipitation (precipitation minus evapotranspiration:
P − E) in late summer (JAS) for 1960–2006. Late summer
P − E indicates the net recharge of water in the soil layer.
It is a useful indicator of the long-term trends in soil
moisture and groundwater discharge to rivers, which canbe related to iron redox reactions in soils and subsequentdFe discharge. For calculating P − E, we used the atmospheric water budget equation (Peixoto and Oort 1983,1992):P − E = C − ∂W/∂t,(1)where P is precipitation, E is evapotranspiration, C is thevertically integrated (from the ground to the 100-hPa)moisture flux convergence, and ∂W/∂t is the temporalchange in the precipitable water. Because ∂W/∂t overlong periods of more than one month is small comparedwith P − E and C, ∂W/∂t is considered as negligible forcalculating mean P − E in late summer. We calculated the
C from specific humidity, zonal and horizontal winds of
the JRA55 dataset.

Wet or dry period in land can change over decadal scale due to the natural variability of the atmosphere (Liu et al. 2022). The atmospheric circulation
pattern in the Amur River basin is closely associatedwith the Pacific Decadal Oscillation (PDO) (Mokhov
and Semenov 2016). To understand the background of
periodic change in late summer P − E (wet or dry tendency) in the Amur River basin, which can be important for iron dynamics, we investigated the relationshipbetween late summer P − E and those in the mean latesummer PDO index. The PDO is a long-term oscillationof the Pacific Ocean on time scales of approximately
20–30 years (Mantua et al. 1997). The PDO index is anindicator of the PDO and is defined as the projectionsof monthly mean sea surface temperature (SST) anomalies onto their first empirical orthogonal functions(EOF) vectors in the North Pacific (north of 20° N).
When the PDO index is positive (negative), SSTs in thecentral part of the North Pacific are likely to be lower(higher) than normal. During our study period (1960–
2006), the PDO was in a positive phase between 1977
and 1997. We obtained monthly PDO index data fromJapan Meteorological Agency (https://​w ww.​data.​jma.​go.​j p/​g md/​k aiyou/​d ata/​s hind ​a n/b_​1 /​p do/​p do.​h tml)
and conducted two-tailed tests of significance for thePearson’s correlation coefficients between the 9-year
moving averages of late summer P − E and those of the
PDO index for 1960–2006. In general, moving average
within 10 years is applied to the interannual variationin the PDO index (e.g. Zhang et al. 2020), and we confirmed that 9-year moving average maximized the correlation between late summer P − E and the PDO index
compared to 3-, 5-, and 7-year moving averages.
To better understand the periodic changes in latesummer P − E in the Amur River basin associated with
PDO phase change, we focused on the characteristics of the atmospheric conditions during the positive
phase of the PDO between 1977 and 1997. We used
JRA55 data to calculate the anomaly of the mean geopotential height at the 500-hPa level in late summer
in 1977–1997 from 1960 to 2006 means (­Z500) and theanomaly of mean vertically integrated water vapour
flux in 1977–1997 from 1960 to 2006 means. Because
positive (negative) P − E means convergence (divergence) of water vapor, the anomaly of Z
­ 500 will exhibit
the appearance of cyclonic (anticyclonic) circulation
patterns which enhances (suppresses) the water vapor
convergence and divergence. In addition, the anomaly
of vertically integrated water vapor flux will allow us tounderstand the change in transport of water vapor flux
associated with cyclonic and anticyclonic circulation
patterns.

Tashiro et al. Progress in Earth and Planetary Science(2024) 11:17

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2.4 Statistical analyses

We conducted cross correlation analyses of the interannual variations in annual, late spring, and late summer
dFe concentration in the Amur River and climate variables (Ta and P − E) in the NE-Amur, the NW-Amur, andthe S-Amur. We used time lags of 0–9 years because soil
permeability is low and it would take several years forchanges in Ta and P − E to affect dFe discharge throughpermafrost degradation in the deeper part of the active
layer (Quinton et al. 2008, 2009; Shamov et al. 2014). We
calculated Pearson’s correlation coefficients as indicatorsof the strength of the association between the variables
and conducted two-tailed tests of significance (n = 46, 45,
44, 43, 42, 41, 40, 39, 38, 37 for time lags of 0, 1, 2, 3, 4, 5,
6, 7, 8 and 9 years, respectively).

3 Results and discussion
3.1 Changes in climate variables in the Amur River basin
between 1960 and 2006

Interannual variations in Ta in the NE-Amur, the NWAmur, and the S-Amur between 1960 and 2006 exhibited similarities (Fig. 2a). Average Ta between 1960 and2006 was − 3.1 °C in the NE-Amur, − 2.8 °C in the NWAmur, and 1.6 °C in the S-Amur. The iron anomaly
occurred between 1995 and 1997; for this period, Ta was
not particularly high in the three regions. Between 1960
and 2006, Ta was relatively high in one out of every few
years, for example in 1963, 1968, and 1975. In particular, high Ta was maintained for three years between 1988
and 1990 throughout the entire Amur River basin, with
1990 being the warmest year between 1960 and 2006 in
the NE-Amur (Ta was − 1.5 °C in 1990) and S-Amur (Tawas 2.8 °C in 1990). The interannual variations in AT in
the three regions were similar to those of Ta; AT was
relatively high in the years with high Ta in 1963, 1968,
1975, and 1988–1990 (Fig. 2b). During the continuous
warm years of 1988–1990, the highest AT in the NEAmur between 1960 and 2006 was shown in 1988 (ATin 1990 in this region was also relatively high). In addition, the interannual variations in AT were significantly
correlated with those in late summer air temperature(Additional file 1: Figs. S2 and S3), indicating that high airtemperature in late summer largely contributes to high
AT. For example, in 1988 with the highest AT between
1960 and 2006, late summer air temperature in the NEAmur was 15.5 °C, which was 1.4°C higher than the meanof 1960–2006 (Additional file 1: Fig. S2). Given that AT
can be an index of maximum active layer thickness (Hinkel et al. 2001), continuous high AT between 1988 and1990 indicates considerable acceleration of permafrost
degradation in the NE-Amur. These results are in agreement with long-term soil temperature monitoring data

Fig. 2 Interannual variations of climate variables in the Amur Riverbasin. Regional mean a annual air temperature (Ta), b accumulated
temperature (AT), and c late summer (July, August, September; JAS)
mean net precipitation (P − E) in the NE-Amur (red), the NW-Amur(green), and the S-Amur (blue). In c, P − E values above the black
dotted line indicate net water gain as a result of infiltration and values
below the line indicate net water loss as a result of evapotranspirationfrom weather stations in sporadic permafrost zones in
the NE-Amur (Shamov et al. 2014); the data showed large
increases in soil temperature between 1988 and 1990.
Interannual variations of late summer P − E in
the NE-Amur, the NW-Amur, and the S-Amur also
exhibited similar patterns (Fig. 2c). In particular, latesummer P − E in the Amur River basin had clear interdecadal variations. In the three regions, P − E decreased
after 1960; after around 1977, P − E increased andremained positive and high until around 1990, and thendecreased to 2006. Increased P − E suggests that net
water infiltration into the soil in the Amur River basin
increased after 1977 (after 1980 for the S-Amur) andthese conditions of increased soil moisture remained
until 2006 throughout the basin. In particular, P − E in
the NE-Amur and the NW-Amur has been higher thanthat in the S-Amur since 1977; this result suggests thatsoil moisture increases in the northern parts of theAmur River basin have been larger than those in thesouthern regions. It should be noted that negative latesummer P − E with large magnitudes was found in the
NE-Amur in 1998. In the NE-Amur, 1998 is known as
an anomalous drought year and is associated with historic catastrophic forest fires in the Khabarovsk Krai
(Sokolova et al. 2019).

Tashiro et al. Progress in Earth and Planetary Science(2024) 11:17

We also found that 9-year moving averages of latesummer P − E in the NE-Amur and NW-Amur were significantly correlated with those of the late summer PDO
index for 1960–2006 (NE-Amur: r2 = 0.38, p = 2,31 × ­10−5;
NW-Amur: r2 = 0.92, p = 1.53 × ­10−22) (Fig. 3a). In 1977,
the PDO switched from negative to positive phase andremained positive until 1997. These results suggest thatthe increase in P − E after 1977 was related to the PDO
phase change. Examination of Z
­ 500 during the positive
phase of the PDO (1977–1997) reveals an anticyclonicanomaly around the Sea of Okhotsk, and a cyclonicanomaly around the NW-Amur (Fig. 3b). These results
are in close agreement with those from Zhang et al.
(2020), which showed the presence of anticyclonic andcyclonic wave-like teleconnection pattern in the midlatitudes of the Northern Hemisphere during the positive
PDO phase. In addition, the anomaly of the verticallyintegrated water vapour flux during 1977 − 1997 showed
increases in eastward water vapour flux into NE-Amurand NW-Amur and northward water vapour flux into
the coastal area of NE-Amur and S-Amur. On the basisof these results, we infer that the increase in late summer P − E in the Amur River basin after 1977 (Fig. 2b),especially in the NE-Amur and NW-Amur, was likely aresult of the changes in the atmospheric circulation pattern associated with the positive phase of the PDO of
1977–1997.
3.2 Lag relationship between the interannual variationsin climate variables and dFe concentration in the Amur
River basin

Figure 4 shows the interannual variations in annual/seasonal dFe concentrations in the Amur River. The
range of annual concentration variations remained small

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Fig. 4 Interannual variations in annual/seasonal dissolved iron (dFe)concentrations in the Amur River. a Annual, b late spring (April, May,
June; AMJ), and c late summer (July, August, September; JAS) meandFe concentrations. Error bars show the standard error of the data.
Data from 2005 are missing

between 1960 and 1994. Between 1995 and 1997, there
was an extremely large increase in annual concentration(Fig. 4a). The peak of annual concentration in 1997 was
1.85 mg ­L−1, which was approximately 500% of the mean
concentration (0.38 mg ­L−1) of 1960–1994. There weresimilar variations in late summer concentration (Fig. 4c).
There was an extremely large increase in late summer

Fig. 3 Changes in late summer net precipitation (P − E), Pacific Decadal Oscillation (PDO) index, and atmospheric circulation. a Interannual
variations in the 9-year moving averages of late summer (July, August, and September; JAS) P − E in the NE-Amur (red), the NW-Amur (green),
the S-Amur (blue), and late summer PDO index (black); b the anomaly of mean geopotential height at the 500-hPa level in late summer
during the positive PDO phase of 1977–1997 relative to 1960–2006. In a, the black dotted two lines indicate the years 1977 and 1997,
when the phase of the PDO changed from negative (positive) to positive (negative). In b, the red area indicates the high-pressure anomaly,
while the blue area indicates the low-pressure anomaly. Arrows denote the anomaly of mean vertically integrated water vapour flux during 1977–
1997 relative to 1960–2006. Yellow arrows denote that the anomaly was statistically significant at the 95% confidence level in t-tests

Tashiro et al. Progress in Earth and Planetary Science(2024) 11:17

concentration between 1995 and 1997; the peak in 1997
was 1.88 mg ­L−1, which was approximately 600% of themean concentration (0.33 mg L­ −1) of 1960–1994. There
was an extremely large increase in late spring concentration between 1997 and 1998 (Fig. 4b), which was 1 year
after the extreme increase in annual and late summer
concentrations. The peak of late spring concentration in1998 was 1.06 mg ­L−1, which was lower than the peak oflate summer concentration (1.88 mg ­L−1) in 1997.
Cross correlation coefficients between annual/seasonaldFe concentrations and climate variables (Ta, AT, and latesummer P − E) are shown in Fig. 5. No significant correlation was found between annual/seasonal concentrations
and late summer P − E at lags of 0–9 years (Fig. 5g–i).
For Ta, the strongest significant positive correlation was
found between annual dFe concentration and Ta at a lagof 7 years (NE-Amur: r = 0.55, p = 0.0003; NW-Amur:r = 0.43, p = 0.0059; S-Amur: r = 0.49, p = 0.0016), andthe second strongest correlation was found at a lag of
8 years (NE-Amur: r = 0.48, p = 0.0021; S-Amur: r = 0.44,
p = 0.0052) (Fig. 5a). Similarly, there was a significant
positive correlation between late summer dFe concentration and Ta at a lag of 7 years (NE-Amur: r = 0.69,
p = 1.4 × ­10−6; NW-Amur: r = 0.54, p = 0.0004; S-Amur:r = 0.60, p = 5.7 × ­10−5) (Fig. 5c). Correlation coefficients between late summer dFe concentrations and Ta

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exceeded those between annual concentrations and Ta.
It is noteworthy that correlation coefficients between
annual/late summer dFe concentration and Ta with a lagof 7 years were the largest in the NE-Amur, where permafrost is sporadically distributed. These results indicate
a close relationship between high Ta in NE-Amur in year
Y and increased annual/late summer dFe concentrationsin the Amur River in year Y + 7. Figure 6a shows the scatter plot of late summer dFe concentration and Ta in NEAmur with a lag of 7 years. The lag of 7 years can also
be found by comparing the interannual variations in Ta
and late summer dFe concentration; in NE-Amur, Ta wasrelatively high in 1963, 1968, 1975, 1988–1990, and 1995
(Fig. 2a), and late summer dFe concentration increased in
1970, 1975, 1982, 1995–1997, and 2002 (Fig. 4c). Thereis a similar lag relationship between annual/seasonal dFe
concentrations and AT in the NE-Amur (Fig. 5d–f ) andthe largest correlation coefficient was found between
late summer concentrations and AT with a lag of 7 years(r = 0.51, p = 0.0010) (Fig. 5f ). This implies that late summer dFe concentration in the Amur River increased
7 years after the acceleration of permafrost degradation
because of warm summer in the NE-Amur.
For late spring dFe concentration, the strongest significant positive correlation was found between late spring
concentration and Ta at a lag of 9 years (NE-Amur:

Fig. 5 Cross correlation coefficients between dissolved iron (dFe) concentrations and climate variables in the Amur River basin. a Annual dFe
concentrations and mean air temperature (Ta); b late spring (April, May, June; AMJ) dFe concentrations and Ta; c late summer (July, August,
September; JAS) dFe concentrations and Ta; d Annual dFe concentrations and accumulated temperature (AT); e late spring dFe concentrations
and AT; f late summer dFe concentrations and AT; g annual dFe concentrations and late summer net precipitation (P − E); h late spring dFe
concentrations and late summer P − E; i late summer dFe concentrations and late summer P − E. In a–c, ** indicates p < 0.01

Tashiro et al. Progress in Earth and Planetary Science(2024) 11:17

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Fig. 6 Relationship between dissolved iron (dFe) concentrations, time lagged annual air temperature (Ta), and discharge. a Late summer (July,
August, and September; JAS) dFe concentrations in the Amur River and Ta with a 7-year lag in the NE-Amur; b late spring (April, May, and June; AMJ)
dFe concentrations and Ta with a 9-year lag in the NE-Amur; c late summer dFe concentrations and discharge; d late spring dFe concentrations
and discharge. Only Ta in the NE-Amur is shown because the Pearson’s coefficient between Ta and dFe in the NE-Amur is higher than that in
NW-Amur and that in S-Amur (Fig. 5a–c). In a and b, seasonal mean dFe concentrations are shown. In c and d, individual measurements of dFe
concentration and discharge are shown. In c, the black circle denotes the data in 1997, which is the peak year of iron anomaly

r = 0.57, p = 0.0002; NW-Amur: r = 0.47, p = 0.0033;
S-Amur: r = 0.52, p = 0.0009) and the second strongest correlation was found at a lag of 8 years (NE-Amur:r = 0.47, p = 0.0027; NW-Amur: r = 0.44, p = 0.0061;
S-Amur: r = 0.47, p = 0.0030) (Fig. 5b). Similar to annual/late summer dFe concentrations, correlation coefficients
between late spring concentration and Ta with a lag of
9 years in the NE-Amur were larger than those for NWAmur and S-Amur. Figure 6b shows the significant positive correlation between late spring dFe concentration
and Ta in NE-Amur with a lag of 9 years.
During a warm year, accelerated permafrost degradation produces thawed soil; Fe(III) minerals in the newly
thawed soil can be exposed to microbial reduction, which
could lead to the intensive generation of soluble Fe(II)in the soils that are deep in the active layer. Studies haveconfirmed the accumulation of dFe and dissolved Fe(II)in the deeper part of the active layer by investigating thevertical distributions of dFe and dissolved Fe(II) in permafrost areas in summer (Herndon et al. 2015; Jessen
et al. 2014). The intensive generation of Fe(II) in deep
soils can potentially increase riverine dFe concentration
by forming complexes with humic substances, which aresoluble in river waters with neutral pH (Laglera and Van
Den Berg 2009). However, because soil permeability islow, the Fe(II) in deep soils will take several years to travel
through the deeper part of the active layer to the rivers(Jessen et al. 2014; Quinton et al. 2008, 2009). Our results
suggest that permafrost degradation in NE-Amur caused
an intensive generation of Fe(II), which took approximately 7 years to reach rivers through the deeper soils in
the active layer and subsequently increased dFe concentration in the Amur River. This is a plausible mechanism
in terms of water path; deep groundwater (suprapermafrost water) considerably influences river water chemistry in late summer when active layer thickness reaches its
maximum (Bagard et al. 2011; Evans et al. 2020). Given
that the correlation coefficients between late summer dFe
concentration and Ta were large for lags of 7 and 8 years,
we infer that increased dFe discharge likely lasted forat least 1–2 years. Unexpectedly, we found a significant
correlation between late spring dFe concentration and
Ta at lags of 8 and 9 years (Fig. 5b and 6b), even though
the influence of groundwater is minimum during springfloods. It is currently difficult to understand the difference between the 7- and 8-year lag in late summer andthe 8- and 9-year lag in late spring, but these higher dFe
concentrations in late spring may be related to increased
dFe discharge in late summer. One possible mechanism
could be that deep groundwater-derived dFe partiallyprecipitated as iron-oxyhydroxides after flowing into theriver in late summer, and dissolved again the following
spring when it came into contact with the large amounts
of DOC that were released from the organic-rich topsoil

Tashiro et al. Progress in Earth and Planetary Science(2024) 11:17

by snowmelt. Another possible mechanism is that deep
groundwater is not fully frozen and continues to interact
with river waters even in spring.
In addition to inflow of dFe-rich groundwater, seasonalhydrological events are well known to greatly influenceon riverine dFe concentration in the Amur River basin(Tashiro et al. 2020; Yan et al. 2016). Tashiro et al. (2020)
observed seasonal variation in dFe concentration in the
Amur-Mid region (central part of the NE-Amur) andfound that spring snowmelt and summer rainfall greatly
contributes to dFe runoff into rivers from organic soil
layer. Increased dFe concentration during spring floods
was also observed in the Amur River and tributary in
the S-Amur (Yan et al. 2016). In general, increases in dFe
concentration in response to hydrological events suchas summer rainfall and spring snowmelt are observed
simultaneously with increased water level and discharge
in the Arctic and sub-Arctic regions (Abesser et al. 2006;
Anderson et al. 2006; Tashiro et al. 2020; Rember andTrefry 2004). However, we found no significant correlation between the individual measurements of Amur River
discharge and late spring/late summer dFe concentration(Fig. 6c–d). Therefore, interannual variations in annual/seasonal dFe concentrations in the Amur River between
1960 and 2006, including the iron anomaly (1995–1997),
were not fully explained by the impacts of snowmelt andrainfall.
3.3 Mechanisms underlying the iron anomaly
between 1995 and 1997

It should be emphasized that the iron anomaly between
1995 and 1997 was a widespread phenomenon, which
was observed in many of the tributaries in the NE-Amur(Shamov et al. 2014). Based on this fact and the 7-year
lag between Ta, AT and late summer dFe concentration(Fig. 3b,e), we hypothesize that the extreme increase indFe concentration in the Amur River between 1995 and1997 was resulted from accelerated permafrost degradation caused by continuous warming between 1988 and1990 in the NE-Amur (Fig. 2a). In particular, 1988 was
the warmest spring–summer between 1960 and 2006 in
the NE-Amur, as shown in interannual variation in AT(Fig. 2b). Actually, late summer air temperature in 1988
in the NE-Amur was 15.5℃, which was 1.4 °C higher
than the mean of 1960–2006 (Additional file 1: Fig. S2).
Although the peaks of AT and late summer air temperature were shown in 1988, the steady increases in soil
temperature by approximately 1.0℃ were recorded atseveral weather stations in the NE-Amur from 1988 to1990 (Shamov et al. 2014). As discussed in the previous
section, accelerated permafrost degradation followed by
the increased soil temperature in these years may havecaused the iron anomaly in the Amur River between

Page 9 of 13

1995 and 1997 by the inflow of dFe-rich groundwater
through the deeper part in active layer. In terms of permafrost hydrology, this mechanism is in good agreementwith the fact that the highest dFe concentration (2.75 mg­L−1) in 1997, the peak year of iron anomaly, was observedin October when the contribution of deep groundwater
to rivers increases as the active layer thickness reaches
its maximum. Moreover, previous study on long-term
record of iron content in the Amur River during the winter low water level showed that the highest dFe discharge(269 t ­day−1) was observed in 1995–1996 winter, which
was considerably higher than the mean of 1950–2012(47.7 t d­ ay−1) (Shesterkin et al. 2013). There was unfortunately no available data of dFe concentration, and winterobservation for 1996–1997 and 1997–1998 were missingin the previous study. Nevertheless, their results support our hypothesized mechanism that the iron anomaly
between 1995 and 1997 was caused by the inflow of dFerich groundwater because winter baseflow is generally
dominated by deep groundwater rich in minerals (Bagard
et al. 2011; Holmes et al. 2012).
Increased late summer P − E after 1977 in the Amur
River basin (Fig. 2c), which is likely resulted fromincreased water vapour flux convergence during thepositive PDO phase (1977–1997) (Fig. 3), could have also
promoted dFe discharge into the Amur River. Although
we found no significant relationship between annual/seasonal dFe concentrations and late summer P − E (Fig. 5g–i), we hypothesize that persistently positive P − E after
1977 throughout the Amur River basin may have had thefollowing effects on the biogeochemical and hydrological cycles: (1) intensification of permafrost degradation
because of increased water infiltration and increased
heat transport to deeper soil (Douglas et al. 2020); (2)promotion of microbial iron reduction under anaerobic
conditions because of increased soil water content (Lipson et al. 2012); and (3) increased groundwater discharge
into rivers (Connon et al. 2014). These effects were likely
more intense in the NE-Amur and the NW-Amur, wherelate summer P − E were larger than those in the S-Amurafter 1977 (Fig. 2c).
The relative importance of dFe transport from theNE-Amur to the Amur River is also supported by thedifferences in the water chemistry of the tributaries inthe three regions. According to previous studies on the
distribution of riverine dFe concentration in the middle
and lower Amur River basin, the amount of dFe, humic
acids, and organically-bound Fe is much higher in rivers
in the NE-Amur than in the S-Amur because of the large
amounts of organic matter and humic substances in thetaiga forests and lowland wetlands in the NE-Amur (Levshina et al. 2012, 2016). Unfortunately, there is no reporton riverine dFe concentration in the NW-Amur, but it isTashiro et al. Progress in Earth and Planetary Science(2024) 11:17

supposed to be low because of the low concentrations of
DOC and humic substances in the rivers in this region(Levshina et al. 2016). Taking into account these regional
characteristics of the river water chemistry in the Amur
River basin, we infer that the NE-Amur has the highest
dFe supply capacity in the basin. In addition, Tashiro
et al. (2020) examined the seasonal variations in dFe concentrations in peat soils and rivers and concluded thatwetlands (peat bogs) with underlying permafrost in the
NE-Amur can be important sources of dFe to the Amur
River. Combining the findings from previous studies andthose from the present study, we infer that increased dFe
discharge from permafrost-distributed landscapes suchas wetlands (Tashiro et al. 2020, 2023) in the NE-Amurwere the primary causes of the extreme increase in dFe
concentration between 1995 and 1997.
In addition to permafrost degradation, land use change
may have a considerable influence on dFe concentration.
According to Ganzey et al. (2010), the areas of forests andwetlands in the NE-Amur remained almost unchanged
between 1930 and 2000, except for the northern part ofSikhote-Alin (Fig. 1) where intensive deforestation was
carried out in the 1980s. In contrast, large-scale agricultural developments have taken place in the Sanjiang Plainin the S-Amur in the twentieth century (Fig. 1). Between
1949 and 1994, 72.2% of the wetland area (approximately
4 Mha) was reclaimed and converted to paddy fields(Pan et al. 2011). This had considerable impacts on riverine dFe concentration in the Sanjiang Plain. For example, the Naoli River in the Sanjiang Plain showed a steadydecrease in the concentration of free iron because ofan 87% decrease in wetlands in the watershed between
1949 and 2000 (Pan et al. 2011). On the contrary, using
Fe(II)-rich groundwater to irrigate paddy fields may
increase dFe discharge into rivers through agricultural
canals. However, the impact of irrigation on dFe discharge is likely to be small. Previous study showed that
more than half of the dFe precipitates during irrigation
because of the low concentration of organic ligands suchas humic acids in the paddy fields of Sanjiang Plain (Panet al. 2011). According to numerical modelling studies,groundwater pumping is estimated to increase the dFe
flux from Sanjiang Plain by 2000 t ­year−1 (Onishi et al.
2009), which is only 3.4% of the extreme increase in dFe
flux (58,400 t y­ ear−1) in the Amur River in 1997 (Shamov
et al. 2014). Therefore, we infer that land use change in
the Amur River basin in twentieth century is clearly not
the major cause of the iron anomaly.
Overall, we hypothesis that the extreme iron anomaly
in the Amur River between 1995 and 1997 was resulted
from continuous warming and permafrost degradation between 1988 and 1990 in the NE-Amur. Unfortunately, there is no multi-decadal monitoring data of dFe

Page 10 of 13

concentration from the tributaries of the Amur River. In
addition, lack of knowledge of the detailed permafrost
distribution and the mechanism of dFe discharge throughthe deeper part of the active layer precludes the verification of our 7-year lag hypothesis. Nevertheless, ourresults highlight the importance of studying the influenceof permafrost degradation from a macroscopic perspective; long-term changes in Ta and late summer P − E, andthese effects over time should be taken into considerationin the study of iron biogeochemistry in the Amur Riverbasin. To improve our understanding of the iron anomaly, further research should be focused on permafrost
distribution, soil profiles (peat and mineral horizons),
soil permeability, and dFe dynamics in the deeper partof the active layer in the NE-Amur. Moreover, numerical modelling studies are also needed to validate the time
lag relationships between Ta and the annual/seasonal dFe
concentrations that were reported in this study.

4 Conclusions
In this study, we took the hydroclimatological approachto assess whether permafrost degradation is responsible for the extreme increase in dFe concentration in
the Amur River during 1995–1997. After 1977, latesummer P − E increased and remained positive andhigh throughout the basin, especially in the NE-Amurand NW-Amur. We inferred that increased soil moisture after 1977 was caused by increased water vapour
flux convergence associated with the positive phase of
the PDO (1977–1997). In the NE-Amur, spring-summers were considerably warm continuously between
1988 and 1990, and the highest AT was shown in 1988
between 1960 and 2006. More importantly, interannual
variations in late summer dFe concentrations in the
Amur River were significantly correlated with interannual variations in Ta and AT in the NE-Amur with a lagof 7 years. On the basis of these results, we propose thefollowing hypothesis as a reasonable cause for the ironanomaly: continuous warming between 1988 and 1990
in the background of persistently higher levels of soil
moisture since 1977 accelerated permafrost degradation in the NE-Amur and promoted iron bioavailability and dFe generation in the deeper part of the active
layer; consequently, large amounts of dFe were discharged into rivers 7 years later, leading to an extreme
increase in dFe concentration in the Amur Riverbetween 1995 and 1997. Further research is needed
to verify our hypothesis. However, by taking a macroscopic perspective in this study, we discovered the significant time lag relationship between Ta, AT and dFe
concentration. To our knowledge, this is the first study
to suggest the time-lagged impact of permafrost degradation on iron biogeochemistry in the Amur RiverTashiro et al. Progress in Earth and Planetary Science(2024) 11:17

basin, and to highlight the importance of the integration of climate data analyses into studies of Arctic andsub-Arctic river biogeochemistry with a focus on theinfluence of permafrost degradation.
Abbreviations
AT	Accumulated temperature
CRU​	Climatic research unitdFe	Dissolved ironJRA-55	Japanese 55-year reanalysis
P − E	Precipitation minus evapotranspiration
PDO	Pacific decadal oscillation
Ta	Annual air temperature

Supplementary Information

Page 11 of 13

Declarations
Competing interests
The authors declare that they have no competing interest.
Author details
1
Institute for Space–Earth Environmental Research, Nagoya University,
Nagoya, Aichi 464‑8601, Japan. 2 The IDEC Institute ‑ Center for Peacefuland Sustainable Futures (CEPEAS), Network for Education and Research On
Peace and Sustainability (NERPS), Graduate School of Humanities and Social
Sciences International Economic Development Program (IEDP), Graduate
School of Innovation and Practice for Smart Society (SmaSo), Seto Inland Sea
Carbon Neutral Research Center, Hiroshima University, Higashi‑Hiroshima,
Hiroshima 739‑8529, Japan.
Received: 28 August 2023 Accepted: 15 March 2024

The online version contains supplementary material available at https://​doi.​
org/​10.​1186/​s40645-​024-​00619-w.
Additional file 1. Figure S1. Relationship between annual air temperature (Ta) calculated from CRU and those from JRA-55 between 1960 and2006 in the NE-Amur (red), the NW-Amur (green), and the S-Amur (blue).
Black straight line denotes 1:1 line (y = x). Figure S2. Interannual variations in late summer (July, August, and September) air temperature in the
NE-Amur (red), the NW-Amur (green), and the S-Amur (blue). Figure S3.
Relationship between accumulated temperature (AT) and late summer air
temperature in the NE-Amur (red), the NW-Amur (green), and the S-Amur(blue).
Acknowledgements
This research was funded by the Japan Society for the Promotion of Science (JSPS) KAKENHI (Grant Number 19H05668) project entitled “Pan-Arctic
Water-Carbon Cycles (PAWCs)” (https://​enpaw​cs.​home.​blog/). It was also
supported by the Japan Science and Technology Agency (JST) Belmont
Forum (Grant Number JPMJBF2003). We thank all the staff in Far Eastern
Hydrometeorology and Environmental Monitoring (Roshydromet). All Amur
River dFe concentration and discharge data were provided by Roshydromet
under project C-04 of the Research Institute for Humanity and Nature (RIHN),
Japan, entitled “Human Activities in Northeastern Asia and Their Impact on the
Biological Productivity in North Pacific Ocean”, with Takayuki Shiraiwa as theprincipal investigator between 2005 and 2009. We thank Tina Tin, PhD, from
Edanz (https://​jp.​edanz.​com/​ac) for editing a draft of this manuscript.
Author contributions
YT conceived the study and analysed the data with significant input from TH,
HK, and MK. YT wrote the paper with substantial help from TH and HK withregard to data handling and interpretation of results. All authors discussed
the results of the study, reviewed the final manuscript, and approved themanuscript submission.
Funding
This research was funded by the Japan Society for the Promotion of Science (JSPS) KAKENHI (Grant Number 19H05668) project entitled “Pan-Arctic
Water-Carbon Cycles (PAWCs)” (https://enpawcs.home.blog/). It was also supported by the Japan Science and Technology Agency (JST) Belmont Forum(Grant Number JPMJBF2003).
Availability of data and materials
Data of dFe concentration in the Amur River are available in the Figshare
repository, https://​doi.​org/https://​doi.​org/​10.​6084/​m9.​figsh​are.​20550​891.
Climatic Research Unit gridded Time Series v4.05 (CRU) data are available at:https://​www.​uea.​ac.​uk/​groups-​and-​centr​es/​clima​tic-​resea​rch-​unit. Japanese
Reanalysis Project (JRA-55, 1.25° × 1.25°) data are available at: https://​jra.​kishou.​go.​jp/​JRA-​55/​index_​ja.​html. PDO index data from Japan Meteorological
Agency are available at: https://​www.​data.​jma.​go.​jp/​gmd/​kaiyou/​data/​shind​an/b_​1/​pdo/​pdo.​html

References
Abesser C, Robinson R, Soulsby C (2006) Iron and manganese cycling in thestorm runoff of a Scottish upland catchment. J Hydrol 326:59–78. https://​doi.​org/​10.​1016/j.​jhydr​ol.​2005.​10.​034
Aiken GR, Spencer RGM, Striegl RG, Schuster PF, Raymond PA (2014) Influencesof glacier melt and permafrost thaw on the age of dissolved organiccarbon in the Yukon River basin. Glob Biogeochem Cycles 28:525–537.
https://​doi.​org/​10.​1002/​2013G​B0047​64
Andersson K, Dahlqvist R, Turner D, Stolpe B, Larsson T, Ingri J, Andersson P(2006) Colloidal rare earth elements in a boreal river: Changing sourcesand distributions during the spring flood. Geochim Cosmochim Acta
70:3261–3274. https://​doi.​org/​10.​1016/j.​gca.​2006.​04.​021
Bagard ML, Chabaux F, Pokrovsky OS, Viers J, Prokushkin AS, Pa S, Rihs S,
Schmitt A, Dupre B (2011) Seasonal variability of element fluxes in two
Central Siberian rivers draining high latitude permafrost dominated areas.
Geochim Cosmochim Acta 75:3335–3357. https://​doi.​org/​10.​1016/j.​gca.​2011.​03.​024
Bruland KW, Lohan MC (2003) Controls of Trace Metals in Seawater. In: Heinrich
DH, Karl KT (eds) Treatise on Geochemistry. Elsevier, Amsterdam, pp
23–47
Colombo N, Salerno F, Gruber S, Freppaz M, Williams M, Fratianni S, Giardino M(2018) Review: impacts of permafrost degradation on inorganic chemistry of surface fresh water. Glob Planet Change 162:69–83. https://​doi.​org/​
10.​1016/j.​glopl​acha.​2017.​11.​017
Connon RF, Quinton WL, Craig JR, Hayashi M (2014) Changing hydrologic
connectivity due to permafrost thaw in the lower Liard River valley, NWT.
Canada Hydrol Process 28:4163–4178. https://​doi.​org/​10.​1002/​hyp.​10206
Douglas TA, Turetsky MR, Koven CD (2020) Increased rainfall stimulates permafrost thaw across a variety of Interior Alaskan boreal ecosystems. NPJ Clim
Atmos Sci 3:1–7. https://​doi.​org/​10.​1038/​s41612-​020-​0130-4
Drake TW, Guillemette F, Hemingway JD, Podgorski DC, Zimov NS, Spencer
RGM (2018) Increasing alkalinity export from large Russian Arctic rivers.
Environ Sci Technol 52:8302–8308. https://​doi.​org/​10.​1021/​acs.​est.​8b010​
51
Evans SG, Yokeley B, Stephens C, Brewer B (2020) Potential mechanistic causes
of increased baseflow across northern Eurasia catchments underlain bypermafrost. Hydrol Process 34:2676–2690. https://​doi.​org/​10.​1002/​hyp.​13759
Frey KE, McClelland JW (2009) Impacts of permafrost degradation on arctic
river biogeochemistry. Hydrol Process 23:169–182. https://​doi.​org/​10.​
1002/​hyp.​7196
Frey KE, McClelland JW, Holmes RM, Smith LG (2007) Impacts of climate
warming and permafrost thaw on the riverine transport of nitrogen andphosphorus to the Kara Sea. JGR Biogeosci 112:1–10. https://​doi.​org/​10.​1029/​2006J​G0003​69
Ganzey SS, Ermoshin VV, Mishina NV, (2010) the landscape changes after 1930
using two kinds of land use maps (1930 and 2000). In: Shiraiwa (ed)Report on Amur-Okhotsk Project, vol 6. Research Institute for Humanity
and Nature, Kyoto, pp 251–262. http://​id.​nii.​ac.​jp/​1422/​00002​691/

Tashiro et al. Progress in Earth and Planetary Science(2024) 11:17

Harris I, Osborn TJ, Jones P, Lister D (2020) Version 4 of the CRU TS monthly
high-resolution gridded multivariate climate dataset. Sci Data 7:1–18.
https://​doi.​org/​10.​1038/​s41597-​020-​0453-3
Herndon EM, Yang Z, Bargar J, Janot N, Regier TZ, Graham DE, Wullschleger SD,
Gu B, Liang L (2015) Geochemical drivers of organic matter decomposition in arctic tundra soils. Biogeochemistry 126:397–414. https://​doi.​org/​
10.​1007/​s10533-​015-​0165-5
Hinkel KM, Paetzold F, Nelson FE, Bockheim JG (2001) Patterns of soil temperature and moisture in the active layer and upper permafrost at Barrow,
Alaska: 1993–1999. Glob Planet Change 29:293–309. https://​doi.​org/​10.​1016/​S0921-​8181(01)​00096-0
Holmes RM, McClelland JW, Peterson BJ, Tank SE, Bulygina E, Eglinton TI,
Gordeev VV, Gurtovaya TY, Raymond PA, Repeta DJ, Staples R, Striegl RG,
Zhulidov AV, Zimov SA (2012) Seasonal and annual fluxes of nutrients andorganic matter from large rivers to the arctic ocean and surrounding seas.
Estuaries Coast 35:369–382. https://​doi.​org/​10.​1007/​s12237-​011-​9386-6
Hydrochemical Institute (2006) Russian international technical standards
52.24.358–2006: Mass concentration of total Fe in waters. https://​files.​stroy​inf.​ru/​Index2/​1/​42938​37/​42938​37319.​htm [In Russian]
Ilina SM, Poitrasson F, Lapitskiy SA, Alekhin YV (2013) Extreme iron isotope
fractionation between colloids and particles of boreal and temperateorganic-rich waters. Geochim Cosmochim Acta 101:96–111. https://​doi.​
org/​10.​1016/j.​gca.​2012.​10.​023
Ingri J, Conrad S, Lidman F, Nordblad F, Engström E, Rodushkin I, Porcelli D(2018) Iron isotope pathways in the boreal landscape: Role of the riparianzone. Geochim Cosmochim Acta 239:49–60. https://​doi.​org/​10.​1016/j.​
gca.​2018.​07.​030
Jessen S, Holmslykke HD, Rasmussen K, Richardt N, Holm PE (2014) Hydrology
and pore water chemistry in a permafrost wetland, Ilulissat, Greenland.
Water Resour Res 50:4760–4774. https://​doi.​org/​10.​1002/​2013W​R0143​76
Kawahigashi M, Kaiser K, Kalbitz K, Rodionov A, Guggenberger G (2004) Dissolved organic matter in small streams along a gradient from discontinuous to continuous permafrost. Glob Change Biol 10:1576–1586. https://​doi.​org/​10.​1111/j.​1365-​2486.​2004.​00827.x
Kobayashi S, Ota Y, Harada Y, Ebita A, Moriya M, Onoda H, Onogi K, Kamahori H,
Kobayashi C, Endo H, Miyaoka K, Takahashi K (2015) The JRA-55 reanalysis:
General specifications and basic characteristics. J Meteor Soc Japan
93:5–48. https://​doi.​org/​10.​2151/​jmsj.​2015-​001
Kokeji SV, Burn CR (2005) Geochemistry of the active layer and near-surface
permafrost, Mackenzie delta region, Northwest Territories, Canada. Can J
Earth Sci 42:37–48. https://​doi.​org/​10.​1139/​E04-​089
Kolosov RR, Prokushkin AS, Pokrovsky OS (2016) Major anion and cation fluxes
from the Central SiberianPlateau watersheds with underlying permafrost.
IOP Conf Ser Earth Environ Sci 48:012018. https://​doi.​org/​10.​1088/​1755-​
1315/​48/1/​012018
Kritzberg ES, Ekström SM (2012) Increasing iron concentrations in surface
waters–A factor behind brownification? Biogeosciences 9:1465–1478.
https://​doi.​org/​10.​5194/​bg-9-​1465-​2012
Laglera LM, Van Den Berg CMG (2009) Evidence for geochemical control ofiron by humic substances in seawater. Limnol Oceanogr 54:610–619.
https://​doi.​org/​10.​4319/​lo.​2009.​54.2.​0610
Levshina SI (2012) Iron distribution in surface waters in the Middle and Lower
Amur basin. Water Resour 39:375–383. https://​doi.​org/​10.​1134/​s0097​
80781​20400​82
Levshina SI (2016) Geochemistry of organic matter in river waters of theAmur basin, Russia. Environ Earth Sci 75:1–10. https://​doi.​org/​10.​1007/​s12665-​015-​5202-0
Lipson DA, Zona D, Raab TK, Bozzolo F, Mauritz M, Oechel WC (2012) Watertable height and microtopography control biogeochemical cycling in an
Arctic coastal tundra ecosystem. Biogeosciences 9:577–591. https://​doi.​
org/​10.​5194/​bg-9-​577-​2012
Liu Y, Sun C, Hao Z, He B (2022) Periodic decadal swings in dry/wet conditions
over Central Asia. Environ Res Lett 17:054050. https://​doi.​org/​10.​1088/​
1748-​9326/​ac6c3bMantua NJ, Hare SR, Zhang Y, Wallace JM, Francis RC (1997) A pacific interdecadal climate oscillation with impacts on salmon production; Bull. Amer
Meteor Soc 78:1069–1079. https://​doi.​org/​10.​1175/​1520-​0477(1997)​078%​
3c1069:​APICOW%​3e2.0.​CO;2
Martin JH, Fitzwater SE (1988) Iron deficiency limits phytoplankton growth in
the north-east Pacific subarctic. Nature 331:341–343. https://​doi.​org/​10.​1038/​33134​1a0

Page 12 of 13

Martin JH, Gordon RM, Fitzwater SE, Broenkow WW (1989) Vertex: phytoplankton/iron studies in the Gulf of Alaska. Deep-Sea Res I: Oceanogr Res Pap
36:649–680. https://​doi.​org/​10.​1016/​0198-​0149(89)​90144-1
Martin JH, Gordon RM, Fitzwater SE (1990) Iron in Antarctic waters. Nature
345:156–158. https://​doi.​org/​10.​1038/​34515​6a0
Martin JH, Coale KH, Johnson KS, Fitzwater SE, Gordon RM, Tanner SJ, Hunter
CN, Elrod VA, Nowicki JL, Coley TL, Barber RT, Lindley S, Watson AJ,
Van Scoy K, Law CS, Liddicoat MI, Ling R, Stanton T, Stockel J, Collins C,
Anderson A, Bidigare R, Ondrusek M, Latasa M, Millero FJ, Lee K, Yao W,
Zhang JZ, Friederich G, Sakamoto C, Chavez F, Buck K, Kolber Z, Greene R,
Falkowski P, Chisholm SW, Hoge F, Swift R, Yungel J, Turner S, Nightingale P, Hatton A, Liss P, Tindale NW (1994) Testing the iron hypothesis inecosystems of the equatorial Pacific Ocean. Nature 371:123–129. https://​doi.​org/​10.​1038/​37112​3a0
Matsunaga K, Nishioka J, Kuma K, Toya K, Suzuki Y (1998) Riverine input ofbioavailable iron supporting phytoplankton growth in Kesennuma Bay(Japan). Water Res 32:3436–3442. https://​doi.​org/​10.​1016/​S0043-​1354(98)​00113-4
McClelland JW, Stieglitz M, Pan F, Holmes RM, Peterson BJ (2007) Recentchanges in nitrate and dissolved organic carbon export from the upper
Kuparuk River, North Slope. Alaska JGR: Biogeosciences 112:1–13. https://​doi.​org/​10.​1029/​2006J​G0003​71
Mokhov II, Semenov VA (2016) Weather and climate anomalies in russian
regions related to global climate change. Russ Meteorol Hydrol 41:84–92.
https://​doi.​org/​10.​3103/​S1068​37391​60200​23
Moore JK, Braucher O (2008) Sedimentary and mineral dust sources of dissolved iron to the world ocean. Biogeosciences 5:631–656. https://​doi.​
org/​10.​5194/​bg-5-​631-​2008
Nagao, S. Terashima M, Kodama H, Kim VI, Shesterkin PV, Makhinov AN, (2007)
Migration behavior of Fe in the Amur River Basin. In: Shiraiwa (ed) Reporton Amur-Okhotsk Project, vol 4. Research Institute for Humanity andNature, Kyoto, pp 37–48. http://​id.​nii.​ac.​jp/​1422/​00002​607/
Nishioka J, Nakatsuka T, Watanabe YW, Yasuda I, Kuma K, Ogawa H, Ebuchi N,
Scherbinin A, Volkov YN, Shiraiwa T, Wakatsuchi M (2013) Intensive mixing
along an island chain controls oceanic biogeochemical cycles. Glob
Biogeochem Cycles 27:920–929. https://​doi.​org/​10.​1002/​gbc.​20088
Nishioka J, Nakatsuka T, Ono K, Volkov YN, Scherbinin A, Shiraiwa T (2014)
Quantitative evaluation of iron transport processes in the Sea of Okhotsk.
Prog Oceanogr 126:180–193. https://​doi.​org/​10.​1016/j.​pocean.​2014.​04.​
011
Novorotskii PV (2007) Climate changes in the Amur River basin in the last 115
years. Russ Meteorol Hydrol 32:102–109. https://​doi.​org/​10.​3103/​S1068​
37390​70200​45
Olefeldt D, Persson A, Turetsky MR (2014) Influence of the permafrost boundary on dissolved organic matter characteristics in rivers within the Boreal
and Taiga plains of western Canada. Environ Res Lett 9:035005. https://​doi.​org/​10.​1088/​1748-​9326/9/​3/​035005
Onishi T, Yoh M, Yan B, Kawahigashi M, (2009) Evaluation of agricultural activity
impacts on dissolved iron flux in the Sanjiang Plain, China. In: Abstractsof the Japanese society of irrigation, drainage and rural engineering
proceedings conference, University of Tsukuba, Ibaraki, 4–6 August 2009.
[In Japanese]
Palviainen M, Lehtoranta J, Ekholm P, Ruoho-Airola T, Kortelainen P (2015)
Land cover controls the export of terminal electron acceptors fromboreal catchments. Ecosystems 18:343–358. https://​doi.​org/​10.​1007/​
s10021-​014-​9832-y
Pan XF, Yan BX, Yoh M (2011) Effects of land use and changes in cover on thetransformation and transportation of iron: a case study of the Sanjiang
Plain, Northeast China. Sci China Earth Sci 54:686–693. https://​doi.​org/​10.​
1007/​s11430-​010-​4082-0
Peixoto JP, Oort AH, (1983) The atmospheric branch of the hydrological cycle
and climate: In Street-Perrott A, Beran M, Ratcliffe R (eds) Variations in the
Global Water Budget, Springer, Dordrecht, pp 5–65. https://​doi.​org/​10.​
1007/​978-​94-​009-​6954-4_2
Peixoto JP, Oort AH (1992) Physics of Climate. American Institute of Physics,
New York
Petrone KC, Jones JB, Hinzman LD, Boone RD (2006) Seasonal export ofcarbon, nitrogen, and major solutes from Alaskan catchments withdiscontinuous permafrost. JGR Biogeosciences 111:1–13. https://​doi.​org/​
10.​1029/​2005J​G0000​55

Tashiro et al. Progress in Earth and Planetary Science(2024) 11:17

Pokrovsky OS, Manasypov RM, Loiko SV, Shirokova LS, Krickov IA, Pokrovsky BG,
Kolesnichenko LG, Kopysov SG, Zemtzov VA, Kulizhsky SP, Vorobyev SN,
Kirpotin SN (2015) Permafrost coverage, watershed area and season control of dissolved carbon and major elements in western Siberian rivers.
Biogeosciences 12:6301–6320. https://​doi.​org/​10.​5194/​bg-​12-​6301-​2015
Pokrovsky OS, Manasypov RM, Loiko SV, Krickov IA, Kopysov SG, Kolesnichenko
LG, Vorobyev SN, Kirpotin SN (2016) Trace element transport in western
Siberian rivers across a permafrost gradient. Biogeosciences 13:1877–
1900. https://​doi.​org/​10.​5194/​bg-​13-​1877-​2016
Price NM, Ahner BA, Morel FMM (1994) The equatorial Pacific Ocean: grazercontrolled phytoplankton populations in an iron-limited ecosystem.
Limnol Oceanogr 39:520–534. https://​doi.​org/​10.​4319/​lo.​1994.​39.3.​0520
Quinton WL, Hayashi M, Carey SK (2008) Peat hydraulic conductivity in cold
regions and its relation to pore size and geometry. Hydrol Process
22:2829–2837. https://​doi.​org/​10.​1002/​hyp
Quinton WL, Hayashi M, Chasmer LE (2009) Peatland hydrology of discontinuous permafrost in the northwest territories: overview and synthesis. Can
Water Resour J 34:311–328. https://​doi.​org/​10.​4296/​cwrj3​404311
Rember RD, Trefry JH (2004) Increased concentrations of dissolved trace metals and organic carbon during snowmelt in rivers of the alaskan arctic.
Geochim Cosmochim Acta 68:477–489. https://​doi.​org/​10.​1016/​S0016-​
7037(03)​00458-7
Sarkkola S, Nieminen M, Koivusalo H, Laurén A, Kortelainen P, Mattsson T,
Palviainen M, Piirainen S, Starr M, Finér L (2013) Iron concentrations are
increasing in surface waters from forested headwater catchments ineastern Finland. Sci Total Environ 463–464:683–689. https://​doi.​org/​10.​1016/j.​scito​tenv.​2013.​06.​072
Shamov VV, Onishi T, Kulakov VV (2014) Dissolved Iron Runoff in Amur BasinRivers in the Late XX Century. Water Res 41:201–209. https://​doi.​org/​10.​1134/​S0097​80781​40201​22
Shesterkin VP, Talovskaya HM, Shesterkina HM (2013) Long-standing dynamics
of iron content and flow in the water of the middle Amur River during
the lowest winter water level. Russ J Pacific Geol 32:106–111 (In Russian)Shiraiwa T (2012) “Giant Fish-Breeding Forest”: A New Environmental System
Linking Continental Watershed with Open Water. In: Taniguchi M,
Shiraiwa T (eds) The Dilemma of Boundaries. Springer, Tokyo, pp 73–85.
https://​doi.​org/​10.​1007/​978-4-​431-​54035-9_8
Sokolova GV, Verkhoturov AL, Korolev SP (2019) Impact of deforestation on
streamflow in the amur river basin. Geosciences 9:262. https://​doi.​org/​10.​3390/​geosc​ience​s9060​262
Sorokin YI, Sorokin PY (1999) Production in the sea of Okhotsk. J Plankton Res
21:201–230. https://​doi.​org/​10.​1093/​plankt/​21.2.​201
Striegl RG, Aiken GR, Dornblaser MM, Raymond PA, Wickland KP (2005) A
decrease in discharge-normalized DOC export by the Yukon River during
summer through autumn. Geophys Res Lett 32:1–4. https://​doi.​org/​10.​1029/​2005G​L0244​13
Sunda WG (2012) Feedback interactions between trace metal nutrients andphytoplankton in the ocean. Front Microbiol 3:1–22. https://​doi.​org/​10.​3389/​fmicb.​2012.​00204
Suzuki K, Hattori-Saito A, Sekiguchi Y, Nishioka J, Shigemitsu M, Isada T, Liu
H, McKay RML (2014) Spatial variability in iron nutritional status of large
diatoms in the Sea of Okhotsk with special reference to the Amur River
discharge. Biogeosciences 11:2503–2517. https://​doi.​org/​10.​5194/​
bg-​11-​2503-​2014
Takeda S, Obata H (1995) Response of equatorial Pacific phytoplankton to
subnanomolar Fe enrichment. Mar Chem 50:219–227. https://​doi.​org/​10.​1016/​0304-​4203(95)​00037-R
Tank SE, Striegl RG, McClelland JW, Kokelj SV (2016) Multi-decadal increases indissolved organic carbon and alkalinity flux from the Mackenzie drainage
basin to the Arctic Ocean. Environ Res Lett 11:054015. https://​doi.​org/​10.​1088/​1748-​9326/​11/5/​054015
Tashiro Y, Yoh M, Shiraiwa T, Onishi T, Shesterkin V, Kim V (2020) Seasonalvariations of dissolved iron concentration in active layer and rivers inpermafrost areas. Russian Far East Water 12:2579. https://​doi.​org/​10.​3390/​
w1209​2579
Tashiro Y, Yoh M, Shesterkin VP, Shiraiwa T, Onishi T, Naito D (2023) Permafrost Wetlands Are Sources of Dissolved Iron and Dissolved Organic
Carbon to the Amur-Mid Rivers in Summer. J Geophys Res Biogeosci
128:e2023JG007481. https://​doi.​org/​10.​1029/​2023J​G0074​81
Toohey RC, Herman-Mercer NM, Schuster PF, Mutter EA, Koch JC (2016) Multidecadal increases in the Yukon River Basin of chemical fluxes as indicators

Page 13 of 13

of changing flowpaths, groundwater, and permafrost. Geophys Res Lett
43:120–130. https://​doi.​org/​10.​1002/​2016G​L0708​17
Vorobyev SN, Pokrovsky OS, Serikova S, Manasypov RM, Krickov IV, Shirokova
LS, Lim A, Kolesnichenko LG, Kirpotin SN, Karlsson J (2017) Permafrost
boundary shift in Western Siberia may not modify dissolved nutrient
concentrations in rivers. Water 9:985. https://​doi.​org/​10.​3390/​w9120​985
Vorobyev SN, Pokrovsky OS, Kolesnichenko LG, Manasypov RM, Shirokova
LS, Karlsson J, Kirpotin SN (2019) Biogeochemistry of dissolved carbon,
major, and trace elements during spring flood periods on the Ob River.
Hydrol Process 33:1579–1594. https://​doi.​org/​10.​1002/​hyp.​13424
Wang L, Yan B, Pan X, Zhu H (2012) The spatial variation and factors controllingthe concentration of total dissolved iron in rivers, Sanjiang Plain. Clean Soil Air Water 40:712–717. https://​doi.​org/​10.​1002/​clen.​20110​0251
Yan B, Guan J, Shesterkin V, Zhu H (2016) Variations of dissolved iron in the
Amur River during an extreme flood event in 2013. Chin Geogr Sci
26(5):679–686. https://​doi.​org/​10.​1007/​s11769-​016-​0828-8
Zhang G, Zeng G, Li C, Yang X (2020) Impact of PDO and AMO on interdecadal
variability in extreme high temperatures in North China over the mostrecent 40-year period. Clim Dyn 54:3003–3020. https://​doi.​org/​10.​1007/​
s00382-​020-​05155-z

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Yuto Tashiro received a Ph.D. in Agricultural Science from Tokyo
University of Agriculture and Technology in 2021. YT is a postdoctoral
researcher at the Institute for Space-Earth Environmental Research,
Nagoya University.
Tetsuya Hiyama received a Ph.D. in science from the University ofTsukuba in 1995. TH is the principal investigator of the JSPS GrantinAid for Scientific Research (KAKENHI) project entitled “Pan-Arctic
Water-Carbon Cycles (PAWCs)”.
Hironari Kanamori received a Ph.D. in science from Graduate
School of Environmental Studies, Nagoya University in 2015. HK is a
researcher at the Institute for Space-Earth Environmental Research,
Nagoya University.
Masayuki Kondo received a Ph.D. in Agricultural Science from
Hokkaido University in 2015. MK is the director of the sustainability division of the Seto Inland Sea Carbon Neutral Research Center(S-CNC) in Hiroshima University.