Current sika deer effective population size is near to reaching its historically highest level in the Japanese archipelago by release from hunting rather than climate change and top predator extinction

Abstract

Deer species were repeatedly overexploited and protected for their meat and fur and they had strong impacts on ecosystems and human society by damaging crops and planted trees, altering vegetation, deer vehicle collision, and increasing ticks that vector zoonosis. To accomplish appropriate population management, the historical demography and its main driver need to be clarified. In this study, we estimated the historical demography of effective population size (Ne) of sika deer (Cervus nippon Temminck) in Hokkaido and Hyogo Prefectures of the Japanese archipelago. We estimated Ne of >100 generations from present (2020) by folded single nucleotide polymorphisms (SNP) frequency spectra and, within 100 generations from present, by linkage disequilibrium between SNP. In Hokkaido, Ne drastically increased around 3.0 ky BP and decreased around 100–150 years ago with the assumption of their generation length as 4 or 9 years. The Ne decreased by a 10th before the recent bottleneck. In Hyogo, Ne increased around 80 and 1 ky BP and decreased around 100–250 years ago. Ne decreased by a 100th before the recent bottleneck. After these recent bottlenecks, Ne of both regions recovered and the current Ne has nearly reaches the highest level of the last 100 ky BP. Literature survey and paleoclimate indicates that the decrease and increase of Ne of sika deer in Japanese archipelago may be caused by variations in the hunting activity of humans rather than climate change or the top predator extinction.

Keywords

effective population size genome-wide sequence hunting Japan RAD-seq sika deer

Introduction

Cervidae are suggested to have evolved around 20 million years ago and speciation progressed during the Pliocene and Quaternary (Chen et al., 2019). Among Cervidae, deer species have historically interacted with human. Humans hunt deer species for obtaining their meat and fur. Deer damage crops and planted trees (Gill, 1992; Walter et al., 2010) and alter plant community irreversibly (Filazzola et al., 2014; Tanentzap et al., 2012). Deer have been overexploited historically (Chen et al., 2019) and since the early 1900s (Hanberry and Hanberry, 2020; Redding, 1995). However, excessive suppression of hunting after overexploitation has caused an increase of various deer species in recent years (Côté et al., 2004; Putman and Moore, 1998; Waller and Alverson, 1997), which leads to new problems like deer vehicle collision (DeNicola and Williams, 2008) and the increase of ticks that vector zoonosis (Ostfeld et al., 2018) in addition to the damage of human products and natural vegetation. Therefore, the population management of deer species is being conducted in many countries (Apollonio et al., 2010; Kaji et al., 2022; Simard et al., 2013; Solberg et al., 1999). To accomplish the appropriate (i.e. avoiding overexploitation or overabundance) population management of deer species, the historical demography of deer species and its main driver should be clarified.

Although various methods have been developed for abundance estimation of wildlife (Iijima, 2020; Nakashima et al., 2018; Royle, 2004; Williams et al., 2002), they require real-time monitoring, which has only been carried out over a limited number of recent decades. Recent advances in genomics has made it possible to estimate the historical effective population sizes (Ne) of various wildlife including mammals, fish, and plants (Barría et al., 2019; Chen et al., 2018; Yamaura et al., 2019). Ne is a good indicator of abundance (Dudgeon and Ovenden, 2015) and the information of Ne is essential for the evaluation of population viability (Hare et al., 2011). Depending on sample size and the desirable range of estimation, various estimation methods have been developed (Beichman et al., 2018). Then, the historical Ne can be an indicator of historical demography of deer species although there have been few estimates of them (but see Ababaikeri et al., 2020).

Sika deer (Cervus nippon Temminck) expanded their distributions in recent decades in the Japanese archipelago (Figure 1). Abundant sika deer cause debarking of trees (Akashi and Nakashizuka, 1999; Iijima and Nagaike, 2015; Nagaike, 2020), the elimination or change of grassland vegetation (Otsu et al., 2019) and forest understory (Otsu et al., 2023), and the increase of ticks that vector zoonosis (Iijima et al., 2022). Population control of sika deer has been strengthened in recent years (Iijima, 2018). However, sika deer reached the Japanese archipelago around 300 ky BP (Nagata et al., 1999) and their distribution range in 12–2.4 ky BP was similar to the current distribution (Tsujino et al., 2010; Figure 1). Then, the necessity of population control and the goal of population management are controversial issues. The trajectory of Ne of sika deer in Japanese archipelago will certainly provide useful information to set the goal of population management in Japan. For example, if a plant community requires recovery from browsing, then Ne at times when the plant community was rarely affected by sika deer can be set as the population management target. However, as far as we know, evaluation of the historical demography of sika deer has never been examined.

Figure 1.

Sika deer distribution in the Japanese archipelago in recent years. The map was redrawn from the data of Ministry of Environment (https://www.env.go.jp/content/900517069.pdf).

The evaluation of historical demography of target species can lead to an understanding of the main driver of historical demography. In the case of recent demography of some deer species in Britain, for example, the increase of their forest habitat, the increase of winter crops in agriculture, a reduction in extensive livestock husbandry, the decrease of hunting pressure, the change of climate, the decrease or extinction of large predators have all been suggested as factors affecting the increase of deer species (Fuller and Gill, 2001). The historical demography of Talim red deer was shown to be affected by climate and human hunting (Ababaikeri et al., 2020). If the main driver of population size change of sika deer relates to human activity, their population control by humans is necessary to accomplish the desirable population size.

Therefore, we aimed to clarify historical demography of sika deer and its driver(s) in the Japanese archipelago by a genetic approach.

Materials and methods

Sampling of sika deer and DNA extraction

A total of 192 sika deer tissue samples collected from the two prefectures in Japan were used in this study: Hokkaido (N = 96) from 1991 to 1996 and Hyogo (N = 96) in 2020 (Figure 2). We define 2020 as “present year” in this study. We sampled to cover almost all the entire sika deer distribution of the two prefectures. Tissue samples were frozen at −20°C or preserved in 99.9% ethanol until DNA extraction. Genomic DNA was extracted using QIAamp DNA Mini Kit (QIAGEN, Hilden, Germany) following the manufacture’s protocol for the phenol-chloroform method (Sambrook et al., 1989).

Figure 2.

Sampling locations of sika deer. Black circles indicate each sampling location.

Genotyping

A total 192 individuals were used in the double digest restriction-site-associated (ddRAD) experiment (Peterson et al., 2012). Briefly, each sample (250 ng DNA) was digested with SphI-HF (10 units per reaction, New England Biolabs Inc., Beverly, MA, USA) and EcoRI-HF (10 units per reaction, New England Biolabs Inc., Beverly, MA, USA), ligated with Y-shaped adaptors, amplified by PCR with KAPA HiFi polymerase (KAPA BIOSYSTEMS). After PCR amplification with adapter specific primer pairs (Access Array Barcode Library for Illumina, Fluidigm), an equal amount of DNA from each sample was mixed and size-selected with the BluePippin agarose gel (Sage Science, Beverly, MA, USA). Approximately 450 bp library fragments were retrieved. Further details of the library preparation method was described in our previous study (Nagamitsu et al., 2020). The quality of the library was checked by the 2100 Bioanalyzer with a high sensitivity DNA chip (Agilent technologies, Waldbronn, Germany), and finally sequenced using an Illumina Hi-Seq X to generate paired-end reads with a 150 bp length. The raw sequence data are available in the DDBJ Sequence Read Archive (https://www.ddbj.nig.ac.jp/dra/index-e.html) under accession number DRR414875-DRR415045.

Mapping and SNP calling

The raw reads were cleaned by removing adapter sequences and low-quality sequences (the amount of reads was lower than 30 MB per individual). Clean reads were aligned on the reference genome of Cervus elaphus hippelaphus (CerEla1.0) (Bana et al., 2018) using bwa (ver. 0.7.17) (Li and Durbin, 2009). An average of 75.1% of clean reads were properly aligned with a mean depth of 44.7-fold. We removed the reads aligned on sex chromosomes and repeat regions. Single nucleotide polymorphisms (SNPs) were identified for each population using stacks (ver. 2.53) (Catchen et al., 2013). Finally, SNPs with a minor allele frequency (MAF) above 0.05 across all samples were found in more than 75% of individuals for each population and were retained for subsequent analysis. After removing samples with missing data on more than 75% of total SNPs, we again identified SNPs in each population using stacks.

Estimation of Ne

Although various ways of estimating Ne exist, the estimable timing and range of generation differ among methods (Nadachowska-Brzyska et al., 2022). We used Stairway plot2 (Liu and Fu, 2020) to estimate Ne >100 generations before present and GONE (Santiago et al., 2020) to estimate it within 100 generations before present.

For the estimation of Ne >100 generations by Stairway plot2, the mutation rate was set as 1.584 × 10⁻⁸ per site per generation (Chen et al., 2019). There are many methods to estimate generation length (hereafter, GL) and survival and reproduction data are necessary to apply these methods (Cooke et al., 2018). We have the age-specific survival rates and fecundity rates only in Hokkaido (Uno and Kaji, 2006). Based on the data of Uno and Kaji (2006), we estimated the GL of sika deer as nine by the life-table method (Cooke et al., 2018). In addition to it, Goodman et al. (1999) suggested as GL = 4 for sika deer. The difference of these GLs was 5. To consider the uncertainty about GL, we applied another GL (14) in addition to 4 and 9 for the conversion of generations to actual years.

Recent demography was inferred based on linkage disequilibrium between SNPs. For this analysis, we selected SNPs that were aligned on the 33 autosomal chromosomes and were shared among more than 15% of samples in each population (Table 1). Linkage disequilibrium was calculated using PLINK (ver. 1.9) (Chang et al., 2015) and Ne in the recent 100 generations were inferred using GONE assuming a constant recombination rate of 1 cM/Mb (Santiago et al., 2020).

Table 1.

Summary of the genetic dataset.

	Hokkaido	Hyogo
Stairway plot2
Num. samples*	75	72
GONE
Num. polymorphic sites on the 33 autosomal chromosomes	36,161	46,895

The sample numbers were lower than those of collected samples (i.e. 96) because of the quality of DNA (see Materials and Methods for details).

In this study, we are interested in the historical demography of Ne, not the absolute Ne. Therefore, we calculated Ne relative to Ne 100 generation ago because the boundary of estimable range of GONE and Stairway plot2 was 100 generation ago as stated above. Genetic diversity of Hokkaido and Hyogo populations are available in Supplemental Table S1, available online.

Paleoclimate

Among various climate conditions, temperature, and precipitation are expected to affect the historical demography of sika deer because temperature affect the amount of snow that are suggested to affect deer survival (Ohashi et al., 2016; Takatsuki, 1992) and precipitation affect the amount of vegetation. We obtained the annual mean temperature (Bio01) and annual precipitation (Bio12) from Beyer et al. (2020) by using R package pastclim (Leonardi et al., 2023).

Results

In Hokkaido, although the timing of increase or decrease of Ne differed depending on the assumption of GL, the historical trend of Ne did not differ irrespective of the assumption of GL (Figure 3). The Ne of sika deer in Hokkaido gradually decreased from 100 to 3 ky BP and increased from 3 to 2 ky BP (Figure 3). It again decreased in 100 (GL = 4), 150 (GL = 9), or 250 years (GL = 14) before present, respectively. By the recent bottleneck, Ne decreased to a 10th of its value before the bottleneck (Figure 3). Ne in Hokkaido recovered from the recent bottleneck and reached its highest level during the estimation period, with the exception of 2–0.4 (GL = 4), 2–0.9 (GL = 9), or 2–1.7 (GL = 13) ky BP, when it was a little less (Figure 3). Mean observed heterozygosity and mean gene diversity were 0.1968 and 0.2059, respectively (Supplemental Table S1, available online).

Figure 3.

Estimated effective population size of sika deer in Hokkaido. GL is generation length. Left panels were estimated by GONE and right panels were estimated by Stairway plot2. We calculated effective population size relative to the effective population size 100 generation ago because the boundary of estimable range of GONE and Stairway plot2 was 100 generation ago. Gray polygons in right panels indicate 95% confidence interval.

In Hyogo, there were two increases of Ne of sika deer, at 80 and 1.1 ky BP (GL = 4 and 9) and a decrease in 100 (GL = 4), 250 (GL = 9), or 300 years (GL = 14) before present (Figure 4). By the recent bottleneck, Ne decreased to 110th of its value before the bottleneck (Figure 4). Current Ne in Hyogo recovered from the bottleneck and reached the highest level during the estimation period (Figure 4). Mean observed heterozygosity and mean gene diversity were 0.2903 and 0.3135, respectively (Supplemental Table S1, available online).

Figure 4.

Estimated effective population size of sika deer in Hyogo. GL is generation length. Left panels were estimated by GONE and right panels were estimated by Stairway plot2. We calculated effective population size relative to the effective population size 100 generation ago because the boundary of estimable range of GONE and Stairway plot2 was 100 generation ago. Gray polygons in right panels indicate 95% confidence interval.

Temperature in Hokkaido and Hyogo greatly fluctuated and was much colder during 60–20 ky BP than present (Figure 5). After 20 ky BP, temperature of both regions gradually increased and reached the same degree of present in 5 ky BP (Figure 5). Precipitation in Hokkaido was relatively stable but increased from 20 ky BP (Figure 5). Precipitation in Hyogo was relatively stable until 12 ky BP but fluctuated after that (Figure 5).

Figure 5.

Annual mean temperature and annual precipitation of Hokkaido and Hyogo. These climate data were obtained from Beyer et al. (2020) via R package pastclim (Leonardi et al., 2023). The square and circle symbols of left edge in each figure indicates the temperature (upper figure) or precipitation (lower figure) of Hokkaido and Hyogo at present.

Discussion

Although the expansion of sika deer in Japan is obvious and the population management of them is an urgent issue (Kaji et al., 2022), there is no goal of population management based on scientific evidence in Japan. Our estimates of Ne have revealed the historical demography of sika deer in the Japanese archipelago over the past 100 ky BP. Among the possible factors for the increase of deer population (the increase of their forest habitat, the increase of winter crops in agriculture, a reduction in extensive livestock husbandry, the decrease of hunting pressure, the change of climate, the decrease or extinction of large predators; Fuller and Gill, 2001), hunting activity may be an important driver of Ne of sika deer in Japanese archipelago.

It is well known that overexploitation of sika deer occurred in Hokkaido and main island of Japanese archipelago in the Meiji period (1868–1912). Although citizens were not be permitted to use guns until then, the restriction was repealed at the beginning of Meiji period, which increased hunting pressure (Inukai, 1952; Table 2). Furthermore, multiple wars, including the Russo-Japanese War (1904–1905) and World War I (1914–1918) also increased the demand for fur from animals, caused the decrease of Ne of sika deer. These recent overexploitations seemed to be well illustrated by the demography of Ne in the case of GL = 4 or 9 (see Supplemental Figures S1 and S2, available online for the demography of Ne of GL = 5–8 of Hokkaido and Hyogo). Previous study based on mitochondrial DNA haplotypes (Nabata et al., 2004) have revealed three haplotypes in Japanese deer remains excavated from archeological sites in Hokkaido that existed from the 17th to 19th centuries that are not present in extant Japanese deer. Nabata et al. (2004) indicates that genetic diversity has decreased due to population bottlenecks over the past 100 years. This supports the finding of this study that Ne has been significantly reduced around the past 100 years (GL = 4) in Hokkaido (Figure 3). Furthermore, Goodman et al. (2001) suggested that while there may have been a dramatic decline in population size in Hokkaido at the end of the 19th century (GL = 9) that occurred in Ne in the past 150 years, the potential bottleneck in Hokkaido may not have been as severe as contemporary observations suggest. This may be manifested in the apparently smaller degree of decline in Ne in Hokkaido when looking at GL = 4 and 9 for Hokkaido and Hyogo in Figures 3 and 4 of this study. Because sika deer were suggested to be reach southern Japan from Korean peninsula via land bridges in the glacial period (Nagata, 2009), the genetic diversity of Hokkaido was lower than that of Hyogo (Supplemental Table S1, available online). Then, the indigenous low genetic diversity of Hokkaido population caused the smaller decline of Ne in Hokkaido. Subsequently, Japanese government and prefectures strictly prohibited the hunting of sika deer (Table 2), which resulted in their recent population recovery (Figure 1) that correspond with the estimated Ne in recent years (Figures 3 and 4).

Table 2.

Population management history of sika deer in recent years.

AD	y BP*	Hokkaido	Hyogo
2020	0
2010	10
2000	20	Maximum hunting quota of female deer per day was removed (2004)²	Maximum hunting quota of female deer per day: two in 2003, unlimited in 2009³
1990	30	Maximum hunting quota per day increased to two individuals (1998)¹
		Introduction of the “management plan” system (1999)¹
		Conditional release of female deer hunting (1994)¹
1980	40
1970	50	Setting maximum hunting quota of deer per day: one individual (1978)¹
1960	60
1950	70
1940	80	Prohibition of female deer hunting (1948)¹
1930	90
1920	100
1910	110
1900	120	Deer hunting permitted (1901)¹
1890	130	Prohibition of deer hunting (1890)¹
1880	140
1870	150	Partial prohibition of deer hunting (1878)¹
1860	160	Gun use for citizens permitted¹

Years before present (2020).

¹ https://www.env.go.jp/nature/choju/plan/plan3-2e/chpt2.pdf

² https://www.pref.hokkaido.lg.jp/fs/5/6/9/5/3/7/7/_/03-1%20北海道エゾシカ管理計画(第6期)_本文.pdf

³ https://web.pref.hyogo.lg.jp/press/documents/20220425_10122_12.pdf

Sika deer was suggested as a major food for humans in Hokkaido during the upper Paleolithic (ca. 22–20.5 ky BP) (Sawada et al., 2014) and in the early Jomon period (ca. 6.5–5 ky BP) (Bleed et al., 1989). However, localized cultivation in Hokkaido occurred during Epi Jomon period (2.3–1.3 ky BP) (Abe et al., 2016). Intense hunting and its relaxation might have contributed to the decrease of sika deer around 3 ky BP and the later increase in Hokkaido (Figure 3 and Table 3). In Honshu Island, including Hyogo Prefecture, sika deer is suggested as the main food for Japanese people during the Jomon period (15–3 ky BP) (Bleed and Matsui, 2010). However, the spread of cultivation during the Yayoi period (3 –1.7 ky BP; Jinam et al., 2021) decreased the dependence on bush meat as a food source. At the same time, fire disturbance increased around Kyoto, which is adjacent to Hyogo (Sasaki and Takahara, 2011) and might have increased the occurrence of herbaceous grasses, the preferred food for sika deer (Iijima and Otsu, 2018).

Table 3.

Historical human activity.

y BP*	Human activity
y BP*	Hokkaido	Hyogo
0
1000
2000	Spread of cultivation^3,5
3000		Sika deer as main food⁴
4000
5000	Sika deer as main food²
6000	Sika deer as main food²
7000
8000
9000
10,000
20,000	Sika deer as main food¹
30,000
40,000
50,000
60,000
70,000
80,000
90,000
100,000

Years before present (2020).

¹Sawada et al. (2014).

²Bleed et al. (1989).

³Abe et al. (2016).

⁴Bleed and Matsui (2010).

⁵Jinam et al. (2021).

Our results indicated that climate change cannot explain the dynamics of Ne. The Japanese archipelago was in last glacial period between 100 and 10 ky BP and the temperature drastically increased after that and reached the similar degree of present at 5 ky BP (Figure 5). Precipitation in Hokkaido was relative stable and that in Hyogo fluctuated after 2 ky BP (Figure 5). Despite the large uncertainty in the estimation of the trajectory of Ne and paleoclimate, no obvious increase or decrease of temperature and precipitation (Figure 5) occurred when Ne in Hokkaido (Figure 3) and Hyogo (Figure 4) drastically increased. Our result also indicated that the predation by Japanese wolf (Canis lupus hodophilax) cannot explain the dynamics of Ne. The extinction of the Japanese wolves in Hokkaido and Honshu is considered to have occurred in the early 1900s (Inukai, 1932; Knight, 1997). However, the Ne of sika deer in Hokkaido and Hyogo greatly fluctuated before the wolf extinction, and Ne at 2–0.4 ky BP (GL = 4) in Hokkaido and at 0.4–0.15 ky BP (GL = 4) in Hyogo were similar or slightly higher than those at present year in the Japanese archipelago (Figures 3 and 4). As already shown in other regions (Vucetich and Peterson, 2004), no obvious effect of predation by wolves on the population dynamics of sika deer was observed. Because Ne of sika deer is mainly affected by human activity in Japanese archipelago, the population management of sika deer is necessary to manage current impacts by sika deer. Although the evaluation of historical demography by Ne has rarely been applied to deer species, we have demonstrated the potential of a knowledge of Ne in the setting of goals for their population management of deer species.

Supplemental Material

sj-docx-1-hol-10.1177_09596836231157063 – Supplemental material for Current sika deer effective population size is near to reaching its historically highest level in the Japanese archipelago by release from hunting rather than climate change and top predator extinction

Supplemental material, sj-docx-1-hol-10.1177_09596836231157063 for Current sika deer effective population size is near to reaching its historically highest level in the Japanese archipelago by release from hunting rather than climate change and top predator extinction by Hayato Iijima, Junco Nagata, Ayako Izuno, Kentaro Uchiyama, Nobuhiro Akashi, Daisuke Fujiki and Takeo Kuriyama in The Holocene

Footnotes

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Our work was supported by JSPS KAKENHI (grant number: 21H02247).

ORCID iDs

Hayato Iijima

Nobuhiro Akashi

Supplemental material

Supplemental material for this article is available online.

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