bioRxiv Science⌕ Search

bioRxiv · 10.64898/2026.04.20.719128

Degradation of net ecosystem carbon balance in cool-temperate forests by sika deer-induced stand structure alterations and subsequent soil erosion

Abstract

Although natural forests sequester carbon, this function may decline under chronic herbivory by abundant ungulates (hereafter overbrowsing). Specifically, overbrowsing alters stand structure, potentially impair carbon exchanges related to the vegetation. Further, overbrowsing may also accelerate soil erosion, especially in heavy-rainfall regions like Monsoon Asia. We quantified these impacts by estimating net ecosystem carbon balance (NECB; g C m-2 yr-1) by subtracting heterotrophic respiration (Rh) and lateral carbon export via erosion (Se) from net primary production (Pn) in southern Kyushu, Japan. Here, about 40-years of overbrowsing by sika deer (Cervus nippon) altered mixed broadleaf-conifer stands with presence of understory (PU) into stands with no understory (NU), then further altered into stands dominated by unpalatable shrublands (SR) or stands with canopy gaps (CG). The PU maintained a positive NECB (plot mean = 307.0 g C m-2 yr-1) because high Pn (721.9) exceeded the sum of Rh (175.4) and Se (239.5). Alteration from PU into NU converted NECB to negative (-98.2 g C m-2 yr-1). This was because the suppressed Pn (400.2 g C m-2 yr-1) could not offset the sum of Rh (170.6) and Se (327.7). Further degradation into CG caused a profound negative NECB (-894.4 g C m-2 yr-1), where Pn (71.9) offset only 7% of the sum of surging Rh (464.8) and Se (501.5). Alteration into SR showed a partially recovered NECB (97.3 g C m-2 yr-1), driven by shrub growth (Pn; 554.5, Rh; 175.4, Se; 239.5). However, this recovery is still limited given that lowered shrub biomass and prior topsoil loss via erosion. Our results validate previous findings that stand alteration from PU to SR or CG through NU leads to up to a 49% loss of ecosystem carbon stocks. Preventing stand alteration and soil erosion are key countermeasures against chronic overbrowsing and subsequent erosion. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=102 SRC="FIGDIR/small/719128v1_ufig1.gif" ALT="Figure 1"> View larger version (36K): org.highwire.dtl.DTLVardef@167aef0org.highwire.dtl.DTLVardef@e45a6org.highwire.dtl.DTLVardef@fec89borg.highwire.dtl.DTLVardef@1246bea_HPS_FORMAT_FIGEXP M_FIG C_FIG We reported that over 40 years of sika deer overbrowsing and subsequent soil erosion severely degraded the net ecosystem carbon balance (NECB) of mountain forests in Japan. The loss of understory vegetation drove the transition of intact stands into degraded states (no-understory, shrub-dominated, or canopy gaps). Based on field measurements, we quantified that this structural alteration suppressed net primary production (Pn) while increased both heterotrophic respiration (Rh) and lateral carbon loss via soil erosion (Se). Consequently, the forest shifted from a net carbon sink (+307 g C m-{superscript 2} yr-{superscript 1}) to a source (up to -894 g C m-{superscript 2} yr-{superscript 1}). These findings provide compelling empirical evidence that increasing ungulate populations, compounded by the rising frequency of heavy rainfall, may severely undermine the carbon sequestration functions traditionally expected of natural forests.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Abe, H., Fu, D., Kume, T., Katayama, A.. 2026-04-23. Degradation of net ecosystem carbon balance in cool-temperate forests by sika deer-induced stand structure alterations and subsequent soil erosion. https://doi.org/10.64898/2026.04.20.719128

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

Operationalising the context in regenerative agriculture: decision-making and farm variability

Soil degradation is a widespread challenge that requires a broad response at the individual farm level. To ensure effectivity, the practices should be tailored to the farm context: land manager objectives and farm specific challenges. These have however been difficult to quantify. Here we demonstrate that a workable farm context can be created based on a value survey, open satellite and soil data, and published models for vegetation gross primary productivity and soil erosion. Based on the findings, despite individual differences, farmers value profitability and operational efficiency, but also biodiversity and soil health. At least the regenerative farmers surveyed also value working for the greater good more than maintaining tradition or power. In spite of wide differences in farm production orientation, we also found that each farm also had a broad variation in individual fields GPP. Most fields have a stable GPP level, which is either high or low, and that there is a 2-3-fold difference between the weakest and best producing fields indicating the potential for improving GPP by improving the growing conditions on currently weak fields. In addition, soil loss was found to be highly concentrated in critical source areas, where 10% of the field area contributed to 50% of the soil loss. Overall, open data can be linked to modelling workflows to rapidly produce a decision-making context for farmers. This facilitates benchmarking and co-learning as well as enables land managers and advisors to identify the farm context for planning effective responses to soil degradation.

ecology↗

Fly, land, listen: Autonomous intermittent locomotion enables scalable low-noise drone ecoacoustic surveys

Ecoacoustic monitoring is enabling scientists and land managers to monitor and manage biodiversity more effectively and cost-efficiently in the face of human pressures and rapidly changing climates. Currently, most ecoacoustic surveys use manually deployed static sensors to record data, limiting the scale and reach of surveying efforts. Here we present a proof-of-concept autonomous drone platform that can use intermittent locomotion to conduct ecoacoustic surveys using an onboard sensor. Our custom prototype is able to fly, navigate, and avoid obstacles autonomously, land at a pre-determined location, record audio from an onboard microphone whilst static, before taking off and moving to the next sampling site. Autonomous navigation and operation enable greater sampling flexibility, reach, and scalability. Furthermore, by recording audio only whilst landed, noise from the drone's rotors does not mask signals or disturb animals, simplifying signal processing and downstream ecological analyses. We conducted trials in a scrubland habitat at the Knepp Estate in West Sussex, where our prototype demonstrated successful autonomous navigation and obstacle avoidance. Furthermore, we found that avian biodiversity data collected from the drone platform was comparable to that from traditional static acoustic sensor deployments, and that vocalisation patterns were not significantly impacted by the noise of the drone arriving or leaving a site. While scaled deployments of our technology would require further technical and regulatory challenges to be solved, our first demonstration of autonomous intermittent robotics-assisted ecoacoustic surveys lays the foundations for more cost-effective and far-reaching biodiversity surveys, with transformative potential for conservation, agricultural management, biosecurity, and more.

ecology↗

Do higher-order moments improve inference of population dynamics?

Fitting mathematical models of population dynamics to microbial time-series data allows us to estimate the ecological processes and interactions taking place in the microbiome. Repeated experiments of microbial systems yield replicates which slightly differ from each other. Some of this variability arises due to the fact that births and deaths occur at random. Most prior work focuses on fitting a deterministic mathematical model to the average across replicates. We use a stochastic model to fit the variability to the observed variability across replicates. Using a simulation-driven approach, we study the conditions under which our approach allows us to infer a larger fraction of ecological parameters correctly. We observe a substantial improvement in parameter inference. Lastly, our Bayesian approach not only allows us to incorporate prior information about the system, but also provides a distribution of parameters which conveys some idea of the uncertainty of the estimates.

ecology↗