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Article

Changes in Forest Hydrology and Biogeochemistry Following a Simulated Tree Mortality Event of Southern Pine Beetle: A Case Study

by
Courtney M. Siegert
1,*,
Heidi J. Renninger
1,
Nicole J. Hornslein
1,2,
Padmanava Dash
3,
John J. Riggins
4 and
Natalie A. Clay
5
1
Department of Forestry, Mississippi State University, Mississippi State, MS 39762, USA
2
Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder, Boulder, CO 80309, USA
3
Department of Geosciences, Mississippi State University, Mississippi State, MS 39762, USA
4
Department of Forest Engineering, Resources & Management, Oregon State University, Corvallis, OR 97331, USA
5
Department of Entomology & Plant Pathology, University of Arkansas, Fayetteville, AR 72701, USA
*
Author to whom correspondence should be addressed.
Forests 2026, 17(2), 211; https://doi.org/10.3390/f17020211
Submission received: 12 December 2025 / Revised: 29 January 2026 / Accepted: 2 February 2026 / Published: 4 February 2026
(This article belongs to the Special Issue Effects of Disturbance on Forest Hydrology)
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Abstract

Southern pine beetle infestations impact ecosystems throughout the southeastern US. Our understanding of hydrologic and biogeochemical impacts on ecosystem structure and function is largely guided by severe outbreaks occurring in the western US. A simulated mortality experiment was conducted on loblolly pine trees via girdling with and without blue-stain fungi inoculation to mimic a small-scale infestation. We measured whole-tree water use, canopy-derived hydrologic and biogeochemical fluxes, soil moisture, and soil respiration for two years following treatments to quantify the impacts of tree mortality on water, carbon, and nitrogen cycles. In the second year of our study, a significant drought occurred, subjecting study trees to a secondary stressor. We found that compared to control trees, girdled trees exhibited reduced water uptake within 6 months and succumbed to mortality within 18 months. We found that by the time trees reached the gray phase of attack, stemflow was 1.7-times lower in girdled trees compared to control trees. Stemflow from girdled trees had up to 7.2-times higher concentrations of ammonium and 2.8-times higher concentrations of total nitrogen. Although stemflow carbon concentrations were indistinguishable between treatments, total carbon flux in stemflow was 2.0-times greater in non-girdled trees (p = 0.030). Finally, even though soil moisture and respiration were not different between treatments, it was not possible to isolate the response of these to mortality versus drought. Our results present the connection between bark beetle outbreaks and the initial impacts on forest biogeochemistry. Changes in the distribution of canopy-derived water inputs, coupled with altered carbon and nitrogen fluxes, serve as hot spots around bark beetle-killed trees. Further research is necessary to understand whether these isolated hot spots may prime the system, alter microbial and invertebrate communities, and lead to changes in decomposition processes at larger scales.

1. Introduction

Widespread tree mortality from insect outbreaks in forested ecosystems are common disturbance event in many parts of the world [1,2,3,4]. Bark beetle infestations occur in forests globally and result in a predictable sequence of mortality, first undergoing the “green-attack” phase, where the trees are infested but still maintain green needles, then the “red-attack” phase, where needle death occurs, followed by the “gray-attack” phase, where needles drop and leave a bare canopy [5]. These phases have differing impacts on forest hydrological and soil biogeochemical processes [6]. For example, Bearup et al. [7] showed that a decline in transpiration following a bark beetle outbreak in the western US led to a 30% increase in groundwater recharge. In contrast, Edburg et al. [5] proposed a framework in which more open forests following mortality would lead to a smaller snow pack and degraded water quality. Understanding both of these outcomes is critical, as bark beetle impacts on water resources determine forest management strategies [8,9,10]. Much of what we know about how bark beetle outbreaks impact forest ecology is derived from the western US and northern Europe. However, in western and northern forest ecosystems, vegetation dynamics that govern regeneration and forest recovery are slower processes compared to eastern US forests, so ecosystem responses may differ among regions. Although the southeastern US has large expanses of pine forests and plantations that are regularly attacked by pine beetles [11,12,13], we understand very little about the ecological consequences of bark beetle attacks in this region.
In the southeastern US, the southern pine beetle (Dendroctonus frontalis Zimm.) is a native bark beetle that attacks many species of southern pine, with the most common being loblolly pine (Pinus taeda L.) due to the species’ widespread use in plantation forestry. Southern pine beetles are one of the most aggressive bark beetles, and are capable of killing a vast number of trees quickly [11,12,14]. Tree death may be accelerated via ophiostomatoid fungi, which are vectored by the southern pine beetle [15,16]. These fungi, commonly referred to as “blue-stain” fungi due to the discoloration the fungi cause to wood [15], colonize the vascular system and restrict plant water uptake, hastening tree mortality [17,18]. Additionally, subterranean termites are often preferentially attracted to wood inhabited by blue-stain fungi [19,20,21]. Together, these processes may lead to faster decomposition rates and nutrient cycling in southeastern US forests attacked by bark beetles [22,23].
Southern pine beetle outbreaks across the southeastern US can cause more than $100 million in timber losses, damaging more than one billion cubic feet of valuable timber [24,25]. While much attention has been given to forest management and outbreak reduction/mitigation [26,27,28,29], less has been given towards changes in the ecological structure and function of these impacted forests [2,30,31,32], especially in the southeastern US [22]. In healthy and well-managed forests, southern pine beetles attack and kill trees at endemic population levels that result in consistent low-density tree mortality [26,33]. However, the ecological, hydrological, and biogeochemical impacts of endemic bark beetle tree mortality are far less understood.
Bark-beetle-attacked forests undergo changes that impact biogeochemical cycling. Bark beetle disturbance leads to large influxes of fresh needles to the forest floor, which is coupled with fine root mortality and turnover [34,35,36]. These serve as sources of mobile carbon and nitrogen that can accelerate mineralization and increase the availability of these key nutrients [35,37]. Moreover, rates of plant uptake of nitrogen and base cations decline with tree mortality, ultimately resulting in greater availability of these nutrients in soil [38]. Despite our growing understanding of belowground responses to bark-beetle-caused tree mortality [6], far less is known about how mortality impacts the biogeochemistry of canopy-derived pathways, particularly stemflow, which serves as a highly localized input of water and nutrients to individual trees, and throughfall, which serves as a more dispersed input.
Bark-beetle-attacked forests undergo changes in forest structure that impact hydrologic cycling through changes in aboveground biomass, leaf area, and canopy structure during tree mortality. For example, throughfall, as a hydrologic input, scales with the leaf area index [39]. Consequently, as foliage dies, the capacity of tree crowns to intercept rainwater decreases, leading to an increase in throughfall. Increased throughfall may lead to greater moisture availability in soils for vegetation and microbial communities, but the reduction in crown area may also increase net radiation and evaporation [40,41]. Another hydrological change caused by tree mortality is in the quantity and quality of stemflow. The ecological significance of stemflow is often overlooked [42,43,44,45] as it is generally less than 5% of the volumetric input at the watershed scale [46,47]. However, stemflow can contribute a large proportion of the nutrient flux to forest soils, which is deposited directly around tree boles and individual root systems [48,49,50]. In particular, stemflow has been shown to increase in the dormant season when deciduous trees are defoliated, and more of the stem is exposed to direct precipitation [51,52,53]. This same process may occur in bark-beetle-killed forests, as needles die and drop to the forest floor. Changes in hydrologic processes such as these can have large impacts on forest ecosystem function in bark beetle outbreak areas, but there is a notable knowledge gap in this area.
Given the extent of loblolly pine silviculture in the southeastern US and the potential impact of southern pine beetle on this ecosystem and associated industry, the paucity of studies in the region connecting insect disturbance and changes to ecohydrologic and biogeochemical cycles is striking. As such, the objective of this study was to quantify changes in hydrologic and biogeochemical cycles from trees undergoing mortality in a simulated bark beetle attack in the southeastern US. We hypothesized that simulated bark-beetle-killed trees would create biogeochemical hotspots near their trunk as they undergo mortality due to (1) increased soil moisture from reductions in plant water uptake and increased stemflow production and (2) enhanced canopy-derived inputs of carbon and nitrogen. Outcomes of this study will better inform our understanding of hydrology and biogeochemical processes following bark beetle outbreaks in the southeastern US. This knowledge can be used to refine models for water resource management, to understand the role of bark beetles in carbon and nutrient cycles, and to provide empirical evidence to support forest management activities following outbreaks, all of which are notably lacking in the southeastern US.

2. Materials and Methods

2.1. Study Site

The study was conducted in a 60-year-old loblolly pine stand in central Mississippi (33.2639° N, 88.8884° W). The overstory basal area (trees with diameter at breast height; DBH) was 21.1 m2 ha−1 with 130 trees ha−1 dominated by loblolly pine. The midstory had a basal area of 11.8 m2 ha−1 with 1664 trees ha−1 dominated by sweetgum (Liquidambar styraciflua L.), red maple (Acer rubrum L.), winged elm (Ulmus alata Michx.), and oak species (Quercus spp.). The soil on this site is classified as somewhat poorly drained Urbo silt loam with slow permeability found on nearly level landscapes around streams that drain uplands in the Southern Coastal Plain physiographic region [54]. Average temperatures in summer (June, July, and August) and winter (December, January, and February) are 27.1 °C and 7.6 °C, respectively (30-year mean 1990–2020; [55]). Total annual rainfall is 1473 mm, which falls fairly evenly throughout the year [55]. During the study period, particularly from Summer 2016 to Winter 2017, an extreme drought (level D3 on 15 November 2016; [56]) was observed throughout the southeastern US, resulting in significant reductions in rainfall (Figure 1).

2.2. Study Design and Treatments

A field study was established in the summer of 2015 to simulate a bark beetle attack and mortality event by girdling loblolly pine trees to sever phloem and cambium tissue [57] (Figure 2). Fifteen canopy-dominant loblolly pine trees were selected around a centrally located data logger and randomly allocated to three different treatments: (1) five trees were girdled and received inoculations of blue-stain fungus (Ophiostoma minus (Hedgc.) Syd. & P. Syd.), (2) five trees were girdled and inoculated with agar as negative controls, and (3) five trees were not girdled and received no inoculations as controls (see Figure 1a,b for site layout and Figure 1c for girdling treatment illustration in Siegert et al. [58],). Fungal inoculations were implemented to further assess the role blue-stain fungi play in controlling rates of tree mortality. Cell stock of previously identified cultures of O. minus was available from prior studies (see [19,20,21]) for use in this study. Pure strains of the fungus were cultured on malt extract agar. Once the fungi were vigorously growing, three 0.5 cm diameter plugs were taken from each Petri dish and were inoculated into the sapwood of the trees using an arch punch just above the girdling. Between trees, tools were flame sterilized to avoid cross-contamination.

2.3. Sapflow Measurements

On all 15 study trees, 2 cm long sapflow probes were installed to measure tree water use following the heat dissipation method [59], which estimates sapflow rates from the temperature deficit between an upper heated and lower reference probe, as described in Hornslein et al. [60]. Sapflow probes were installed radially into the outermost sapwood tissue, positioned above the stem girdle and approximately 1 m above ground level. Probes were covered by reflective insulation and connected to a CR1000 datalogger and AM16/32B multiplexer (Campbell Scientific Inc., Logan, UT, USA) powered by deep-cycle batteries and a solar panel located in a nearby canopy gap. Measurements were recorded every 30 s and averaged over 30 min increments. These raw millivolt temperature data were imported into the BaseLiner software program version 3.0.8 (Duke University, Durham, NC, USA) to calculate sapflow velocities (g m−2 sapwood area s−1) based on the empirical equation developed by [59]. To scale measurements to the tree level, sapwood depths were calculated from DBH measurements and an allometric equation from Blanche et al. [61]. In addition, radial decreases in sapflow velocity with depth were accounted for using data from Ford et al. [62]. Sapflow was monitored in trees until the cessation of flow in girdled trees in late 2016.

2.4. Stemflow, Throughfall, and Precipitation Quantity and Quality

All 15 focal trees were outfitted with stemflow collars constructed from 2.5 cm inner diameter polyethylene tubing cut longitudinally and placed around the trunk of each tree above the girdled location, sapflow probes, and an inoculation site (see Figure 1c in Siegert et al. [58] for stemflow collar illustration). Stemflow collars were sealed around the tree trunk with silicone caulk and held in place with aluminum nails. Collars drained into 20 L polyethylene bins. Because trees designated for girdling were randomly selected from the 15 focal trees, there was limited ability to isolate the effect of girdling on throughfall. Therefore, throughfall samples were not utilized to isolate the effects of girdling, but instead served as net measurements of stand-level changes in throughfall quantity and quality. As such, net throughfall was measured with five 1 L polyethylene containers fitted with 20.3 cm diameter funnels. Open precipitation was measured with 1 L polyethylene containers fitted with 20.3 cm diameter funnels placed in a clearing 250 m south of the study plot. Stemflow and throughfall volume were measured directly from the sample collectors. Precipitation quantity was measured with a tipping bucket rain gauge (RG3-M, Onset, Inc., Bourne, MA, USA), located adjacent to the open precipitation collector. Water samples for chemical analysis were collected from open precipitation, stemflow, and throughfall containers within 24 h of the end of a storm event. Water samples were filtered through a 0.45 μm membrane and stored at 4 °C until chemical analysis. Sample collection began in fall 2015 and continued through fall 2017. The data presented herein build upon preliminary data reported by Siegert et al. [58].
Water samples from stemflow, throughfall, and rainfall were analyzed for carbon and nitrogen. Dissolved organic carbon (DOC) was analyzed on a DR5000 UV-Vis Spectrophotometer (Hach Company, Loveland, CO, USA) with the Low-Range Total Organic Carbon Test kit (Hach Company, Loveland, CO, USA). Colored dissolved organic matter (CDOM) absorbance was measured using a Lambda 850 UV-Vis Spectrophotometer (PerkinElmer, Waltham, MA, USA). After ultrapure water correction and a correction for baseline fluctuations of the absorbance spectra, the absorption coefficient (a254), a metric that describes the aromaticity of DOM, was calculated by
a 254 = 2.303 × A ( λ ) l
where A ( λ ) = the absorbance at 254 nm, l = the cell path length of the instrument, set to 0.01 m [63]. The specific UV absorbance (SUVA) describes compound aromaticity and was standardized for the concentration of DOC in the sample by
S U V A 254 = a 254 [ D O C ]
where [DOC] = the concentration of dissolved organic carbon in the sample [64].
Dissolved nitrogen species [total nitrogen (TN), organic nitrogen (ON), nitrate ( N O 3 − –N), and ammonium ( N H 4 + –N)] were analyzed on a Bran+Luebbe Auto Analyzer 3 (SEAL Analytical, Mequon, WI, USA). N O 3 − –N was determined using cadmium reduction methods. N H 4 + –N was determined using phenate methods. TN was determined using microwave digestion in which all ON forms of nitrogen are converted to N O 3 − –N, then analyzed using cadmium reduction methods. ON was calculated as
O N = T N − N O 3 − 1 + N H 4 + 3
All laboratory methods followed QA/QC protocols, including standards, blanks, and duplicate testing.

2.5. Soil Moisture and Respiration

Soil moisture and respiration were measured around each of the 15 individual trees, beginning in spring 2016. A circular grid with concentric rings of three 0.5 m intervals split into six sample quadrants was established around each tree for soil sampling and respiration measurements. To isolate the soil for respiration, a 20 cm inner diameter polyvinyl chloride (PVC) pipe cut to a length of 10 cm was installed permanently into the soil profile at the center point of each of the three concentric distance quadrants. Installation locations were randomly generated, but these locations remained fixed throughout the study to limit disturbance of the soil and root profile. Each tree had a total of three respiration collars randomly located around the tree base: one at a distance of 0.5 m, one at a distance of 1.0 m, and one at a distance of 1.5 m (see Figure 1c in Siegert et al. [58] for respiration collar placement). Respiration was measured monthly with a LI8100A Soil Automated Flux Analyzer (Li-Cor, Inc., Lincoln, NE, USA) outfitted with a 20 cm survey chamber along with a volumetric water content sensor (ECH2O model EC-5, Decagon Devices, Inc., Pullman, WA, USA) and soil temperature thermistor probe (Li-Cor, Inc., Lincoln, NE, USA). Respiration data were adjusted based on the average measured depth of each PVC collar.

2.6. Data Analysis and Statistics

All measurements were aggregated to the seasonal scale (Fall: September–November; Winter: December–February; Spring: March–May; Summer: June–August) to provide a common baseline comparison across continuous measurements (sapflow), discrete event-level measurements (stemflow, throughfall, and precipitation), and discrete seasonal measurements (soil moisture and respiration).
We evaluated treatment differences over time using a linear mixed-effects model that accounted for the repeated measurements of response variables in the data. For each response variable (e.g., sapflow, soil moisture, stemflow, throughfall, soil respiration), we fit a mixed model with girdling treatment (girdled vs. control), season, and their interaction (treatment × season) as fixed effects and individual tree as the random effect that was repeatedly sampled. Mixed-effects modeling was conducted using the ‘lmer’ function in the lme4 package [65] in R statistical software, version 4.4.2 [66]. Differences between treatment groups and season were then evaluated using estimated marginal means with the ‘emmeans’ function in the emmeans package [67]. Model-adjusted means and standard errors are reported in summary tables.

3. Results

Two years following a simulated bark beetle attack, all girdled trees had shed their needles and died. Four of the five control trees were healthy and had fully foliated canopies, while one of the control trees succumbed to mortality for unknown and unidentifiable reasons. For this reason, this tree was omitted from further analysis.

3.1. Plant Water Uptake, Canopy-Derived Hydrologic Inputs, and Soil Moisture

Throughout the study, sapflow data indicated no differences between trees inoculated with blue-stain fungi versus those inoculated with agar as controls, leading us to assume that the blue-stain inoculations were either unsuccessful or did not affect tree water use and the mortality process (see [60] for further details and statistical analyses). Therefore, the results presented here separate the treatments into control (i.e., non-girdled) and girdled.
Sapflow rates were not statistically different between control and girdled pines during the growing season immediately following the girdling treatment (Summer and Fall 2015). Girdled pines began to exhibit significantly lower sapflow rates in December of 2015 and maintained lower sapflow for the remainder of the study (p < 0.050, Figure 3). By the end of the second growing season following girdling, all girdled trees ceased sapflow and measurements were no longer recorded [60].
Throughout the study, 30 storm events were sampled. Stemflow production remained largely unchanged between treatments through the first year and a half of the study, with the exception of minor differences observed in Winter 2016, when control trees had 1.6-times more stemflow than girdled trees (318 L m−2 vs. 194 L m−2, p = 0.029) (Figure 4). Then, in Spring 2017, with the onset of the gray phase, differences in stemflow volumetric flux increased and remained consistent for the remainder of the study period, with control trees generating ~50% more stemflow than girdled trees (p < 0.050). Over the entire study, control trees generated 1.7-times more stemflow than girdled trees (1563 ± 260 L m−2 vs. 930 ± 134 L m−2; p < 0.001).
Soil volumetric water content was slightly higher in soils surrounding girdled trees than around control trees (0.268 ± 0.007 vs. 0.246 ± 0.012, p < 0.001). Across all sampling periods, soil volumetric water content was not different among the three different distances from the tree bole (p = 0.421). When evaluated within each season, soils around control trees were generally drier than average, while soils around girdled trees were generally wetter than average (Figure 5). However, it was not until late in the gray phase in Fall 2017 that soils around girdled trees were significantly wetter than soils around control trees. In particular, soils closest to tree boles (0.5 m distance) around girdled trees were 14% wetter (0.272 ± 0.012 vs. 0.232 ± 0.020, p = 0.021) while there were still no differences in soil moisture between treatments farther away from tree boles (1.0 m: p = 0.437; 1.5 m: p = 0.099) (Figure 5).

3.2. Canopy-Derived Biogeochemical Inputs and Soil Respiration

Stemflow dissolved organic carbon concentrations were 9.5-times higher than rainfall and 2.7-times higher than throughfall (Table 1). However, there was no significant difference in stemflow DOC between healthy trees and girdled trees throughout any period of measurement in the study (Figure 6A). The quality of dissolved carbon was also different in hydrologic pathways. SUVA values were approximately 2.6-times greater in both throughfall and stemflow compared to rainfall, indicating higher aromaticity (Table 1). However, there were no differences in SUVA in stemflow between control and girdled trees throughout the study (Figure 6B).
Nitrogen concentrations in stemflow and throughfall when pooled across time were not statistically different than rainfall in this study (Table 1). However, differences in stemflow nitrogen concentrations were observed between girdled and control trees once the trees entered the gray phase (Figure 7). This was largely driven by differences in N H 4 + –N concentrations that led to differences in total nitrogen flux. In particular, by the gray phase, N H 4 + –N and TN concentrations of stemflow collected in this phase were 2.4–7.2-times and 2.3–2.8-times higher in stemflow from girdled trees compared to control trees, respectively (Figure 7B,D). N O 3 − –N concentrations were also 10.1-times higher in stemflow from girdled trees compared to control trees by the end of the study (Figure 7A). No differences in organic nitrogen concentrations were observed in stemflow across treatments at any point in the study (Figure 7C). Interestingly, organic nitrogen concentrations across all hydrologic pathways, including throughfall and stemflow, exhibited a modest increase (p = 0.066) following the prolonged drought at the end of 2016.
Total nutrient fluxes were calculated from nutrient concentrations with stemflow volume inputs between control and girdled trees (Table 2). Total DOC flux accumulated by the end of the study was 2.0-times greater in control trees compared to girdled trees (p = 0.030). This was largely driven by the greater total volume of stemflow generated by control trees. However, there were no differences among girdling treatments for any of the cumulative nitrogen fluxes among treatments. Instead, the greater nitrogen concentrations in stemflow from girdled trees were offset by the greater volume of stemflow from control trees.
Lastly, there were no effects of distance from the tree bole (p = 0.134) or girdling treatment (p = 0.384) on soil respiration. Instead, differences in respiration were dominated by seasonality (p < 0.001). Only in the third growing season did differences appear in which soils at 1.5 m away from tree stems that were girdled were 2.2 times greater (p = 0.002, Figure 8C).

4. Discussion

Bark beetles impact forests around the world, but their impact on ecological processes remains relatively understudied, particularly in the southeastern US [6]. In this study, we sought to quantify changes in hydrologic and soil processes using a simulated bark beetle attack by girdling trees, inoculation with blue-stain fungi, and comparing them to ungirdled healthy trees. We found that hydrologic and biogeochemical cycles were altered in girdled trees compared to non-girdled trees, but that blue-stain inoculation had no impact (Figure 9). Contrary to our predictions, we found limited differences in soil moisture between treatments throughout the first two years of the study, and stemflow actually decreased 1.7 times relative to control trees by the end of two years (Figure 4). Importantly, we found disconnects between the quality and quantity of stemflow with regard to carbon and nitrogen. In particular, greater stemflow nitrogen concentrations were negated by lower volumes of stemflow in girdled trees, while unchanged stemflow carbon concentrations resulted in lower total carbon fluxes as a result of lower volumes of stemflow in girdled trees.
These results suggest that changes in hydrologic and biogeochemical fluxes from bark-beetle-attacked trees are not evident in early stages of attack (e.g., green or red) but become apparent only after the trees transition to the gray phase. As trees die, water uptake and transpiration cease [31,60], yet stand regeneration following insect outbreaks may offset or even dwarf these reductions in water use [68,69]. The hydrologic response may be further altered by the presence of blue-stain fungi. Bark beetles vector these fungi, where they colonize sapwood and lead to rapid restriction in tree water uptake [70,71]. In our study, we did not detect a response in water uptake across fungal inoculation treatments, so it remains unknown whether the blue-stain fungi inoculation was unsuccessful or whether the act of girdling dominated the physiological trajectory of our experiment. However, evidence suggests that the net effect of tree mortality on water availability and watershed discharge also depends on interacting factors of death and regrowth [42,72].
Delayed hydrological and biogeochemical flux changes have similarly been observed in other conifer forests in North America and Europe [36,68,73,74,75], wherein the greatest effects are most strongly manifested in the gray phase. However, the rate at which attacked trees reach the gray phase in conifer forests in the eastern US is faster; 2 years in our study, compared to 4–10+ years elsewhere [68]. A confounding factor in our study was the significant drought that occurred one year after the girdling treatment, when trees had begun entering the red phase. No rainfall occurred during this critical period of mortality, and therefore left a gap in our understanding of canopy-derived fluxes in the red phase. As droughts become more common, forests may exhibit similar levels of stress compared to bark beetle attacks, impacting hydrology and the biogeochemical fluxes delivered to the forest floor. In the positive feedback cycle where droughts may increase bark beetle activity by increasing tree stress [76,77], even greater long-term impacts on forest biogeochemistry are likely to be observed.
Across broad landscapes, reductions in water uptake and transpiration, coupled with reductions in canopy interception of incident rainfall, lead to increased water availability, streamflow [68,78,79], and groundwater [7] in bark-beetle-attacked watersheds. We observed a decrease in sapflow during the initial stage of mortality (i.e., red phase), with a complete cessation of water transport by the end of the second growing season post-treatment, when trees entered the gray stage. However, we expected to see an increase in stemflow following mortality and needle loss. In general, stemflow increases as crown area increases [80], but more stemflow is generally observed during leafless canopy phases in deciduous trees because stems have a greater probability of intercepting rainfall and generating stemflow when foliar surfaces are absent [51]. In contrast, pines generate less stemflow than deciduous trees, so the loss of even a meager canopy likely impacted canopy contributions to stemflow generation [81]. In the one known study of stemflow and tree mortality, Frost and Levia [82] found that dead trees had 60-times less stemflow than living counterparts among hardwood species. Bark morphology of loblolly pine is complex, with bark plates layered on top of one another, resulting in higher porosity [83,84] that may be accessible to rainwater for bark water storage. Thus, as canopy foliage diminishes, rainwater access to bark water storage locations increases, which may further limit stemflow production. Additionally, we observed sawdust generation from secondary attacks on dead trees, which would suggest stems were becoming more porous and absorbing more incident rainwater. Therefore, a reduction in stemflow on bark-beetle-attacked trees may actually reduce biogeochemical inputs to soil and serve to inhibit decomposition around bark-beetle-attacked trees. In particular, while we observed no net change in nitrogen flux, we observed a decrease in total DOC fluxes from girdled trees, suggesting a reduction in carbon-based food sources for soil microbes [85,86]. This trend, coupled with lower soil moisture around girdled trees, is likely to further reduce soil microbial activity, impacting nutrient cycling and slowing rates of decomposition [87,88]. Further research is warranted to better understand decomposition trajectories of standing dead trees.
In this study, while there were no differences in stemflow C concentrations or the degree of C lability/recalcitrance, the reduction in total stemflow water from girdled trees resulted in a decrease in net C flux in stemflow. However, we did not observe any definitive response in soil respiration, suggesting that additional substrates beyond stemflow inputs are reaching soils and supporting microbial respiration throughout mortality. For example, fine roots and their mycorrhizal fungal associates release labile C into soil [89], whereby the death of trees and, subsequently, fine root systems halt this input of easily accessible carbon [90]. In our study, fine roots likely experienced mortality and turnover as a result of both tree mortality [91] and drought stress. This may have provided increased carbon for decomposer microbes, leading to an increase in their abundance and activity. Additionally, the turnover of fine roots may transfer nitrogen to the microbial soil biomass [92]. Alternatively, increased microbial stress could have also caused increased respiration, leading to the lack of differences between treatments. Regardless, at these time and spatial scales, CO2 flux from soils under simulated bark beetle attack did not differ from controls, suggesting that small bark beetle attacks are unlikely to have significant impacts on soil respiration rates.
Surprisingly, there were limited effects on soil moisture between girdling treatments despite the observed decrease in plant water uptake and decrease in stemflow associated with girdled trees. This suggests that the magnitude of these processes occurring simultaneously is roughly equivalent, leading to no net change in soil moisture between treatments. Additionally, throughfall volumes are likely higher in girdled trees, allowing for more precipitation to reach soils below trees. Alternatively, the small spatial extent of our study may have impeded any changes in soil moisture as the remaining healthy trees in the vicinity continued to transpire and provide shading [69], which could also moderate soil moisture. The role of drought experienced during the second year of the study also confounds our soil moisture response. However, the lack of change to soil moisture has been observed in other studies where the degree of tree mortality was manipulated, suggesting changes in water demand, canopy water partitioning, and energy availability offset any changes in soil moisture [93].

5. Conclusions

This study examined how small-scale bark beetle outbreak spots in the southeastern US impact ecological processes throughout tree mortality by simulating bark beetle attack with girdling treatments. The largest differences between control and girdled trees occurred once trees entered the gray phase. Few studies examine both short- and long-term impacts of bark beetles on ecological processes, and these data are particularly scarce from the southeastern US. Southern pine beetles are increasing their range into New England states [94] and continue to have massive outbreaks in Central America and in poorly managed forests in the southeastern US [28]. Understanding how bark-beetle-killed trees impact forest ecosystems is thus increasingly important.
By chance, this study also incorporated the impacts of drought on hydrologic and biogeochemical processes post-bark-beetle attack. A four-month extreme drought had negative impacts on canopy-derived C and N transport and soil moisture, rendering responses of control trees similar to bark-beetle-attacked trees and possibly masking the effect of mortality. Directly, climate change is facilitating range expansion of bark beetles [2], while indirectly, climate change is increasing the frequency and intensity of droughts [95,96], which further facilitates tree susceptibility to attack from some bark beetles [97]. Yet the interaction between drought and bark-beetle-derived tree mortality on ecological processes has received little attention in the eastern US. Our results suggest that droughts may increase the negative impacts of bark beetle attacks by rendering non-attacked trees similar to bark-beetle-killed trees even one year post drought.
Our understanding of the impacts of pine beetle outbreaks on ecosystem structure and function is largely guided by research based on the devastating outbreaks occurring in the western US. Smaller spots of southern pine beetle activity are common in the southeastern US, particularly in recent years due to what is hypothesized to be better forest management practices, although large outbreaks in forests with limited management are currently ongoing. Thus, this study provides realistic and needed data on ecological processes at two years and smaller spatial scales. Given the widespread impact of the southern pine beetle on forest ecosystems throughout the southeastern US, it is critical for management and planning activities to understand the role of these disturbances.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/f17020211/s1.

Author Contributions

Conceptualization, C.M.S., H.J.R., J.J.R. and N.A.C.; methodology, C.M.S., H.J.R., J.J.R. and N.A.C.; formal analysis, C.M.S.; investigation, C.M.S., H.J.R. and N.J.H.; resources, C.M.S. and P.D.; writing—original draft preparation, C.M.S.; writing—review and editing, C.M.S., H.J.R., N.J.H., P.D., J.J.R. and N.A.C. All authors have read and agreed to the published version of the manuscript.

Funding

This work is a contribution of the Forest and Wildlife Research Center and the Mississippi Agricultural and Forestry Experiment Station, Mississippi State University. This work was funded through the National Science Foundation (DEB #1660346) and supported by the National Institute of Food and Agriculture, United States Department of Agriculture, Mclntire Stennis capacity grant #MISZ-069390 and Hatch project #311330. Any opinions, findings, conclusions, or recommendations expressed in this publication are those of the authors and do not necessarily reflect the views of the United States Department of Agriculture.

Data Availability Statement

The original contributions presented in this study are included in the Supplementary Materials. Further inquiries can be directed to the corresponding author.

Acknowledgments

The authors would like to thank A.A. Sasith Karunarathna, Juliet Tang, Brent Chaney, Mercedes Siegle-Gaither, and Jacob Landfield for field and laboratory support. We would also like to thank Misty Booth, at the John W. Starr Memorial Forest, where this work was conducted.

Conflicts of Interest

J.R. is an inventor on a patent involving blue-stain fungi in baiting methods for termites (US9924706B2). The author and his institution may financially benefit from this patent.

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Figure 1. Actual observed precipitation and 30-year normal (1990–2020) precipitation for the study site (33.2671, −88.8834) from publicly available U.S. Climate Normals (1991–2020) [55].
Figure 1. Actual observed precipitation and 30-year normal (1990–2020) precipitation for the study site (33.2671, −88.8834) from publicly available U.S. Climate Normals (1991–2020) [55].
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Figure 2. Study trees across each phase of simulated bark beetle attack, including (a) green-attack phase, where trees are infested but still maintain green needles, (b) red-attack phase, where needle death occurs, and (c) gray-attack phase, where needles drop and leave a bare canopy [5].
Figure 2. Study trees across each phase of simulated bark beetle attack, including (a) green-attack phase, where trees are infested but still maintain green needles, (b) red-attack phase, where needle death occurs, and (c) gray-attack phase, where needles drop and leave a bare canopy [5].
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Figure 3. Mean seasonal differences in sapflow in L per tree between treatments with standard error bars. Seasonal labels on the x-axis are labeled with seasonal abbreviations and year (Su: Summer; Fa: Fall; Wi: Winter; Sp: Spring). Differences in sapflow between treatments within each season are denoted by “*”. Data collection ceased after Winter 2017 because no sapflow was produced from girdled trees after Fall 2016. Green phase: trees infested but still maintain green needles; red phase: needle death; gray phase: needles drop and bare canopy [5].
Figure 3. Mean seasonal differences in sapflow in L per tree between treatments with standard error bars. Seasonal labels on the x-axis are labeled with seasonal abbreviations and year (Su: Summer; Fa: Fall; Wi: Winter; Sp: Spring). Differences in sapflow between treatments within each season are denoted by “*”. Data collection ceased after Winter 2017 because no sapflow was produced from girdled trees after Fall 2016. Green phase: trees infested but still maintain green needles; red phase: needle death; gray phase: needles drop and bare canopy [5].
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Figure 4. Mean seasonal stemflow volumetric flux per square meter of basal area between treatments with standard error bars. Seasonal labels on the x-axis are labeled with seasonal abbreviations and year (Su: Summer; Fa: Fall; Wi: Winter; Sp: Spring). Differences in stemflow between treatments within each season are denoted by “*”. Note: no rain occurred in Summer 2015 or Fall 2016. Green phase: trees infested but still maintain green needles; red phase: needle death; gray phase: needles drop and bare canopy [5].
Figure 4. Mean seasonal stemflow volumetric flux per square meter of basal area between treatments with standard error bars. Seasonal labels on the x-axis are labeled with seasonal abbreviations and year (Su: Summer; Fa: Fall; Wi: Winter; Sp: Spring). Differences in stemflow between treatments within each season are denoted by “*”. Note: no rain occurred in Summer 2015 or Fall 2016. Green phase: trees infested but still maintain green needles; red phase: needle death; gray phase: needles drop and bare canopy [5].
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Figure 5. Seasonal volumetric water content (VWC) deviation from overall season mean between treatments with standard error bars at 0.5 m, 1.0 m, and 1.5 m distances from tree boles. Positive values indicate soils are wetter than average, and negative values indicate soils are drier than average. Seasonal labels on the x-axis are labeled with seasonal abbreviations and year (Su: Summer; Fa: Fall; Wi: Winter; Sp: Spring). Differences in VWC between treatments within each season are denoted by “*”. Volumetric water content measurements began in Spring 2016 along with soil respiration. Green phase: trees infested but still maintain green needles; red phase: needle death; gray phase: needles drop and bare canopy [5].
Figure 5. Seasonal volumetric water content (VWC) deviation from overall season mean between treatments with standard error bars at 0.5 m, 1.0 m, and 1.5 m distances from tree boles. Positive values indicate soils are wetter than average, and negative values indicate soils are drier than average. Seasonal labels on the x-axis are labeled with seasonal abbreviations and year (Su: Summer; Fa: Fall; Wi: Winter; Sp: Spring). Differences in VWC between treatments within each season are denoted by “*”. Volumetric water content measurements began in Spring 2016 along with soil respiration. Green phase: trees infested but still maintain green needles; red phase: needle death; gray phase: needles drop and bare canopy [5].
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Figure 6. Estimated marginal mean seasonal (A) dissolved organic carbon (DOC) concentrations and (B) specific UV absorbance (SUVA) in rainfall, throughfall, and stemflow from control and girdled trees with standard error bars. Seasonal labels on the x-axis are labeled with seasonal abbreviations and year (Su: Summer; Fa: Fall; Wi: Winter; Sp: Spring). Note: no rain occurred in Summer 2015 or Fall 2016. Green phase: trees infested but still maintain green needles; red phase: needle death; gray phase: needles drop and bare canopy [5].
Figure 6. Estimated marginal mean seasonal (A) dissolved organic carbon (DOC) concentrations and (B) specific UV absorbance (SUVA) in rainfall, throughfall, and stemflow from control and girdled trees with standard error bars. Seasonal labels on the x-axis are labeled with seasonal abbreviations and year (Su: Summer; Fa: Fall; Wi: Winter; Sp: Spring). Note: no rain occurred in Summer 2015 or Fall 2016. Green phase: trees infested but still maintain green needles; red phase: needle death; gray phase: needles drop and bare canopy [5].
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Figure 7. Mean seasonal (A) nitrate ( N O 3 − –N) concentration, (B) ammonium ( N H 4 + –N) concentration, (C) organic nitrogen concentration, and (D) total nitrogen concentration in rainfall, throughfall, and stemflow (control and girdled trees) with standard error bars. Labels on the x-axis are seasonal abbreviations and year (Su: Summer; Fa: Fall; Wi: Winter; Sp: Spring). Differences in stemflow concentrations between treatments within each season are denoted by “*”. Note: no rain occurred in Summer 2015 or Fall 2016. Green phase: trees infested but still maintain green needles; red phase: needle death; gray phase: needles drop and bare canopy [5].
Figure 7. Mean seasonal (A) nitrate ( N O 3 − –N) concentration, (B) ammonium ( N H 4 + –N) concentration, (C) organic nitrogen concentration, and (D) total nitrogen concentration in rainfall, throughfall, and stemflow (control and girdled trees) with standard error bars. Labels on the x-axis are seasonal abbreviations and year (Su: Summer; Fa: Fall; Wi: Winter; Sp: Spring). Differences in stemflow concentrations between treatments within each season are denoted by “*”. Note: no rain occurred in Summer 2015 or Fall 2016. Green phase: trees infested but still maintain green needles; red phase: needle death; gray phase: needles drop and bare canopy [5].
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Figure 8. Mean seasonal soil respiration across all three distances from tree boles: 0.5 m (A), 1.0 m (B), 1.5 m (C), with standard error bars. Seasonal labels on the x-axis are labeled with seasonal abbreviations and year (Su: Summer; Fa: Fall; Wi: Winter; Sp: Spring). Respiration measurements began in Spring 2016. Differences in respiration between treatments within each season are denoted by “*”. Green phase: trees infested but still maintain green needles; red phase: needle death; gray phase: needles drop and bare canopy [5].
Figure 8. Mean seasonal soil respiration across all three distances from tree boles: 0.5 m (A), 1.0 m (B), 1.5 m (C), with standard error bars. Seasonal labels on the x-axis are labeled with seasonal abbreviations and year (Su: Summer; Fa: Fall; Wi: Winter; Sp: Spring). Respiration measurements began in Spring 2016. Differences in respiration between treatments within each season are denoted by “*”. Green phase: trees infested but still maintain green needles; red phase: needle death; gray phase: needles drop and bare canopy [5].
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Figure 9. Summary of impacts to water (blue bars), stemflow chemistry (green bars), and soil respiration (brown bars) of simulated bark beetle mortality using girdling compared to ungirdled, control trees. Brackets around nutrients denote concentrations.
Figure 9. Summary of impacts to water (blue bars), stemflow chemistry (green bars), and soil respiration (brown bars) of simulated bark beetle mortality using girdling compared to ungirdled, control trees. Brackets around nutrients denote concentrations.
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Table 1. Estimated marginal means ± standard error of chemical concentrations in rainfall, throughfall, and stemflow from linear mixed-effects model comparing hydrologic pathway among treatments, season, and their interaction. Letters denote statistical differences for each solute within the four hydrological pathways of PG—precipitation; TF—throughfall; SF: Control—stemflow from control trees; SF: girdled—stemflow from girdled trees. Significant p-values are denoted in bold.
Table 1. Estimated marginal means ± standard error of chemical concentrations in rainfall, throughfall, and stemflow from linear mixed-effects model comparing hydrologic pathway among treatments, season, and their interaction. Letters denote statistical differences for each solute within the four hydrological pathways of PG—precipitation; TF—throughfall; SF: Control—stemflow from control trees; SF: girdled—stemflow from girdled trees. Significant p-values are denoted in bold.
Solute Concentration (mg/L)p-Value
PGTFSF:
Control		SF:
Girdled		TreatmentSeasonTreatment × Season
DOC4.67 ± 8.69 a16.23 ± 6.31 a44.76 ± 3.27 b45.16 ± 4.92 b<0.0010.2140.873
SUVA4.57 ± 0.64 a7.93 ± 0.40 b7.97 ± 0.27 b8.04 ± 0.55 b<0.0010.0720.802
N O 3 − –N0.15 ± 0.38 a0.08 ± 0.24 a0.28 ± 0.19 a0.36 ± 0.12 a0.7260.2990.001
N H 4 + –N0.24 ± 1.22 a0.23 ± 0.78 a1.54 ± 0.62 a2.37 ± 0.39 a0.0670.8450.635
ON0.27 ± 0.78 a0.69 ± 0.50 a1.29 ± 0.12 a1.75 ± 0.17 a0.3890.0660.998
TN0.63 ± 1.79 a0.90 ± 1.13 a2.57 ± 0.92 a3.92 ± 0.58 a0.0700.5960.743
Table 2. Mean ± standard error of cumulative chemical fluxes in stemflow across girdling treatments in mg of flux standardized per one square meter of basal area. Significant p-values are denoted in bold.
Table 2. Mean ± standard error of cumulative chemical fluxes in stemflow across girdling treatments in mg of flux standardized per one square meter of basal area. Significant p-values are denoted in bold.
Control TreesGirdled Treesp-Value
DOC (mg m−2 BA)69,669 ± 22,46834,249 ± 33700.030
N O 3 − –N (mg m−2 BA)154 ± 50161 ± 620.913
N H 4 + –N (mg m−2 BA)1191 ± 841601 ± 2800.392
ON (mg m−2 BA)1738 ± 3661243 ± 1300.127
TN (mg m−2 BA)2813 ± 4032746 ± 3880.923
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Siegert, C.M.; Renninger, H.J.; Hornslein, N.J.; Dash, P.; Riggins, J.J.; Clay, N.A. Changes in Forest Hydrology and Biogeochemistry Following a Simulated Tree Mortality Event of Southern Pine Beetle: A Case Study. Forests 2026, 17, 211. https://doi.org/10.3390/f17020211

AMA Style

Siegert CM, Renninger HJ, Hornslein NJ, Dash P, Riggins JJ, Clay NA. Changes in Forest Hydrology and Biogeochemistry Following a Simulated Tree Mortality Event of Southern Pine Beetle: A Case Study. Forests. 2026; 17(2):211. https://doi.org/10.3390/f17020211

Chicago/Turabian Style

Siegert, Courtney M., Heidi J. Renninger, Nicole J. Hornslein, Padmanava Dash, John J. Riggins, and Natalie A. Clay. 2026. "Changes in Forest Hydrology and Biogeochemistry Following a Simulated Tree Mortality Event of Southern Pine Beetle: A Case Study" Forests 17, no. 2: 211. https://doi.org/10.3390/f17020211

APA Style

Siegert, C. M., Renninger, H. J., Hornslein, N. J., Dash, P., Riggins, J. J., & Clay, N. A. (2026). Changes in Forest Hydrology and Biogeochemistry Following a Simulated Tree Mortality Event of Southern Pine Beetle: A Case Study. Forests, 17(2), 211. https://doi.org/10.3390/f17020211

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