Tropical forests exert a disproportionately large influence on terrestrial carbon (C) balance but projecting the effects of climate change on C cycling in tropical forests remains uncertain. Reducing this uncertainty requires improved quantification of the independent and interactive effects of variable and changing temperature and precipitation regimes on C inputs to, cycling within and loss from tropical forests. Here, we quantified aboveground litterfall and soil‐surface CO2efflux (“soil respiration”;
Identifying factors controlling forest productivity is critical to understanding forest‐climate change feedbacks, modelling vegetation dynamics and carbon finance schemes. However, little research has focused on productivity in regenerating tropical forests which are expanding in their fraction of global area have an order of magnitude larger carbon uptake rates relative to older forest. We examined above‐ground net primary productivity (ANPP) and its components (wood production and litterfall) over 10 years in forest plots that vary in successional age, soil characteristics and species composition using band dendrometers and litterfall traps in regenerating seasonally dry tropical forests in northwestern Costa Rica. We show that the components of ANPP are differentially driven by age and annual rainfall and that local soil variation is important. Total ANPP was explained by a combination of age, annual rainfall and soil variation. Wood production comprised 35% of ANPP on average across sites and years, and was explained by annual rainfall but not forest age. Conversely, litterfall increased with forest age and soil fertility yet was not affected by annual rainfall. In this region, edaphic variability is highly correlated with plant community composition. Thus, variation in ecosystem processes explained by soil may also be partially explained by species composition. These results suggest that future changes in annual rainfall can alter the secondary forest carbon sink, but this effect will be buffered by the litterfall flux which varies little among years. In determining the long‐term strength of the secondary forest carbon sink, both rainfall and forest age will be critical variables to track. We also conclude that detailed understanding of local site variation in soils and plant community may be required to accurately predict the impact of changing rainfall on forest carbon uptake.
- NSF-PAR ID:
- 10375684
- Publisher / Repository:
- Wiley-Blackwell
- Date Published:
- Journal Name:
- Journal of Ecology
- Volume:
- 109
- Issue:
- 11
- ISSN:
- 0022-0477
- Page Range / eLocation ID:
- p. 3903-3915
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
more » « less
Abstract F S) in nine plots organized across a highly constrained 5.2°C mean annual temperature (MAT) gradient in tropical montane wet forest. We used five consecutive years of these measurements, during which annual rainfall (AR) steadily increased, in order to: (a) estimate total belowground C flux (TBCF); (b) examine how interannual variation in AR alters the apparent temperature dependency (Q10) of above‐ and belowground C fluxes; and (c) quantify stand‐level C allocation responses to MAT and AR. Averaged across all years,F S, litterfall, and TBCF increased positively and linearly with MAT, which accounted for 49, 47, and 46% of flux rate variation, respectively. Rising AR lowered TBCF andF S, but increased litterfall, with patterns representing interacting responses to declining light. The Q10ofF S, litterfall, and TBCF all decreased with increasing AR, with peak sensitivity to MAT in the driest year and lowest sensitivity in the wettest. These findings support the conclusion that for this tropical montane wet forest, variations in light, water, and nutrient availability interact to strongly influence productivity (litterfall+TBCF), the sensitivity of above‐ and belowground C fluxes to rising MAT (Q10ofF S, litterfall, and TBCF), and C allocation patterns (TBCF:[litterfall+TBCF]). -
more » « less
Abstract Landslides are common natural disturbances in tropical montane forests. While the geomorphic drivers of landslides in the Andes have been studied, factors controlling post‐landslide forest recovery across the steep climatic and topographic gradients characteristic of tropical mountains are poorly understood.
Here we use a LiDAR‐derived canopy height map coupled with a 25‐year landslide time‐series map to examine how landslide, topographic and biophysical factors, along with residual vegetation, affect canopy height and heterogeneity in regenerating landslides. We also calculate above‐ground biomass accumulation rates and estimate the time for landslides to recover to mature forest biomass levels.
We find that age and elevation are the biggest determinants of forest recovery, and that the jump‐start in regeneration that residual vegetation provides lasts for at least 18 years. Our estimates of time to biomass recovery (31.6–37.1 years) are surprisingly rapid, and as a result we recommend that future research pair LiDAR with hyperspectral imagery to estimate forest above‐ground biomass in frequently disturbed landscapes.
Synthesis . Using a high‐resolution LiDAR dataset and a time‐series inventory of 608 landslides distributed across a wide elevational gradient in Andean montane forest, we show that age and elevation are the most influential predictors of forest canopy height and canopy variability. Other features of landslides, in particular the presence of residual vegetation, shape post‐landslide regeneration trajectories. LiDAR allows for a detailed analysis of forest structural recovery across large landscapes and numbers of disturbances, and provides a reasonable upper bound on above‐ground biomass accumulation rates. However, because this method does not capture the effect of compositional change through succession on above‐ground biomass, wherein high‐wood density species gradually replace light‐wooded pioneer species, it overestimates above‐ground biomass. Given previously estimated stem turnover rates along this elevational gradient, we posit that above‐ground biomass recovery takes at least three times as long as our recovery time estimates based on LiDAR‐derived structure alone. -
more » « less
Abstract Greater tree density and forest productivity at the tundra–taiga ecotone (TTE) are expected with climate warming, with potential feedbacks to the climate system. Yet, competition for nitrogen (N) may impact TTE dynamics. Greater tree density will likely increase N demand, while reducing N supply through soil shading and slower decomposition rates. We explored whether characteristics of roots and root‐associated fungi important to N acquisition responded to changes in density at the TTE and were related to above‐ground stand productivity and N cycling.
We measured rooting depth, uptake of N forms among soil layers and ectomycorrhizal (EcM) colonization and composition along a natural tree density gradient of monodominant larch
Larix cajanderi in northeastern Siberia. We tested relationships between larch root and fungal characteristics, above‐ground productivity and stand‐level N cycling parameters.Overall, there was preferential uptake of ammonium compared to glycine or nitrate. Nitrogen uptake was greatest in shallow soils of the organic horizon and related to root chemistry, root‐associated fungi and above‐ground N cycling parameters, but the direction of these relationships depended on N form. Uptake of different N forms, rooting depth and EcM colonization and composition were not related to tree density, but fungal composition was correlated with root N chemistry and above‐ground N cycling parameters. In addition to EcM, the abundance of dark septate endophytes and other ascomycetous taxa was positively related to N uptake and above‐ground N cycling parameters.
Synthesis . There was little impact of tree density on root and fungal parameters related to N acquisition suggesting intraspecific larch competition for N was not amplified with increased density. There was, however, a strong impact of root‐associated fungi on N uptake and stand N dynamics regardless of tree density. Together, this suggests an important role of root‐associated fungi on broadscale patterns of N cycling in TTE larch forests independent of changes in tree density expected with climate warming. -
more » « less
Summary Arbuscular mycorrhizal fungi (AMF) and ectomycorrhizal fungi (EMF) produce contrasting plant–soil feedbacks, but how these feedbacks are constrained by lithology is poorly understood.
We investigated the hypothesis that lithological drivers of soil fertility filter plant resource economic strategies in ways that influence the relative fitness of trees with AMF or EMF symbioses in a Bornean rain forest containing species with both mycorrhizal strategies.
Using forest inventory data on 1245 tree species, we found that although AMF‐hosting trees had greater relative dominance on all soil types, with declining lithological soil fertility EMF‐hosting trees became more dominant. Data on 13 leaf traits and wood density for a total of 150 species showed that variation was almost always associated with soil type, whereas for six leaf traits (structural properties; carbon, nitrogen, phosphorus ratios, nitrogen isotopes), variation was also associated with mycorrhizal strategy. EMF‐hosting species had slower leaf economics than AMF‐hosts, demonstrating the central role of mycorrhizal symbiosis in plant resource economies.
At the global scale, climate has been shown to shape forest mycorrhizal composition, but here we show that in communities it depends on soil lithology, suggesting scale‐dependent abiotic factors influence feedbacks underlying the relative fitness of different mycorrhizal strategies.
-
more » « less
Abstract A central goal at the interface of ecology and conservation is understanding how the relationship between biodiversity and ecosystem function (B–EF) will shift with changing climate. Despite recent theoretical advances, studies which examine temporal variation in the functional traits and mechanisms (mass ratio effects and niche complementarity effects) that underpin the B–EF relationship are lacking.
Here, we use 13 years of data on plant species composition, plant traits, local‐scale abiotic variables, above‐ground net primary productivity (ANPP), and climate from the alpine tundra of Colorado (USA) to investigate temporal dynamics in the B–EF relationship. To assess how changing climatic conditions may alter the B–EF relationship, we built structural equation models (SEMs) for 11 traits across 13 years and evaluated the power of different trait SEMs to predict ANPP, as well as the relative contributions of mass ratio effects (community‐weighted mean trait values; CWM), niche complementarity effects (functional dispersion; FDis) and local abiotic variables. Additionally, we coupled linear mixed effects models with Multimodel inference methods to assess how inclusion of trait–climate interactions might improve our ability to predict ANPP through time.
In every year, at least one SEM exhibited good fit, explaining between 19.6% and 57.2% of the variation in ANPP. However, the identity of the trait which best explained ANPP changed depending on winter precipitation, with leaf area, plant height and foliar nitrogen isotope content (δ15N) SEMs performing best in high, middle and low precipitation years, respectively. Regardless of trait identity, CWMs exerted a stronger influence on ANPP than FDis and total biotic effects were always greater than total abiotic effects. Multimodel inference reinforced the results of SEM analysis, with the inclusion of climate–trait interactions marginally improving our ability to predict ANPP through time.
Synthesis . Our results suggest that temporal variation in climatic conditions influences which traits, mechanisms and abiotic variables were most responsible for driving the B–EF relationship. Importantly, our findings suggest that future research should consider temporal variability in the B–EF relationship, particularly how the predictive power of individual functional traits and abiotic variables may fluctuate as conditions shift due to climate change.
