The Sensitivity of Dry Tropical Montane Forests to Precipitation Variability: Insights from a Forest Simulation Model
Tropical montane forests, found in high-altitude regions of the tropics, are unique and fragile ecosystems. They are home to a rich array of biodiversity, provide essential ecosystem services such as water regulation and carbon sequestration, and support the livelihoods of millions of people. However, these forests are increasingly threatened by climate change and human activities, leading to degradation and deforestation.
Munessa-Shashemene Forest: A Case Study
The dry tropical montane forest of Munessa-Shashemene in Ethiopia is a prime example of a forest facing these challenges. The forest has experienced a dramatic decline, with the percentage of natural high forest cover decreasing from 16% to only 3% during 1972–2000. Climate change is expected to exacerbate these pressures. The region is projected to experience an increase in total annual precipitation, but also more frequent extreme weather events such as droughts and torrential rains.
Understanding Forest Dynamics with FORMIX3
To understand how these changes in precipitation might affect the Munessa-Shashemene forest, Hiltner et al. (2016) used the FORMIX3 forest simulation model. This model simulates the growth and competition of individual trees, taking into account factors such as light availability, water availability, and species-specific traits. The researchers parameterized the model using field data, including tree-ring measurements, to ensure its accuracy.
Impact of Precipitation Variability
The study found that the forest is highly sensitive to changes in precipitation. Both the total amount of annual precipitation and its intra-annual distribution (i.e., the timing and intensity of rainfall events) significantly influence forest growth and species composition.
- Increased Precipitation: The model predicts that an increase in mean annual precipitation would lead to an increase in both overall biomass and species richness, as depicted in Figure 1. This suggests that the forest could potentially benefit from a wetter climate, at least up to a certain point. Beyond an annual precipitation of about 1500 mm, the positive effects on biomass start to plateau.
- Intra-annual Variability: However, the study also found that changes in the timing and intensity of rainfall events can have negative impacts. More frequent droughts or torrential rains can disrupt the forest's water balance and lead to decreased growth and even tree mortality. As shown in Figure 1, the model predicts a decrease in overall biomass and species diversity under scenarios with increased intra-annual precipitation variability, even if the total annual precipitation remains the same.
Key insights from figure 1
Panel (a):
- Aboveground Biomass and Precipitation: This panel shows how the total aboveground biomass (AGB) of a forest changes with the amount of annual precipitation. There are two scenarios explored: one where the total amount of precipitation changes (SET 1), and another where the frequency of precipitation events changes (SET 2).
- Biomass Increase with Precipitation: In general, as annual precipitation increases, so does the aboveground biomass. This is evident in the upward trend of both the red and green dots and their respective dashed trend lines.
- Plateau at High Precipitation: However, there seems to be a point where increasing precipitation further doesn't lead to a significant increase in biomass. This is suggested by the flattening of the trend lines at higher precipitation values.
- Scenario Comparison: The red dots (IPCC AR5-based scenarios) generally show lower biomass values than the green dots (reference scenarios) for the same amount of precipitation. This indicates that climate change projections might lead to reduced forest growth compared to current conditions.
Panel (b):
- Shannon Index and Precipitation: This panel shows the relationship between the Shannon index (a measure of species diversity) and the amount of annual precipitation.
- Peak Diversity at Intermediate Precipitation: The curve shows a hump-shaped pattern, suggesting that species diversity is highest at intermediate levels of precipitation. Both very low and very high precipitation levels seem to support lower diversity.
- Scenario Comparison: Again, the red dots (IPCC AR5-based scenarios) tend to show lower diversity values than the green dots (reference scenarios) for the same amount of precipitation, hinting at potential biodiversity loss under climate change.
Shannon index: The Shannon index, also known as the Shannon-Wiener index or Shannon entropy, is a quantitative measure that reflects how many different types (e.g., species) there are in a dataset (e.g., a forest) and how evenly the basic entities (e.g., individual trees) are distributed among those types.
- A higher Shannon index indicates a more diverse community, with a greater number of species and a more even distribution of individuals among those species.
- A lower Shannon index suggests a less diverse community, with either fewer species or a more uneven distribution of individuals (i.e., dominance by a few species).
The value range of the Shannon index is theoretically from 0 (a community with only one species) to the natural logarithm of the number of species in the dataset (a community with perfect evenness among all species). In practice, the values typically fall within a smaller range depending on the specific ecosystem and the number of species present.
Relevance to the blog:
This figure supports the blog's central theme of the sensitivity of dry tropical montane forests to changes in precipitation. It visually demonstrates:
- Positive impact of increased rainfall on forest growth (biomass), but only up to a certain point. This reinforces the idea that while these forests might benefit from a wetter climate, there are limits to this positive effect.
- Negative impact of changing rainfall patterns on species diversity. This highlights the potential biodiversity loss these forests might face under climate change, even if the total rainfall increases.
- Potential negative effects of climate change on both forest growth and diversity. The comparison between the IPCC AR5-based scenarios and the reference scenarios suggests that climate change might lead to less productive and less diverse forests.
Overall, the figure emphasizes the delicate balance of these ecosystems and the need for careful management and conservation in the face of climate change.
Importance of Tree-Ring Data
The study also highlights the value of tree-ring data for understanding forest dynamics and improving model accuracy. By analyzing the growth rings of trees, researchers can gain insights into past climate conditions and how the forest has responded to them. This information can then be used to calibrate and validate forest models, making them more reliable for predicting future changes.
Key insights from figure 2
Unveiling the Growth Secrets of C. macrostachyus
This figure provides a glimpse into the growth patterns of Croton macrostachyus, a key tree species in the study, using a combination of wood anatomy analysis and tree-ring data.
Panel (a): Wood Anatomy
This panel showcases a cross-section of C. macrostachyus wood, highlighting its anatomical features:
- Vessels (V): These are tube-like structures responsible for transporting water and minerals throughout the tree. Their size and distribution can reveal insights into the tree's water-use efficiency and adaptation to its environment.
- Rays (R): These are radial structures that transport nutrients and store food reserves. They contribute to the tree's structural integrity and resilience.
- Growth-ring boundary (GRB): This marks the transition between one year's growth and the next. The thickness of each ring reflects the tree's growth rate during that year, with wider rings indicating more growth.
Panel (b): Tree-ring Chronology
This panel presents a 35-year tree-ring chronology for C. macrostachyus. The blue line shows the mean annual increment rates, with peaks and troughs indicating years of faster and slower growth, respectively. The red line represents a 5-year running mean, smoothing out the year-to-year fluctuations to reveal longer-term growth trends. The dashed line indicates the overall mean ring-width, providing a baseline for comparison.
Panel (c): Number of Synchronized Trees
This panel shows the number of trees used to create the chronology in each year. A higher number of trees contributes to a more robust and reliable chronology.
Panel (d): Model Parameterization
This panel demonstrates how the tree-ring data is translated into a growth model. The stem diameter increment curve, derived from the tree-ring measurements, represents the maximum potential growth of an individual tree in the absence of competition. This curve is then incorporated into the FORMIX3 model, allowing it to simulate tree growth more accurately.
Relevance to the Blog
Figure 2 underscores the importance of tree-ring analysis in understanding and predicting forest dynamics. By revealing past growth patterns and their relationship to environmental factors, tree-ring data helps researchers calibrate and validate forest models like FORMIX3. This, in turn, enables more accurate simulations of forest responses to future climate change and disturbances, ultimately informing sustainable forest management practices. The figure also emphasizes the intricate link between tree growth, environmental conditions, and the overall health of forest ecosystems.
Need for Comprehensive Forest Inventory Data
The collection and analysis of field data, such as forest inventories, are crucial for understanding the dynamics of tropical montane forests and developing effective conservation and management strategies. The importance of such data will be further explored in a future blog post.
Implications for Forest Management
The findings of this study have important implications for the management of dry tropical montane forests. They suggest that conservation efforts should focus not only on protecting these forests from deforestation but also on managing them in a way that enhances their resilience to climate change. This might involve strategies such as promoting tree species that are tolerant to drought or planting trees in areas that are likely to receive more rainfall in the future. Additionally, the study emphasizes the need to consider the potential negative impacts of increased precipitation variability, even in scenarios where total annual rainfall increases.
Future of Tropical Montane Forests
The future of tropical montane forests like Munessa-Shashemene is uncertain. Climate change is likely to bring significant challenges, but with careful management and a better understanding of forest dynamics, we can help these vital ecosystems adapt and thrive. Forest simulation models, validated with real-world data, will be crucial tools in this effort.
Reference
Hiltner, U., Bräuning, A., Gebrekirstos, A., Huth, A., Fischer, R., 2016. Impacts of precipitation variability on the dynamics of a dry tropical montane forest. Ecol. Model. 320, 92–101. https://doi.org/10.1016/j.ecolmodel.2015.09.021
