Reply to: Is apparent optimum soil moisture equivalent to field capacity? – Nature

Report on Ecosystem Photosynthesis, Soil Moisture, and Sustainable Development

Introduction and Relevance to Sustainable Development Goals (SDGs)

A scientific discourse has emerged concerning the acclimation of ecosystem photosynthesis, measured as Gross Primary Productivity (GPP), to soil moisture. This report analyzes a response to a commentary by Zhao et al., which questioned the concept of ecosystem acclimation and proposed an equivalence between apparent optimum soil moisture (SM_opt^GPP) and soil field capacity (θ_FC). Understanding this relationship is critical for advancing several Sustainable Development Goals (SDGs), including:

• SDG 13 (Climate Action): Accurately modeling the global carbon cycle and climate feedbacks depends on a precise understanding of how terrestrial ecosystems respond to water availability.
• SDG 15 (Life on Land): The productivity and resilience of terrestrial ecosystems are fundamentally linked to soil moisture dynamics. Effective conservation and management strategies require robust scientific models.
• SDG 2 (Zero Hunger): GPP is a direct indicator of plant growth, which underpins agricultural productivity and global food security.
• SDG 6 (Clean Water and Sanitation): The study touches upon soil hydraulic properties, which are integral to managing water resources sustainably.

The responding analysis identifies three primary issues with the commentary by Zhao et al., which challenge its conclusions and reaffirm the importance of ecosystem water acclimation in the context of global environmental change.

Analysis of Key Scientific Discrepancies

The response refutes the commentary’s central claims by highlighting significant conceptual and analytical weaknesses. These points are crucial for ensuring that policies related to climate action and land management are based on sound science.

1. Conceptual Confusion Between Ecosystem and Soil Properties

   A fundamental issue identified is the conflation of two distinct concepts: SM_opt^GPP and θ_FC. This distinction is vital for progress on SDG 15, which relies on a clear understanding of ecosystem functions.

   • Apparent Optimum Soil Moisture (SM_opt^GPP): This is defined as an ecosystem property derived from the GPP-soil moisture response curve. It represents the soil water level required to maximize an ecosystem’s photosynthetic productivity.
   • Field Capacity (θ_FC): This is a soil hydraulic property, indicating the amount of water a particular soil type can retain after excess water has drained. It is a characteristic of the soil itself, not the ecosystem’s response.

   Treating these concepts as equivalent is conceptually inappropriate and misrepresents the complex interactions between soil, water, and vegetation that govern ecosystem health and contribute to climate regulation (SDG 13).

2. Lack of Direct Evidentiary Support

   The commentary’s assertion of equivalence between SM_opt^GPP and θ_FC is not supported by compelling, direct evidence. The analysis relies on simulated data, which may introduce unaddressed biases, and employs inappropriate statistical methods.

   • The use of linear regression is not suitable for testing equivalence between two variables.
   • A re-analysis of the commentary’s own data reveals that the ratio of SM_opt^GPP to θ_FC varies widely, from 0.81 to 1.41, directly contradicting the claim of equivalence.

   This lack of robust evidence undermines the commentary’s conclusions and emphasizes the need for rigorous, field-verified data to inform models used for climate and agricultural forecasting (SDG 13, SDG 2).

3. Uncertainties and Methodological Flaws in Analysis

   The commentary attributes variations in SM_opt^GPP to soil texture, concluding that inherent soil properties, not acclimation, are the primary drivers. However, this analysis contains significant uncertainties.

   • The analysis establishes a correlation but fails to prove a causal link between soil texture and SM_opt^GPP.
   • Crucially, the analysis did not account for co-varying factors, particularly local soil water availability during the growing season (SM_growth), which the original study identified as a key factor influencing SM_opt^GPP through acclimation.
   • The original study demonstrated through statistical controls and a field experiment that the effect of soil texture becomes negligible when other factors are considered, whereas SM_growth remains a strong, causal driver of SM_opt^GPP.

Implications for Climate Action and Ecosystem Management (SDG 13 & 15)

The concept of water acclimation has significant ecological implications for predicting how ecosystems will respond to changing climate patterns, a core concern of SDG 13. The relationship between SM_growth and SM_opt^GPP determines whether increased soil moisture will stimulate or suppress ecosystem productivity.

• If SM_opt^GPP does not increase proportionally with SM_growth, ecosystems may become more susceptible to productivity declines from excess moisture (e.g., waterlogging).
• Conversely, if SM_opt^GPP adjusts proportionally to higher SM_growth, ecosystems can better capitalize on increased water availability to enhance carbon uptake.

This dynamic is essential for understanding carbon-climate feedbacks and managing forests, grasslands, and agricultural lands for maximum productivity and resilience, directly supporting the objectives of SDG 15 and SDG 2.

Conclusion and Future Directions for Sustainable Management

The evidence strongly supports the water acclimation of ecosystem photosynthesis, a process with critical implications for global sustainability. The analysis presented by Zhao et al. is not sufficiently robust to overturn this finding. Future research, particularly through global networks of controlled field experiments, is necessary to further investigate the mechanisms controlling SM_opt^GPP. Such efforts will improve our understanding of carbon-climate feedbacks and provide the scientific foundation needed to achieve key targets within the Sustainable Development Goals, especially those related to climate action (SDG 13), life on land (SDG 15), and sustainable water management (SDG 6).

Analysis of Sustainable Development Goals (SDGs) in the Article

1. Which SDGs are addressed or connected to the issues highlighted in the article?

The article’s scientific discussion on ecosystem photosynthesis, soil moisture, and water retention properties connects to several Sustainable Development Goals. The primary focus on terrestrial ecosystems, water dynamics, and their role in the global carbon cycle establishes these links.

• SDG 2: Zero Hunger: The research into Gross Primary Productivity (GPP) is fundamentally about the photosynthetic capacity of ecosystems, which is the basis for all plant growth, including agricultural crops. Understanding the optimal soil moisture for maximizing GPP has direct implications for improving agricultural productivity and ensuring sustainable food production systems.
• SDG 6: Clean Water and Sanitation: The article is centered on soil moisture, a critical component of the water cycle. It discusses soil’s capacity to retain water (field capacity, θ_FC) and the availability of water for plants. This relates to the efficient use of water resources and the health of water-related ecosystems.
• SDG 13: Climate Action: The article explicitly mentions that understanding the dynamics of optimal soil moisture and its control mechanisms is valuable for improving our “understanding of carbon-climate feedbacks.” This research contributes directly to the knowledge base needed to model climate change and develop mitigation and adaptation strategies.
• SDG 15: Life on Land: This is the most directly relevant SDG. The article discusses terrestrial ecosystem functions (photosynthesis), soil properties (soil texture, water retention), and the impact of water availability (drought) on these systems. The research aims to protect and understand the functioning of terrestrial ecosystems.

2. What specific targets under those SDGs can be identified based on the article’s content?

Based on the article’s focus, several specific SDG targets can be identified:

1. Target 2.4: By 2030, ensure sustainable food production systems and implement resilient agricultural practices that increase productivity and production.
   • Explanation: The article’s investigation into the “apparent optimum soil moisture” to “maximize GPP” is directly aimed at understanding how to increase the primary productivity of ecosystems. This knowledge is crucial for developing agricultural practices that optimize water use to enhance crop yields.
2. Target 6.4: By 2030, substantially increase water-use efficiency across all sectors and ensure sustainable withdrawals and supply of freshwater to address water scarcity.
   • Explanation: The core debate in the article revolves around how ecosystems acclimate to soil moisture to optimize photosynthesis. Understanding the relationship between “soil water availability (SM_growth)” and “ecosystem photosynthesis” is key to managing water resources more efficiently in both natural and agricultural settings.
3. Target 13.3: Improve education, awareness-raising and human and institutional capacity on climate change mitigation, adaptation, impact reduction and early warning.
   • Explanation: The scientific discourse in the article, which aims to clarify complex relationships in “carbon-climate feedbacks,” contributes to the advanced knowledge required for building institutional capacity. The research itself is a form of knowledge generation that underpins effective climate action strategies.
4. Target 15.3: By 2030, combat desertification, restore degraded land and soil, including land affected by drought and floods, and strive to achieve a land degradation-neutral world.
   • Explanation: The article discusses key factors related to land health, such as “soil texture,” “soil sand fraction,” and “inherent soil water retention properties.” It also references the “International Drought Experiment,” highlighting the importance of understanding and mitigating the impacts of drought on ecosystems, which is central to combating desertification and land degradation.

3. Are there any indicators mentioned or implied in the article that can be used to measure progress towards the identified targets?

Yes, the article mentions or implies several specific scientific metrics and concepts that can serve as indicators for measuring progress.

• Gross Primary Productivity (GPP): Mentioned throughout the article, GPP is a direct measure of the rate at which an ecosystem captures and stores carbon through photosynthesis. It serves as a key indicator for Target 2.4 (agricultural productivity) and Target 15.3 (ecosystem health and restoration).
• Soil Moisture Content: This is a central variable in the study. Monitoring soil moisture is a direct indicator for Target 6.4 (water-use efficiency) and Target 15.3 (drought and land degradation), as it quantifies the water available to plants.
• Soil Water Retention Properties (including Field Capacity, θ_FC, and soil texture): The article discusses these properties as critical factors influencing water availability. These are indicators of soil health and its ability to support life, relevant to Target 15.3. For instance, the article notes the importance of “soil texture in influencing” water dynamics.
• Understanding of Carbon-Climate Feedbacks: While not a quantitative metric itself, the article’s conclusion emphasizes the need for further research to “improve our understanding of carbon-climate feedbacks.” Progress in this scientific understanding, through studies like this one, is an indicator for Target 13.3, as it enhances the capacity to model and address climate change.

4. Create a table with three columns titled ‘SDGs, Targets and Indicators” to present the findings from analyzing the article. In this table, list the Sustainable Development Goals (SDGs), their corresponding targets, and the specific indicators identified in the article.

Source: nature.com