Report on Scale-Dependent Biodiversity Loss from Land-Use Change and Implications for Sustainable Development Goals

Executive Summary

A comprehensive study on avian biodiversity in Colombia reveals that the impacts of converting forests to cattle pasture are significantly underestimated by conventional, local-scale assessments. This report synthesizes the findings, highlighting a critical gap in monitoring progress towards the Sustainable Development Goals (SDGs), particularly SDG 15 (Life on Land). The research, conducted across 13 distinct biogeographic regions, demonstrates that biodiversity losses are, on average, 60% more severe when measured at a near-national scale compared to a single-region scale. This discrepancy is attributed to biotic homogenization, where the unique species compositions (high beta-diversity) of different forest regions are replaced by a uniform set of species in pastures. The primary drivers of this homogenization are the erosion of species turnover across vast geographic distances and elevational gradients. These findings underscore the urgent need to revise biodiversity assessment methodologies to incorporate spatial scale, ensuring that policies aimed at achieving SDG 15, SDG 2 (Zero Hunger), and SDG 12 (Responsible Consumption and Production) are based on accurate data reflecting true, large-scale environmental impacts.

Introduction: The Challenge of Scaling Biodiversity Assessments for Sustainable Development

The global biodiversity crisis, driven primarily by land-use change, poses a direct threat to achieving the 2030 Agenda for Sustainable Development. Tropical forests, which harbor the majority of terrestrial species, are particularly vulnerable. Accurately quantifying biodiversity loss is fundamental to tracking progress on SDG 15 (Life on Land), which aims to halt biodiversity loss and restore terrestrial ecosystems. However, current understanding is predominantly based on local-scale studies. This approach creates a critical challenge:

• Biotic Homogenization: Land conversion, such as for agriculture, often replaces diverse, specialized native species with a small number of widespread, generalist species. This process reduces the unique character of local ecosystems (beta-diversity).
• The Scaling Problem: Aggregating results from multiple local studies may not capture the cumulative loss of unique species across a larger region, leading to a significant underestimation of the true impact. This leaves a considerable uncertainty gap for policymakers and undermines efforts to integrate biodiversity values into national planning as mandated by SDG Target 15.9.

This report details a study that addresses this scaling problem by empirically quantifying biodiversity change from local to near-national scales, providing crucial insights for achieving sustainable land management.

Methodology: A Pan-National Assessment in Colombia

To investigate the spatial scaling of biodiversity loss, a large-scale avian field study was conducted in the megadiverse country of Colombia, contrasting natural forest habitats with cattle pasture—the nation’s dominant agricultural land use.

Study Design

• Sampling Scope: The study encompassed 848 sampling points across 13 distinct biogeographic regions, covering a wide range of elevations (100–4,060 m) and environmental gradients. This scale far exceeds typical field-based biodiversity assessments.
• Data Collection: Using point count methodology, researchers obtained 24,981 detections of 971 bird species.
• Analytical Framework: A biogeographic multi-species occupancy model (bMSOM) was employed to analyze the data. This advanced statistical tool allowed for:
  1. Modeling species-specific responses to forest conversion for 1,614 species (including those not directly detected).
  2. Accounting for imperfect detection during surveys.
  3. Predicting species occupancy across the entire study region in both forest and pasture scenarios.

Key Findings: Scale-Dependent Biodiversity Loss and Biotic Homogenization

Severe Underestimation of Biodiversity Loss at Larger Scales

The study’s primary finding is that biodiversity loss is substantially more severe when viewed at a larger, multi-region scale. This directly impacts the assessment of progress towards SDG 15.5 (halt biodiversity loss).

• Losses at the pan-Colombian scale were 60% more severe than the average loss within a single region.
• Estimates of biodiversity loss did not stabilize and reflect the pan-Colombian value until data from six to seven biogeographic regions were combined.
• This indicates that the vast majority of existing studies, which typically sample only one or two regions, are systematically underestimating the true severity of biodiversity loss from deforestation.

The Role of Beta-Diversity in Driving Regional Impacts

The discrepancy between local and regional losses is driven by the erosion of beta-diversity. Regions with high beta-diversity (i.e., rapid species turnover across space) experience the greatest “excess regional loss.”

• In regions with high beta-diversity, the impacts of habitat conversion at the regional scale were more than double the severity of local-scale impacts.
• Forest conversion to pasture leads to biotic homogenization, where spatially separated agricultural landscapes host highly similar communities of disturbance-tolerant species.
• This process erases the unique ecological character of different regions, a critical dimension of biodiversity that is missed by local-scale metrics.

Geographic and Elevational Gradients as Key Drivers

Generalized dissimilarity models (GDMs) were used to identify the factors driving species turnover. The results show that cattle farming flattens the natural ecological gradients that structure biodiversity.

• Geographic Distance: In forests, bird communities become increasingly dissimilar with greater distance. In pastures, this pattern collapses; communities show negligible turnover beyond 200 km.
• Elevation: Forests exhibit high species turnover along elevational gradients. This turnover is dramatically reduced in pastures, as non-forest species expand their ranges into formerly forested elevations.

Implications for Sustainable Development Goals (SDGs)

The study’s findings have profound implications for global conservation policy and the monitoring of the 2030 Agenda.

SDG 15: Life on Land

The systematic underestimation of biodiversity loss challenges our ability to accurately track progress towards key targets. To effectively halt biodiversity loss (Target 15.5) and promote the sustainable management of forests (Target 15.2), monitoring frameworks must be redesigned to incorporate spatial structure and large-scale dynamics. The accrual of biodiversity loss at larger scales highlights the immense value of protecting even small forest patches, as their contribution to regional biodiversity is greater than local assessments suggest.

SDG 2 & SDG 12: Sustainable Agriculture and Consumption

The research focuses on cattle pasture but notes that the findings are applicable to other major agricultural commodities (oil palm, soy, coffee) that span multiple ecoregions. This highlights a direct conflict between current agricultural expansion and biodiversity conservation, undermining efforts to build sustainable food production systems (SDG 2.4) and ensure sustainable consumption and production patterns (SDG 12). While practices like silvopasture may offer local benefits, they are unlikely to fully mitigate the large-scale homogenizing effects of agriculture. This reinforces the need for land-sparing approaches and integrated land-use planning that protects large, intact forest landscapes.

SDG 17: Partnerships for the Goals

Addressing the scale-dependent nature of biodiversity loss requires a paradigm shift in research and policy. This necessitates enhanced global partnerships (SDG 17) to:

1. Develop and adopt new analytical tools and statistical frameworks capable of delivering reliable, large-scale biodiversity metrics.
2. Design and fund monitoring schemes with embedded spatial structures that can capture regional dynamics.
3. Foster policy coherence for sustainable development (Target 17.14) by ensuring that agricultural, economic, and environmental policies are aligned and informed by accurate, scale-appropriate data.

Conclusion and Recommendations

The prevailing reliance on local-scale assessments provides a dangerously incomplete picture of biodiversity loss in the Anthropocene. By failing to account for the collapse of beta-diversity across large spatial scales, we are systematically underestimating the impact of land-use change, particularly from widespread agricultural activities like cattle farming.

Recommendations

1. Adopt Scale-Appropriate Monitoring: National and international bodies, including those monitoring the SDGs, must move beyond aggregating local data and implement monitoring programs designed to assess biodiversity change across large biogeographic gradients.
2. Prioritize Landscape-Scale Conservation: Conservation strategies should focus on protecting networks of habitats across entire landscapes to maintain beta-diversity. This includes supporting major area-based targets (e.g., 30×30), protecting Intact Forest Landscapes, and recognizing the role of Indigenous communities in safeguarding regional biodiversity.
3. Integrate Land-Use Planning: Governments must develop and enforce integrated land-use plans that strategically balance agricultural production with the retention of natural habitat across diverse ecoregions, thereby preventing large-scale biotic homogenization.
4. Invest in Analytical Capacity: There is an urgent need for investment in the statistical tools and analytical frameworks, such as the one used in this study, that can reliably deliver robust, large-scale biodiversity metrics to guide effective and sustainable policy-making.

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

SDG 15: Life on Land

• The article’s central theme is the impact of land-use change on terrestrial biodiversity, which is the core focus of SDG 15. It specifically investigates how converting forests to cattle pasture in Colombia leads to a loss of avian biodiversity. The study emphasizes the importance of protecting terrestrial ecosystems, particularly forests and mountain ecosystems, and halting biodiversity loss. The text states, “Land-use change is a leading driver of the global biodiversity crisis, particularly in the highly diverse tropics.”

SDG 2: Zero Hunger

• The article connects to SDG 2 through its discussion of agriculture and food production systems. The land-use change examined is driven by “cattle pasture,” a key component of the livestock sector. The article touches upon the sustainability of these practices by mentioning “low-productivity pastures” and contrasting them with potentially more sustainable “silvopastoral systems,” which aligns with the goal of ensuring sustainable food production systems.

SDG 12: Responsible Consumption and Production

• This goal is relevant as the article discusses the environmental consequences of a specific production system—cattle ranching. The conversion of “219 million hectares of tropical moist forest… pan-tropically” for agriculture, including cattle, highlights unsustainable production patterns. The article’s conclusion implies that the impacts of other commodities like “oil palm, soy, coffee and sugar cane” are also likely underestimated, pointing to a broader issue of unsustainable resource management in global supply chains.

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

SDG 15: Life on Land

1. Target 15.1: By 2020, ensure the conservation, restoration and sustainable use of terrestrial and inland freshwater ecosystems and their services, in particular forests, wetlands, mountains and drylands, in line with obligations under international agreements.
   • The article directly addresses this by quantifying biodiversity loss in forest and mountain ecosystems due to conversion to cattle pasture. The study’s focus on “13 biogeographic regions of Colombia,” including “montane forests” and “Andean páramos,” demonstrates a clear link to the conservation of these specific ecosystem types.
2. Target 15.2: By 2020, promote the implementation of sustainable management of all types of forests, halt deforestation, restore degraded forests and substantially increase afforestation and reforestation globally.
   • The research is fundamentally about the consequences of deforestation (“converting forest to pasture”). It highlights the urgency of halting this process by revealing that its impacts are “severely underestimated.” The conclusion calls for “effective protection across landscape-scale biogeographic variation” to prevent further deforestation.
3. Target 15.4: By 2030, ensure the conservation of mountain ecosystems, including their biodiversity, in order to enhance their capacity to provide benefits that are essential for sustainable development.
   • The study explicitly samples across “all three Andean cordilleras, the Santa Marta massif” and finds that communities in montane forests “displayed greatest sensitivity to habitat conversion.” This directly supports the need to conserve mountain biodiversity as outlined in this target.
4. Target 15.5: Take urgent and significant action to reduce the degradation of natural habitats, halt the loss of biodiversity and, by 2020, protect and prevent the extinction of threatened species.
   • The article’s core finding is about “biotic homogenization” and the “loss of small-ranged forest-dwelling species.” It quantifies biodiversity loss by analyzing 971 bird species and warns that current assessment methods lead to a “major underestimation of biodiversity loss in the Anthropocene,” directly aligning with the call for urgent action to halt this loss.
5. Target 15.9: By 2020, integrate ecosystem and biodiversity values into national and local planning, development processes, poverty reduction strategies and accounts.
   • The paper argues that aggregating “local estimates of species richness change… fails to reflect global trends with enough accuracy to be useful for policymaking.” It calls for “globally applicable metrics of biodiversity value” and the design of “monitoring schemes with embedded spatial structures” to better inform planning and policy, which is the essence of this target.

SDG 2: Zero Hunger

1. Target 2.4: By 2030, ensure sustainable food production systems and implement resilient agricultural practices that increase productivity and production, that help maintain ecosystems… and that progressively improve land and soil quality.
   • The article evaluates the impact of “low-productivity pastures,” a dominant agricultural system in Colombia. It implicitly critiques its sustainability by highlighting its severe impact on biodiversity. It also mentions “silvopastoral systems” as a more wildlife-friendly alternative that could “triple bird species richness,” pointing towards more sustainable agricultural practices that help maintain ecosystems.

SDG 12: Responsible Consumption and Production

1. Target 12.2: By 2030, achieve the sustainable management and efficient use of natural resources.
   • The conversion of hyperdiverse tropical forests, a critical natural resource, into “low-productivity pastures” is presented as an inefficient and unsustainable use of land and natural capital. The article’s conclusion that “biodiversity impacts of land-use conversion are underestimated in general” for many commodities underscores the widespread challenge of achieving sustainable resource management.

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

Indicators for SDG 15

• Indicator 15.1.1 (Forest area as a proportion of total land area): The article implicitly uses this by studying the conversion of forests to pasture. It provides context by stating that “pasturelands are the dominant agricultural land use… accounting for over 34 million hectares (30% of Colombia’s land area) and over 75% of all cleared forestland.”
• Indicator 15.4.2 (Mountain Green Cover Index): While not named, the study’s entire methodology of comparing “forest and cattle pasture across 13 biogeographic regions,” including extensive mountain ranges like the Andes, is a direct assessment of the change in green cover and habitat quality in mountain ecosystems.
• Indicator 15.5.1 (Red List Index): The article does not use the Red List Index by name, but its entire analytical framework is designed to measure the components that influence it. The study develops metrics like “species-specific sensitivity to habitat conversion,” “biotic homogenization,” “beta-diversity,” and “species richness.” These are used to quantify how land-use change affects the viability and distribution of 971 bird species, including “24 endemic bird species,” which is a direct assessment of extinction risk and biodiversity loss.
• Indicator 15.9.1 (Progress towards national targets established in accordance with Aichi Biodiversity Target 2 of the Strategic Plan for Biodiversity 2011–2020): The article is a critique of current biodiversity assessment methods and a proposal for improved metrics. It argues for “metrics tailored to the appropriate regional scale of policy interest” and the development of “analytical frameworks and statistical tools capable of reliably delivering these metrics.” This directly addresses the need for robust measurement systems to integrate biodiversity into national planning.

Indicators for SDG 2

• Indicator 2.4.1 (Proportion of agricultural area under productive and sustainable agriculture): The article provides a qualitative assessment related to this indicator. It characterizes the dominant land use as “low-productivity pastures” and contrasts this with “silvopastoral systems” that can “triple bird species richness,” thereby providing a biodiversity-based metric to differentiate between less sustainable and more sustainable agricultural practices.

4. Table of SDGs, Targets, and Indicators

Source: nature.com