A machine-learning approach to human footprint index estimation with applications to sustainable development

The human footprint index (HFI) is an extensively used tool for interpreting the accelerating pressure of humanity on Earth. Up to now, the process of creating the HFI has required significant data and modeling, and updated versions of the index often lag the present day by many years. Here we introduce a near-present, global-scale machine learning-based HFI (ml-HFI) which is capable of routine update using satellite imagery alone. We present the most up-to-date map of the HFI, and document changes in human pressure during the past 20 years (2000–2019). Moreover, we demonstrate its utility as a monitoring tool for the United Nations Sustainable Development Goal 15 (SDG15), ‘Life on Land’, which aims to foster sustainable development while conserving biodiversity. We identify 43 countries that are making progress toward SDG15 while also experiencing increases in their ml-HFI. We examine a subset of these in the context of conservation policies that may or may not enable continued progress toward SDG15. This has immediate policy relevance, since the majority of countries globally are not on track to achieve Goal 15 by the declared deadline of 2030. Moving forward, the ml-HFI may be used for ongoing monitoring and evaluation support toward the twin goals of fostering a thriving society and global Earth system.

It is widely accepted that the main driver of the observed decline in biological diversity is increasing human pressure on Earth's ecosystems. However, the spatial patterns of change in human pressure and their relation to conservation efforts are less well known. We developed a spatially and temporally explicit map of global change in human pressure over 2 decades between 1990 and 2010 at a resolution of 10 km(2) . We evaluated 22 spatial data sets representing different components of human pressure and used them to compile a temporal human pressure index (THPI) based on 3 data sets: human population density, land transformation, and electrical power infrastructure. We investigated how the THPI within protected areas was correlated to International Union for Conservation of Nature (IUCN) management categories and the human development index (HDI) and how the THPI was correlated to cumulative pressure on the basis of the original human footprint index. Since the early 1990s, human pressure increased 64% of the terrestrial areas; the largest increases were in Southeast Asia. Protected areas also exhibited overall increases in human pressure, the degree of which varied with location and IUCN management category. Only wilderness areas and natural monuments (management categories Ib and III) exhibited decreases in pressure. Protected areas not assigned any category exhibited the greatest increases. High HDI values correlated with greater reductions in pressure across protected areas, while increasing age of the protected area correlated with increases in pressure. Our analysis is an initial step toward mapping changes in human pressure on the natural world over time. That only 3 data sets could be included in our spatio-temporal global pressure map highlights the challenge to measuring pressure changes over time.

Biodiversity loss is a global environmental concern, mainly driven by human-induced factors, encompassing both direct and indirect drivers. This study investigates the long-term relationship between either the Human Footprint Index (HFI), which measures the extent of human pressures (i.e., direct drivers), or the Gross Domestic Product (GDP), a measure of economic growth (i.e., indirect driver) and biodiversity change, using bird population trends as indicators. The analysis was based on time-series data for Portugal (2004–2023) aggregated at national and sub-national scales, representative of different socio-economic contexts. Multi-species indices were regressed against either the HFI or GDP using Autoregressive Distributed Lag (ARDL) to identify long-run relationships. Bird population trends varied by species group (common, agricultural, and forest birds) and socio-economic context underscoring the importance of sub-national assessments. The HFI and GDP had varying predictive value across species groups and socio-economic contexts, with the HFI showing greater consistency, particularly as a predictor for agricultural birds. While most models showed a negative association between species abundance and either the HFI or GDP, revealing a signal of socio-economic pressures on bird populations at sub-national scales, some models suggested mixed results, indicating that conservation policies must take local contexts into account.

Recent increases in human pressure and forest loss threaten many Natural World Heritage Sites

Sand fixation and human activities on the Qinghai-Tibet Plateau for ecological conservation and sustainable development

Intensified human activities have been seriously threatening the structure and ecological processes of ecosystems, resulting in habitat degradation. Therefore, coordinating the coupling between human activities and habitat quality (HQ) is crucial for high‐quality sustainable regional development and human well‐being. This study evaluated the human activities and HQ in the Pearl River Delta (PRD) urban agglomeration in China from 2000 to 2020 using the human footprint index (HFI) and the integrated valuation of ecosystem services and tradeoffs model. Then, we employed bivariate spatial autocorrelation and a coupling coordination degree (CCD) model to explore the synergistic relationship between human activities and HQ. The results show that spatial changes in HQ were predominantly driven by human activities. The gradual outward urban expansion resulted in significant HQ degradation. Slight HQ improvement by ecological restoration in urban outskirts cannot offset HQ losses caused by urbanization. During the study period, high‐HQ low‐HFI clusters decreased by 1.02%, while low‐HQ high‐HFI clusters increased by 4.67%, the two main clustering types in the PRD. Despite the CCD between HFI and HQ increased after 2010, the continuous changes of CCD characteristics from the HFI significantly lagged type to the HQ lagged. HFI showed an inverted U‐shaped relationship with CCD. The CCD peaks during 2000–2020 corresponded to HFI decreasing from 0.711 to 0.566. This indicates that the risk of decoupling between human activities and HQ gradually increased. Furthermore, CCD levels and characteristics in different bivariate clusters exhibited varying changes over time. These results reveal that the spatiotemporal dislocation between urbanization and ecological restoration induced the spatial nonstationarity of the coupling relationship between human activities and HQ. Urbanization exacerbates the imbalance between human development and biodiversity conservation. Therefore, we suggest reasonably delimiting urban boundaries, controlling the scale of urban sprawl, and strengthening biodiversity protection in areas undergoing rapid urbanization. In addition, we advocate for the division of ecological barrier zones, urban development buffer zones, and urban built‐up areas, each with tailored management and protection measures. Our findings can provide an important reference for the ecological restoration of urban agglomerations.

SummaryMedium- and large-sized mammals play important roles in maintaining forest ecosystem functions, and these functions often diminish when mammal species are depleted by human activities. Understanding the sensitivity or tolerance of mammal species to human pressure and detecting species changes through monitoring programmes can inform appropriate management decisions. The objective of our study was to identify medium- and large-sized mammal species that can be included in a monitoring programme in the Southern Yungas of Argentina. We used occupancy modelling to estimate the probability of habitat use (ψ) of 13 of 25 mammal species detected by 165 camera traps placed in forests across a range of human footprint index (HFI) values. As defined by the HFI, 54% of the study area is wilderness. The probabilities of habitat use of two mammal species were significantly associated with the HFI: the lowland tapir (Tapirus terrestris; ψ = 0.33, range = 0.22–0.50) was inversely associated with HFI values, whereas the grey brocket deer (Mazama gouazoubira; ψ = 0.79, range = 0.67–0.87) was positively associated with the HFI. Monitoring the probability of habitat use of the sensitive species (lowland tapir) could help us to detect changes in areas experiencing anthropogenic impacts before they cause extirpation, whereas the high probability of the habitat use values of the tolerant species (grey brocket deer) might indicate that anthropogenic impacts are strongly influencing habitat, signalling that mitigation strategies might be warranted. The Southern Yungas retains an intact mammal fauna, and we showed that the HFI is useful for monitoring anthropogenic impacts on these mammals. There are still opportunities to develop conservation strategies to minimize threats to mammal species in the region by implementing a monitoring programme with the proposed species.

Global landscapes are changing due to human activities with consequences for both biodiversity and ecosystems. For single species, terrestrial mammal population densities have shown mixed responses to human pressure, with both increasing and decreasing densities reported in the literature. How the impacts of human activities on mammal populations translates into altered global density patterns remains unclear. Here we aim to disentangle the effect of human impacts on large‐scale patterns of mammal population densities using a global dataset of 6729 population density estimates for 468 mammal species (representing 59% and 44% of mammalian orders and families). We fitted a mixed effect model to explain the variation in density based on a 1‐degree resolution as a function of the human footprint index (HFI), a global proxy of direct and indirect human disturbances, while accounting for body mass, trophic level and primary productivity (normalized vegetation index; NDVI). We found a significant positive relationship between population density and HFI, where population densities were higher in areas with a higher HFI (e.g. agricultural or suburban areas – no populations were located in very high HFI urban areas) compared to areas with a low HFI (e.g. wilderness areas). We also tested the effect of the individual components of the HFI and still found a consistent positive effect. The relationships remained positive even across populations of the same species, although variability among species was high. Our results indicate shifts in mammal population densities in human modified landscapes, which is due to the combined effect of species filtering, increased resources and a possible reduction in competition and predation. Our study provides further evidence that macroecological patterns are being altered by human activities, where some species will benefit from these activities, while others will be negatively impacted or even extirpated.

Previous assessments of the effectiveness of protected areas (PAs) focused primarily on changes in human pressure over time and did not consider the different human‐pressure baselines of PAs, thereby potentially over‐ or underestimating PA effectiveness. We developed a framework that considers both human‐pressure baseline and change in human pressure over time and assessed the effectiveness of 338 PAs in China from 2010 to 2020. The initial state of human pressure on PAs was taken as the baseline, and changes in human pressure index (HPI) were further analyzed under different baselines. We used the random forest models to identify the management measures that most improved effectiveness in resisting human pressure for the PAs with different baselines. Finally, the relationships between the changes in the HPI and the changes in natural ecosystems in PAs were analyzed with different baselines. Of PAs with low HPI baselines, medium HPI baselines, and high HPI baselines, 76.92% (n=150), 11.11% (n=12), and 22.86% (n=8) , respectively, showed positive effects in resisting human pressure. Overall, ignoring human‐pressure baselines somewhat underestimated the positive effects of PAs, especially for those with low initial human pressure. For PAs with different initial human pressures, different management measures should be taken to improve effectiveness and reduce threats to natural ecosystems. We believe our framework is useful for assessing the effectiveness of PAs globally, and we recommend it be included in the Convention on Biological Diversity Post‐2020 Strategy.

Human footprint defining conservation strategies in Patagonian landscapes: Where we are and where we want to go?

The non-profit sector plays a pivotal role in achieving the Kingdom’s Vision 2030, where it represents a potential economic opportunity for development. Therefore, the current study aimed to identify ways non-profit organizations (NPOs) can support sustainable economic development through community activities, leading to the achievement of the United Nations Sustainable Development Goals and Saudi Vision 2030. The Ensan Association in the Kingdom of Saudi Arabia was chosen as a case study due to its importance and influence in this sector. The study also aimed to identify the impact of Ensan Association’s social responsibility activities on sustainable economic development in the local community, focusing on two indicators: raising the standard of living of individuals and reducing unemployment rates in Saudi Arabia. The study relied on a mixed methodology to collect data using questionnaires and interviews. Correlation analysis results showed a strong relationship between social responsibility activities and achieving the economic goals of sustainable development, namely raising the standard of living and reducing unemployment. Simple regression results also showed that a one-unit increase in social responsibility activities leads to a significant improvement in these economic goals, which positively impacts sustainable economic development. Furthermore, the results of the multiple linear regression demonstrated strong statistical significance for the model, and the study confirmed the importance of NPOs’ social responsibility activities in supporting sustainable economic development. Based on the study’s findings, it recommends empowering NPOs by developing specialized training programs for the most vulnerable groups and diversifying their funding sources to ensure sustainability. It also encourages decision-makers to adopt supportive policies and legislation that strengthen partnerships and secure investment to achieve sustainable development. The non-profit sector plays a pivotal role in achieving the Kingdom’s Vision 2030, where it represents a potential economic opportunity for development. Therefore, the current study aimed to identify ways non-profit organizations (NPOs) can support sustainable economic development through community activities, leading to the achievement of the United Nations Sustainable Development Goals and Saudi Vision 2030. The Ensan Association in the Kingdom of Saudi Arabia was chosen as a case study due to its importance and influence in this sector. The study also aimed to identify the impact of Ensan Association’s social responsibility activities on sustainable economic development in the local community, focusing on two indicators: raising the standard of living of individuals and reducing unemployment rates in Saudi Arabia. The study relied on a mixed methodology to collect data using questionnaires and interviews. Correlation analysis results showed a strong relationship between social responsibility activities and achieving the economic goals of sustainable development, namely raising the standard of living and reducing unemployment. Simple regression results also showed that a one-unit increase in social responsibility activities leads to a significant improvement in these economic goals, which positively impacts sustainable economic development. Furthermore, the results of the multiple linear regression demonstrated strong statistical significance for the model, and the study confirmed the importance of NPOs’ social responsibility activities in supporting sustainable economic development. Based on the study’s findings, it recommends empowering NPOs by developing specialized training programs for the most vulnerable groups and diversifying their funding sources to ensure sustainability. It also encourages decision-makers to adopt supportive policies and legislation that strengthen partnerships and secure investment to achieve sustainable development.

In the face of river basin environmental challenges and the urgent need for sustainable development strategies, understanding the complex interactions among ecological services, human activities, and vegetation cover is of paramount importance. Although previous studies have extensively documented the widespread impact of human activities on ecosystem service value (ESV), the mechanisms by which different human activities affect ESV with different functions are still unclear. To bridge these gaps, this study investigated the relationships among ESV, human footprint index (HFI), and fractional vegetation coverage (FVC) in the Yangtze River Basin (YRB). We used land cover change analysis and the equivalent factor method to study the spatiotemporal structure of ESV in YRB from 2000 to 2020, and selected different human footprint indicators to evaluate HFI and vegetation cover assessment FVC. The results revealed that construction land in YRB has increased the most significantly, reaching 25014 km2, and ESV has increased by 4.55% in general, approximately 22915 billion CNY. Among them, the regulating service value (RSV) has increased by 18696 billion CNY. The FVC shows a pattern of 'high in the middle, low in the east and west', of which 71.30% shows a significant increase, especially in the upstream areas. Curve estimation analysis revealed that an increasing HFI is associated with decreases in RSV, supporting service value (SSV), and cultural service value (CSV), whereas provisioning service value (PSV) increases. Conversely, an increase in vegetation coverage, was positively correlated with ESV. The strong positive correlation between FVC and ESV highlights the importance of vegetation cover in sustaining ecosystem services. This underscores the significant impact of the HFI and FVC on ESV and emphasizes the need to consider regional differentiation in ecosystem assessments. These insights are crucial for policymakers and conservation practitioners aiming to promote sustainable ecosystem development and conservation in the YRB.

Spatio-temporal interaction and constraint effects between ecosystem services and human activity intensity in Shaanxi Province,China

The added value of partnerships in implementing the UN sustainable development goals

ABSTRACTJordan faces stringent energy challenges mainly in the form of import dependence and escalating demand. The building sector accounts for 58% of total national electricity consumption and therefore plays an important role in addressing these challenges. This article investigates how energy efficiency in green buildings certified by the Leadership in Energy and Environmental Design (LEED) rating system contribute towards achieving United Nations (UN) Sustainable Development Goals (SDGs) in Jordan. Furthermore, this paper proposes a new Comprehensive Contribution to Sustainable Development Index (CCSDI) to assess the contributions of implementation of the LEED 2009 prerequisites and credits in the Energy and Atmosphere (EA) category to achieve UN SDGs in Jordan. Questionnaire surveys were conducted to obtain data. Relative Importance Index (RII) method was used to evaluate the contributions of LEED 2009 prerequisites and credits in the EA category. Results indicate a positive relationship between the LEED 2009 prerequisites and credits in category and UN SDGs 7−9 and 12−13. We conclude that our proposed CCSDI is a robust tool for assessing the contribution of energy efficiency in LEED 2009 certified green buildings towards achieving UN SDGs in Jordan.