Modeling the spatio-temporal dynamics and interactions of households, landscapes, and giant panda habitat

Gaps and opportunities in modelling human influence on species distributions in the Anthropocene

Understanding species distributions is a global priority for mitigating environmental pressures from human activities. Ample studies have identified key environmental (climate and habitat) predictors and the spatial scales at which they influence species distributions. However, regarding human influence, such understandings are largely lacking. Here, to advance knowledge concerning human influence on species distributions, we systematically reviewed species distribution modelling (SDM) articles and assessed current modelling efforts. We searched 12,854 articles and found only 1,429 articles using human predictors within SDMs. Collectively, these studies of >58,000 species used 2,307 unique human predictors, suggesting that in contrast to environmental predictors, there is no 'rule of thumb' for human predictor selection in SDMs. The number of human predictors used across studies also varied (usually one to four per study). Moreover, nearly half the articles projecting to future climates held human predictors constant over time, risking false optimism about the effects of human activities compared with climate change. Advances in using human predictors in SDMs are paramount for accurately informing and advancing policy, conservation, management and ecology. We show considerable gaps in including human predictors to understand current and future species distributions in the Anthropocene, opening opportunities for new inquiries. We pose 15 questions to advance ecological theory, methods and real-world applications.

Optimizing protected areas to boost the conservation of key protected wildlife in China

To meet the challenge of biodiversity loss and reach the targets of the proposed Post-2020 Global Biodiversity Framework, the Chinese government updated the list of national key protected wildlife in 2021 and has been continually expanding the protected areas (PAs). However, the status of protected wildlife in PAs remains unclear. In this study, we conducted a national assessment of the status of protected wildlife and suggested an optimization plan to overcome these shortcomings. From 1988 to 2021, the number of protected species almost doubled, and the area of PAs increased by 2.4 times, covering over 92.8% of the protected species. Nonetheless, 70.8% of the protected species are still not effectively protected by PAs, with some having less than 10% of their habitat included in PAs. Despite the significant addition of amphibians and reptiles to the latest protection list, they are the fewest species and are the least covered by PAs compared with birds and mammals. To fix these gaps, we systematically optimized the current PAs network by adding another 10.0% of China's land area as PAs, which resulted in 37.6% coverage of protected species' habitats in PAs. In addition, 26 priority areas were identified. Our research aimed to identify gaps in current conservation policies and suggest optimization solutions to facilitate wildlife conservation planning in China. In general, updating the list of key protected wildlife species and systematically optimizing PA networks are essential and applicable to other countries facing biodiversity loss.

Quantifying the Evolution of Giant Panda Habitats in Sichuan Province under Different Scenarios

The giant panda (Ailuropoda melanoleuca) is a relic species in China and a flagship species in the field of endangered wildlife conservation. The conservation of the giant panda’s habitat has gained widespread attention for this reason. Historically, Chinese Giant Panda Nature Reserves are surrounded by communities and the resource utilization behavior of households disturbs the giant panda habitat. Changes in these communities and in Giant Panda Nature Reserves began around 2010, with the feminization and aging of the farm labor force. These changes brought different resource utilization behaviors that led to different evolutionary tendencies in giant panda habitats. This research study assesses the impact of these tendencies based on data from the fourth survey of the giant panda in the Sichuan Province and from geographic information data. The paper aims to uncover the internal mechanisms of farmers’ resource utilization behavior in terms of the changes wrought to giant panda habitats. The paper simulates the future habitat of the giant panda based on the LUCC (land use/cover change) model to identify anticipated changes in future landscape patterns and the habitat quality of giant pandas under the current scenarios. The paper analyzes the spatial-temporal change of landscape patterns through the land use transfer matrix, based on the Markov model. The results of the scenario analyses illustrate the spatial and temporal difference in habitat quality. The driving mechanism for landscape pattern change is explored using the logistic regression model. The paper simulates the variation tendency of giant panda habitats under differential labor force structures and resource utilization behavior based on the CA (cellular automata) model, with the robustness of the results verified by participatory experiment. Through four scenarios of simulated farm labor force structure and resource utilization behavior, results suggest that the quality of giant panda habitats in the future will be relatively high when workforce feminization and aging is intense and resource utilization behavior is weakened. The simulated results confirm that the current agricultural labor force structure can reduce the intensity of resource utilization behavior. In this scenario, disturbance to giant panda habitats would decrease and their quality would improve.

A global assessment of the impact of individual protected areas on preventing forest loss

Globally, the number and extent of terrestrial protected areas (PAs) are expanding rapidly. Nonetheless, their impacts on preventing forest loss and the factors influencing the impacts are not well understood, despite the critical roles of forests in biodiversity conservation, provision of ecosystem services, and achievement of the United Nations' Sustainable Development Goals. To address this important knowledge gap, we quantified the impacts of 54,792 PAs worldwide on preventing forest loss from 2000 to 2015, and assessed important landscape and management factors affecting the impacts of PAs. Although the majority (71.4%) of the PAs contributed to preventing forest loss, only 30.5% of forest loss in the PAs have been prevented. PAs with higher rates of forest loss in their surrounding regions, located at lower elevations, within a few hours of travel from the nearest city, with higher agricultural productivity, and permission for fewer human uses were better able to prevent forest loss. Impacts on preventing forest loss were similar regardless of whether the PAs were privately or publicly owned. Our findings highlight the potential benefits of strict protections, involving private entities in the establishment of PAs, and situating PAs in areas exposed to high risks of forest loss to enhance the capacity to combat global forest loss.

National Level Land-Use Changes in Functional Urban Areas in Poland, Slovakia, and Czechia

Land-use and cover change (LUCC) impacts global environmental changes. Therefore, it is crucial to obtain cross-national level LUCC data that represents past and actual LUCC. As urban areas exhibit the most significant dynamics of the changes, accompanied by such processes as urban sprawl, it seems desirable to take into account LUCC information from such areas to acquire national level information. The paper analyses land-use changes (LUCs) in urban areas in Czechia, Poland, and Slovakia. The analysis is based on functional urban area (FUA) data from the European Urban Atlas project for 2006 and 2012. The area of urbanised land grew at the expense of agricultural areas, semi-natural areas, and wetlands over the investigated period in all three countries. The authors determined LUC direction models in urban areas based on the identified land-use change. The proposed LUC direction models for the investigated period and area should offer national level LUC data for such purposes as modelling of future changes or can be the point of reference for planning analyses. The paper proposes the following models: mean model, median model, weighted mean model where the weight is the urbanised to vegetated area ratio, and weighted mean model where the weight is the share of urbanised areas. According to the proposed LUC models, areas considered as urbanised grow in FUAs on average in six years by 5.5900‰ in Czechia, 7.5936‰ in Poland, and 4.0769‰ in Slovakia. Additionally, the change models facilitated determination of a LUC dynamics ratio in each country. It reached the highest values in Poland and the lowest in Slovakia.

Characteristics and impacts of solid waste on giant panda habitat in Wanglang Nature Reserve

Systematic research on solid waste pollution in giant panda habitat is lacking. To fill in this gap in the literature, a survey for solid waste was conducted in Wanglang Nature Reserve in July and August of 2018 and 2019. A total of 16 transects, 16 giant panda habitat plots, 16 livestock habitat plots, and 16 common habitat plots were surveyed. We analyzed the type and distribution of solid waste and the possible impacts of typical solid waste. Results showed that 133 solid waste samples from the five categories (livestock feces, plastic waste, metal waste, construction waste, and paper waste) were detected. Livestock feces accounted for the highest proportion of solid waste at 82.7%, while the remaining types of waste accounted for only 17.3% of the solid waste observed. Livestock feces were distributed relatively evenly within 400 m from roads, while 69.6% of non-livestock fecal waste were distributed 0-100 m away from roads. Giant panda habitat and common habitat (shared by giant pandas and livestock) did not significantly differ in habitat characteristics, but livestock habitat was significantly different from them in the number of trees and the height of bamboo. Specifically, livestock habitat had more trees and shorter bamboo. Based on the short bamboo located in livestock habitat, we predicted that bamboo in the common habitat has a high probability of being damaged by livestock. To limit solid waste pollution, livestock should be forbidden from entering giant panda habitat. In addition, tourism and infrastructure construction activities should be strictly controlled. To ensure the effectiveness of conservation, the needs and possible contributions of residents in surrounding communities should be taken into account in the giant panda conservation plan, and routine monitoring of solid waste should be performed.

The Transferability of Random Forest in Canopy Height Estimation from Multi-Source Remote Sensing Data

Canopy height is an important forest structure parameter for understanding forest ecosystem and improving global carbon stock quantification accuracy. Light detection and ranging (LiDAR) can provide accurate canopy height measurements, but its application at large scales is limited. Using LiDAR-derived canopy height as ground truth to train the Random Forest (RF) algorithm and therefore predict canopy height from other remotely sensed datasets in areas without LiDAR coverage has been one of the most commonly used method in large-scale canopy height mapping. However, how variances in location, vegetation type, and spatial scale of study sites influence the RF modelling results is still a question that needs to be addressed. In this study, we selected 16 study sites (100 km2 each) with full airborne LiDAR coverage across the United States, and used the LiDAR-derived canopy height along with optical imagery, topographic data, and climate surfaces to evaluate the transferability of the RF-based canopy height prediction method. The results show a series of findings from general to complex. The RF model trained at a certain location or vegetation type cannot be transferred to other locations or vegetation types. However, by training the RF algorithm using samples from all sites with various vegetation types, a universal model can be achieved for predicting canopy height at different locations and different vegetation types with self-predicted R2 higher than 0.6 and RMSE lower than 6 m. Moreover, the influence of spatial scales on the RF prediction accuracy is noticeable when spatial extent of the study site is less than 50 km2 or the spatial resolution of the training pixel is finer than 500 m. The canopy height prediction accuracy increases with the spatial extent and the targeted spatial resolution.

Dietary flexibility of Bale monkeys (Chlorocebus djamdjamensis) in southern Ethiopia: effects of habitat degradation and life in fragments

BACKGROUND

Understanding the effects of habitat modification on the feeding strategies of threatened species is essential to designing effective conservation management plans. Bale monkeys (Chlorocebus djamdjamensis) are endemic to the rapidly shrinking montane forests of the southern Ethiopian Highlands. Most populations inhabit continuous bamboo forest subsisting largely on the young leaves and shoots of a single species of bamboo. Because of habitat disturbance in recent decades, however, there are now also several dozen small populations inhabiting isolated forest fragments where bamboo has been degraded. During 12-months, we assessed Bale monkey responses to habitat degradation by comparing habitat composition, phenological patterns, and feeding ecology in a largely undisturbed continuous forest (Continuous groups A and B) and in two fragments (Patchy and Hilltop groups).

RESULTS

We found that habitat quality and food availability were much lower in fragments than in continuous forest. In response to the relative scarcity of bamboo in fragments, Bale monkeys spent significantly less time feeding on the young leaves and shoots of bamboo and significantly more time feeding on non-bamboo young leaves, fruits, seeds, stems, petioles, and insects in fragments than in continuous forest. Groups in fragments also broadened their diets to incorporate many more plant species (Patchy: ≥ 47 and Hilltop: ≥ 35 species)-including several forbs, graminoids and cultivated crops-than groups in continuous forest (Continuous A: 12 and Continuous B: 8 species). Nevertheless, bamboo was still the top food species for Patchy group (30% of diet) as well as for both continuous forest groups (mean = 81%). However, in Hilltop group, for which bamboo was especially scarce, Bothriochloa radicans (Poaceae), a grass, was the top dietary species (15% of diet) and bamboo ranked 10th (2%).

CONCLUSIONS

We demonstrate that Bale monkeys are more dietarily flexible than previously thought and able to cope with some degradation of their primary bamboo forest habitat. However, crop raiding and other terrestrial foraging habits more common among fragment groups may place them at greater risk of hunting by humans. Thus, longitudinal monitoring is necessary to evaluate the long-term viability of Bale monkey populations in fragmented habitats.

The minimum area requirements (MAR) for giant panda: an empirical study

Habitat fragmentation can reduce population viability, especially for area-sensitive species. The Minimum Area Requirements (MAR) of a population is the area required for the population's long-term persistence. In this study, the response of occupancy probability of giant pandas against habitat patch size was studied in five of the six mountain ranges inhabited by giant panda, which cover over 78% of the global distribution of giant panda habitat. The probability of giant panda occurrence was positively associated with habitat patch area, and the observed increase in occupancy probability with patch size was higher than that due to passive sampling alone. These results suggest that the giant panda is an area-sensitive species. The MAR for giant panda was estimated to be 114.7 km² based on analysis of its occupancy probability. Giant panda habitats appear more fragmented in the three southern mountain ranges, while they are large and more continuous in the other two. Establishing corridors among habitat patches can mitigate habitat fragmentation, but expanding habitat patch sizes is necessary in mountain ranges where fragmentation is most intensive.

Spatial assessment of attitudes toward tigers in Nepal

In many regions around the world, wildlife impacts on people (e.g., crop raiding, attacks on people) engender negative attitudes toward wildlife. Negative attitudes predict behaviors that undermine wildlife management and conservation efforts (e.g., by exacerbating retaliatory killing of wildlife). Our study (1) evaluated attitudes of local people toward the globally endangered tiger (Panthera tigris) in Nepal's Chitwan National Park; and (2) modeled and mapped spatial clusters of attitudes toward tigers. Factors characterizing a person's position in society (i.e., socioeconomic and cultural factors) influenced attitudes toward tigers more than past experiences with tigers (e.g., livestock attacks). A spatial cluster of negative attitudes toward tigers was associated with concentrations of people with less formal education, people from marginalized ethnic groups, and tiger attacks on people. Our study provides insights and descriptions of techniques to improve attitudes toward wildlife in Chitwan and many regions around the world with similar conservation challenges.

Nonlinear effects of group size on collective action and resource outcomes

For decades, scholars have been trying to determine whether small or large groups are more likely to cooperate for collective action and successfully manage common-pool resources. Using data gathered from the Wolong Nature Reserve since 1995, we examined the effects of group size (i.e., number of households monitoring a single forest parcel) on both collective action (forest monitoring) and resource outcomes (changes in forest cover) while controlling for potential confounding factors. Our results demonstrate that group size has nonlinear effects on both collective action and resource outcomes, with intermediate group size contributing the most monitoring effort and leading to the biggest forest cover gain. We also show how opposing effects of group size directly and indirectly affect collective action and resource outcomes, leading to the overall nonlinear relationship. Our findings suggest why previous studies have observed differing and even contradictory group-size effects, and thus help guide further research and governance of the commons. The findings also suggest that it should be possible to improve collective action and resource outcomes by altering factors that lead to the nonlinear group-size effect, including punishing free riding, enhancing overall and within-group enforcement, improving social capital across groups and among group members, and allowing self-selection during the group formation process so members with good social relationships can form groups autonomously.

Giant panda habitat networks and conservation: is this species adequately protected?

Context. Giant pandas (Ailuropoda melanoleuca) are restricted to six mountain ranges at the edge of the Tibetan Plateau. One of these ranges, the Qinling Mountains, contains the highest density of giant pandas and is home to ~20% of those remaining in the wild. Commercial logging and other developments have resulted in habitat fragmentation, and an efficient and powerful conservation network is now needed for the species in this area. Aims. This study sought to assess giant panda habitat and estimate the carrying capacity of this reserve network. Our goal was to improve the function and carrying capacity of the reserve network and facilitate population growth and gene flow among subpopulations of giant pandas. Methods. We use habitat suitability models to assess the efficacy of conservation networks. With estimation of carrying capacity by home range, we can reveal issues facing reserves and populations of endangered species they contain. Here, we define key habitat, linkages, corridors and overall connectivity and then use habitat network modelling and spatial analyses to design a conservation landscape for giant pandas across their Qinling Mountains stronghold. Key results. We found that 91% of giant panda sightings were in suitable or marginally suitable habitat. The total area of giant panda habitat present in the Qinling Mountains is ~1600 km2 fragmented across four key habitat blocks by national roads or other human activity. The current nature reserve network encompasses 71% of available suitable habitat and 62% of available marginal habitat, meaning a significant proportion of panda habitat remains outside the current conservation network. We found that giant panda reserves across this region are not equal in their carrying capacity; some reserves contain an overabundance of giant pandas and the wellbeing of these populations are in doubt. Conclusions. Our results highlight the potential risk of high densities and bamboo flowering events to the safety of giant pandas. With poor population size and heavy isolation, small populations will not persist without translocation. Implication. Redrawing the reserve network to correct localised problems may improve the function of the giant panda protection system, build capacity in the reserve network, and decrease human–wildlife conflict. We propose a new reserve and adjustment of the borders and region for three reserves.

A review of the relationships between human population density and biodiversity

To explore the impacts of increasing human numbers on nature, many studies have examined relationships between human population density (HPD) and biodiversity change. The implicit assumption in many of these studies is that as population density increases so does the threat to biodiversity. The implications of this assumption are compounded by recent research showing that species richness for many taxonomic groups is often highest in areas with high HPD. If increasing HPD is a threat to conservation, this threat may be magnified owing to the spatial congruence between people and species richness. Here, I review the relationships between HPD and measures of biodiversity status focussing in particular on evidence for the spatial congruence between people and species richness and the threat that increasing HPD may pose to biodiversity conservation. The review is split into two major sections: (i) a quantitative assessment of 85 studies covering 401 analyses, including meta-analyses on discrete relationships; and (ii) a discussion of the implications of the quantitative analyses and major issues raised in the literature. Our understanding of the relationships between HPD and biodiversity is skewed by geographic and taxonomic biases in the literature. Most research has been conducted in the Northern Hemisphere and focussed primarily on birds and mammals, largely ignoring relationships with other taxonomic groups. A total of 127 analyses compared HPD with the species richness of particular taxonomic groups. A meta-analysis of these results found a significant positive population correlation indicating that, on average, species-rich regions and human settlements co-occur. However, there was substantial unexplained heterogeneity in these data. Some of this heterogeneity was explained by the size of the sampling unit used by researchers - as this increased so did the strength of the correlation between HPD and species richness. The most convincing result for a taxonomic group was a significant positive population correlation between HPD and bird species richness. Significant positive population correlations were also found for HPD versus the richness of threatened and geographically restricted species. Hence, there is reasonably good evidence for spatial congruence between people and species-rich regions. The reasons for this congruence are only just beginning to be explored, but key mutual drivers appear to include available energy and elevation. The evidence for increasing HPD as a threat to conservation was weak, owing primarily to the extreme heterogeneity in the approaches used to address this issue. There was some suggestion of a positive relationship between HPD and species extinction, but this result should be interpreted with caution owing to the wide diversity of approaches used to measure extinction. Identifying strong links between human development and species extinction is hampered in part by the difficulty of recording extinction events. The most convincing indication of the negative impact of increasing HPD was a significant negative population correlation between density and the size of protected areas. The magnitude and implications of spatial congruence between people and biodiversity are now being explored using the principles of complementarity and irreplaceability. Human development as a threat to conservation is usually assessed within a complex, interdisciplinary modelling framework, although population size is still considered a key factor. Future population growth and expansion of human settlements will present increasing challenges for conserving species-rich regions and maximising the benefits humans gain from nature.

Interactive effects of natural and human disturbances on vegetation dynamics across landscapes

Accurate measures of human effects on landscape processes require consideration of both the direct impacts from human activities and the indirect consequences of the interactions between humans and the landscape. This is particularly evident in systems experiencing regular natural disturbances such as in the mountainous areas of southwestern China, where the remaining population of giant pandas (Ailuropoda melanoleuca) is supported. Here the spatiotemporal patterns of human impacts, forests, and bamboo episodic die-offs combine to determine the distribution of panda habitat. To study the complex interactions of humans and landscapes, we developed an integrated spatiotemporally explicit model of household activities, natural vegetation dynamics, and their impacts on panda habitat. Using this model we examined the direct consequences of local fuelwood collection and household creation on areas of critical giant panda habitat and the indirect impacts when coupled with vegetation dynamics. Through simulations, we found that over the next 30 years household impacts would result in the loss of up to 30% of the habitat relied on by pandas during past bamboo die-offs. The accumulation and spatial distribution of household impacts would also have a considerable indirect influence on the spatial distribution of understory bamboo. While human impacts influence both bamboo die-off and regeneration, over 19% of pre-existing low-elevation bamboo habitat may be lost following an episodic die-off depending on the severity of the impacts and timing of the die-offs. Our study showed not only the importance of the spatial distribution of direct household impacts on habitat, but also the far-reaching effects of the indirect interactions between humans and the landscapes they are modifying.