Globally, urbanization is increasing at an unprecedented rate at the cost of agricultural and forested lands in peri-urban areas fringing larger cities. Such land-cover change generally entails negative implications for societal and environmental sustainability, particularly in South Asia, where high demographic growth and poor land-use planning combine. Analyzing historical land-use change and predicting the future trends concerning urban expansion may support more effective land-use planning and sustainable outcomes. For Nepal’s Tarai region—a populous area experiencing land-use change due to urbanization and other factors—we draw on Landsat satellite imagery to analyze historical land-use change focusing on urban expansion during 1989–2016 and predict urban expansion by 2026 and 2036 using artificial neural network (ANN) and Markov chain (MC) spatial models based on historical trends. Urban cover quadrupled since 1989, expanding by 256 km² (460%), largely as small scattered settlements. This expansion was almost entirely at the expense of agricultural conversion (249 km²). After 2016, urban expansion is predicted to increase linearly by a further 199 km² by 2026 and by another 165 km² by 2036, almost all at the expense of agricultural cover. Such unplanned loss of prime agricultural lands in Nepal’s fertile Tarai region is of serious concern for food-insecure countries like Nepal.

The energy demand in Indonesia has increased significantly with its population growth, urbanization, and economic development. The growing concern of meeting energy demand while reducing dependency on fossil fuels has resulted in an increasing demand for renewable energy. As a country with a rich biomass base, bioenergy is now an important component of Indonesia’s energy agenda. However, a crucial problem in bioenergy production is the selection of species that can provide a sustainable supply of feedstock without having an impact on food security and the environment. In this context, we discuss the characteristics and benefits of using bamboo, a perennial grass, as a potential species for bioenergy feedstock in Indonesia. We describe the fuel characteristics of bamboo along with the possibility to align its cultivation, production, and usage with environmental and developmental agendas which makes it a suitable bioenergy crop in the country. In addition, its ability to grow on degraded lands, fast growth, long root system, and easy maintenance prove it as a powerful ally for the restoration of degraded land. We recommend in-depth research on the social, ecological, and economic feasibility of using this species for bioenergy production.

Background: Establishing protected areas is a key approach to protecting nature. However, protected areas are often biased towards remote and less productive lands. It is important to evaluate the impacts protected areas have had, or in other words, what changes in outcomes of interest are attributable to protected areas. Studies that evaluate the impact of protected areas on vegetation—the state and processes that support biodiversity—are scarce and published in a range of disciplines. This systematic review will scope, identify, and synthesize studies that quantitatively measure the impact of protected areas on vegetation extent and condition. The findings will be useful for researchers and policy makers and provide important knowledge for setting post 2020 targets of the Convention on Biological Diversity. This review will also identify research gaps in the current evidence base and provide direction for future research.Methods: This review follows the Collaboration for Environmental Evidence guidelines for evidence synthesis and complies with the ROSES (RepOrting standards for Systematic Evidence Synthesis) reporting framework. We will use a comprehensive search strategy developed through several rounds of scoping review to cover databases; Web of Science, Scopus and CAB Abstracts, 16 organizational websites, google scholar and existing review documents. Our search terms and strategies aim to find impact evaluation studies (both peer-reviewed and grey literature) in English from protected areas globally. The search results will be screened at title, abstract, and then full text by two independent reviewers. A quality appraisal of evidence will be conducted using Joanna Briggs Institute (JBI) risk of bias tool. Review results will be presented in the form of narrative synthesis, as well as in meta-analysis form, where data quality and amount allow.

Programs to protect biodiversity on private land are increasingly being used worldwide. To understand the efficacy of such programs, it is important to determine their impact: the difference between the program's outcome and what would have happened without the program. Typically, these programs are evaluated by estimating the average program‐level impact, which readily allows comparisons between programs or regions, but masks important heterogeneity in impact across the individual conservation interventions. We used synthetic control design, statistical matching, and time‐series data to estimate the impact of individual protected areas over time and combined individual‐level impacts to estimate program‐level impact with a meta‐analytic approach. We applied the method to private protected areas governed by conservation covenants (legally binding on‐title agreements to protect biodiversity) in the Goldfields region of Victoria, Australia using woody vegetation cover as our outcome variable. We compared our results with traditional approaches to estimating program‐level impact based on a subset of covenants that were the same age. Our results showed an overall program‐level impact of a 0.3–0.8% increase in woody vegetation cover per year. However, there was significant heterogeneity in the temporal pattern of impact for individual covenants, ranging from −4 to +7% change in woody vegetation cover per year. Results of our approach were consistent with results based on traditional approaches to estimating program‐level impact. Our study provides a transparent and robust workflow to estimate individual and program‐level impacts of private protected areas.

Globally, private protected areas (PPAs) have become an important tool for biodiversity conservation. While they are expanding in size and number, there is limited evidence on their potential impact on avoiding biodiversity loss, and how this impact compares to the public protected areas (public PAs). The impact of protection is measured as the actual biodiversity outcome within the area protected relative to the hypothetical outcome without protection. To maximise this positive impact, PAs need to be placed strategically on land that both harbours biodiversity and would be at risk of losing some of the biodiversity if it were not protected. We evaluate and compare the locations of PPAs and public PAs relative to random sites of similar governance type, and a range of covariates that capture biodiversity and the risk of biodiversity loss. We utilised data from a national PA database, and high-resolution data on nationally significant threatened species and indicators that capture risk of biodiversity loss at a continental scale in Australia. We find that PPAs tend to target areas of high threatened species richness. However, on average, PPAs are placed in areas that have lower risk of being cleared compared to randomly selected private land. We observe that this bias towards unproductive land is more prominent in PPAs when compared to public PAs. As nations work towards effectively conserving and managing at least 30% of the world’s lands by 2030 under the new Kunming-Montreal Global Biodiversity Framework, it becomes essential to prioritise PAs and PPAs that deliver impacts on avoiding biodiversity loss rather than solely focusing on areas that represent biodiversity.