Linking democracy and biodiversity conservation: Empirical evidence and research gaps

Role of national regime ideology for predicting biodiversity outcomes

The rapid decline of global biodiversity has engendered renewed debate about the social, economic, and political factors contributing to it. Specifically, there is little understanding of the role that political ideology within a country (e.g., nationalism, conservatism, socialism) plays in determining biodiversity outcomes. We used negative binomial generalized linear models to investigate the importance of national regime ideology in predicting threatened animal species and protected area establishment compared with other factors that affect biodiversity outcomes, such as gross domestic product, inequality, and democracy. For threatened animals, the model with the highest Akaike weight suggested adverse biodiversity outcomes arose from larger gross domestic product (β = 0.120, p < 0.001). However, nationalism (β = 0.371, p < 0.01) and socialism (β = 0.293, p < 0.05) were also significantly associated with increased proportions of threatened species. For protected areas, the model with the highest Akaike weight suggested increases in democracy (β = 0.880, p < 0.001) led to a rise in relative protected area estate. Conservative regime ideology was also associated with greater protected area estate, although this did not increase the weight of evidence in support of the best models. These findings highlight the relevance of political ideology for predicting biodiversity outcomes at a national scale and illustrate opportunities to tailor policies and advocacy to promote biodiversity conservation more effectively. By targeting appropriate messaging and political advocacy, conservationists can improve the likelihood that politicians and their nations will participate in positive biodiversity actions.

A global assessment of the Raunkiaeran shortfall in plants: geographic biases in our knowledge of plant traits

This article is part of the Special Collection ‘Global plant diversity and distribution’. See https://www.newphytologist.org/global-plant-diversity for more details.

Energy justice, democracy and deforestation

This paper contributes to the debate on the determinants of deforestation, a menace that is posing threat to sustainable development particularly in tropical developing regions. Specifically, the paper focuses on the effect of energy justice and democratization. The main contribution to the literature hinges on the emphasis on energy justice - operationalized as rural-urban equality in access to electricity and clean fuels and technologies for cooking - and its interaction with democracy. Using a panel data of 47 sub-Saharan African countries over the period 2000-2020 and the dynamic two-step generalized method of moment estimator, the results generally indicate that improvement in rural-urban equality in access to electricity and clean fuels and technologies for cooking is associated with a reduction in deforestation. Democracy is similarly found to be associated with reduction in deforestation. The conditional effect analysis largely depicts an intensified reducing effect of energy justice on deforestation in the presence of improved democratic practices. The results though robust to an alternative estimator, the Driscoll-Kraay estimator, differ when sub-regional analysis is considered. The paper aligns with the Sustainable Development Goals, particularly Goals 7, 13, 15 and 16.

Biodiversity Research in Central America: A Regional Comparison in Scientific Production Using Bibliometrics and Democracy Indicators

Central America science production on biodiversity topics is important in planning future adaptive and conservation policies in a climate-related risk region that is considered a biodiversity hotspot but has the lowest Human Development Index of Latin America. Science production on biodiversity is related to geo-referenced species occurrence records, but the accessibility depends on political frameworks and science funding. This paper aims at foregrounding how the democratic shifts throughout the years have had an impact on science production on biodiversity research, and species records. For this exploration we developed a novel systematic scientometric analysis of science production on biodiversity topics, we used Bio-Dem (open-source software of biodiversity records and socio-political variables) and briefly analyzed the history—from 1980 to 2020—of Guatemala, El Salvador, Honduras, Nicaragua, Costa Rica, and Panama. With a data set of 16,304 documents, our analysis shows the significant discrepancies between the low science production of Central American Northern countries (Guatemala, El Salvador, Honduras, and Nicaragua), the prolific production from the Southern (Costa Rica and Panama), and how this relates to democratic stability. Scientific production tends to be more abundant when democratic conditions are guaranteed. The state capture phenomenon and colonial-rooted interactions worldwide have an effect on the conditions under which science is being produced in Central America. Democracy, science production, funding, and conservation are core elements that go hand in hand, and that need to be nourished in a region that struggles with the protection of life and extractive activities in a climate change scenario.

Impact of climate change on biodiversity loss: global evidence

The present study investigates the impact of climate change on biodiversity loss using global data consisting of 115 countries. In this study, we measure biodiversity loss using data on the total number of threatened species of amphibians, birds, fishes, mammals, mollusks, plants, and reptiles. The data were compiled from the Red List published by the International Union for Conservation of Nature (IUCN). For climate change variables, we have included temperature, precipitation, and the number of natural disaster occurrences. As for the control variable, we have considered governance indicator and the level of economic development. By employing ordinary least square with robust standard error and robust regression (M-estimation), our results suggest that all three climate change variables - temperature, precipitation, and the number of natural disasters occurrences - increase biodiversity loss. Higher economic development also impacted biodiversity loss positively. On the other hand, good governance such as the control of corruption, regulatory quality, and rule of law reduces biodiversity loss. Thus, practicing good governance, promoting conservation of the environment, and the control of greenhouse gasses would able to mitigate biodiversity loss.

Safeguarding marine life: conservation of biodiversity and ecosystems

Marine ecosystems and their associated biodiversity sustain life on Earth and hold intrinsic value. Critical marine ecosystem services include maintenance of global oxygen and carbon cycles, production of food and energy, and sustenance of human wellbeing. However marine ecosystems are swiftly being degraded due to the unsustainable use of marine environments and a rapidly changing climate. The fundamental challenge for the future is therefore to safeguard marine ecosystem biodiversity, function, and adaptive capacity whilst continuing to provide vital resources for the global population. Here, we use foresighting/hindcasting to consider two plausible futures towards 2030: a business-as-usual trajectory (i.e. continuation of current trends), and a more sustainable but technically achievable future in line with the UN Sustainable Development Goals. We identify key drivers that differentiate these alternative futures and use these to develop an action pathway towards the desirable, more sustainable future. Key to achieving the more sustainable future will be establishing integrative (i.e. across jurisdictions and sectors), adaptive management that supports equitable and sustainable stewardship of marine environments. Conserving marine ecosystems will require recalibrating our social, financial, and industrial relationships with the marine environment. While a sustainable future requires long-term planning and commitment beyond 2030, immediate action is needed to avoid tipping points and avert trajectories of ecosystem decline. By acting now to optimise management and protection of marine ecosystems, building upon existing technologies, and conserving the remaining biodiversity, we can create the best opportunity for a sustainable future in 2030 and beyond.

Safeguarding marine life: conservation of biodiversity and ecosystems

Marine ecosystems and their associated biodiversity sustain life on Earth and hold intrinsic value. Critical marine ecosystem services include maintenance of global oxygen and carbon cycles, production of food and energy, and sustenance of human wellbeing. However marine ecosystems are swiftly being degraded due to the unsustainable use of marine environments and a rapidly changing climate. The fundamental challenge for the future is therefore to safeguard marine ecosystem biodiversity, function, and adaptive capacity whilst continuing to provide vital resources for the global population. Here, we use foresighting/hindcasting to consider two plausible futures towards 2030: a business-as-usual trajectory (i.e. continuation of current trends), and a more sustainable but technically achievable future in line with the UN Sustainable Development Goals. We identify key drivers that differentiate these alternative futures and use these to develop an action pathway towards the desirable, more sustainable future. Key to achieving the more sustainable future will be establishing integrative (i.e. across jurisdictions and sectors), adaptive management that supports equitable and sustainable stewardship of marine environments. Conserving marine ecosystems will require recalibrating our social, financial, and industrial relationships with the marine environment. While a sustainable future requires long-term planning and commitment beyond 2030, immediate action is needed to avoid tipping points and avert trajectories of ecosystem decline. By acting now to optimise management and protection of marine ecosystems, building upon existing technologies, and conserving the remaining biodiversity, we can create the best opportunity for a sustainable future in 2030 and beyond.

Improvements in reports of species redistribution under climate change are required

Studies have documented climate change-induced shifts in species distributions but uncertainties associated with data and methods are typically unexplored. We reviewed 240 reports of climate-related species-range shifts and classified them based on three criteria. We ask whether observed distributional shifts are compared against random expectations, whether multicausal factors are examined on equal footing, and whether studies provide sufficient documentation to enable replication. We found that only ~12.1% of studies compare distributional shifts across multiple directions, ~1.6% distinguish observed patterns from random expectations, and ~19.66% examine multicausal factors. Last, ~75.5% of studies report sufficient data and results to allow replication. We show that despite gradual improvements over time, there is scope for raising standards in data and methods within reports of climate-change induced shifts in species distribution. Accurate reporting is important because policy responses depend on them. Flawed assessments can fuel criticism and divert scarce resources for biodiversity to competing priorities.

Mapping Africa's Biodiversity: More of the Same Is Just Not Good Enough

Species distribution data are fundamental to the understanding of biodiversity patterns and processes. Yet, such data are strongly affected by sampling biases, mostly related to site accessibility. The understanding of these biases is therefore crucial in systematics, biogeography, and conservation. Here we present a novel approach for quantifying sampling effort and its impact on biodiversity knowledge, focusing on Africa. In contrast to previous studies assessing sampling completeness (percentage of species recorded in relation to predicted), we investigate whether the lack of knowledge of a site attracts scientists to visit these areas and collect samples of species. We then estimate the time required to sample 90% of the continent under a Weibull distributed biodiversity sampling rate and the number of sampling events required to record $ \ge $50% of the species. Using linear and spatial regression models, we show that previous sampling has been strongly influencing the resampling of areas, attracting repeated visits. This bias has existed for over two centuries, has increased in recent decades, and is most pronounced among mammals. It may take between 172 and 274 years, depending on the group, to achieve at least one sampling event per grid cell in the entire continent. Just one visit will, however, not be enough: in order to record $ \ge $50% of the current diversity, it will require at least 12 sampling events for amphibians, 13 for mammals, and 27 for birds. Our results demonstrate the importance of sampling areas that lack primary biodiversity data and the urgency with which this needs to be done. Current practice is insufficient to adequately classify and map African biodiversity; it can lead to incorrect conclusions being drawn from biogeographic analyses and can result in misleading and self-reinforcing conservation priorities. [Amphibians; birds; mammals; sampling bias; sampling gaps; Wallacean shortfall.].

Data for Politics: Creating an International Research Infrastructure Measuring Democracy

Questions such as how democratic a country is, how free are its media, or how independent is its judiciary are highly important to researchers and decision makers. We describe a research infrastructure that produces the world's largest dataset on democracy, governance, human rights, and related topics. The dataset is far more resolved and accurate than previous efforts, currently covers 202 political units from 1789 until the present, and is regularly updated each spring. The infrastructure involves an online survey of over 3,000 experts from 180 countries. Survey design and advanced statistical techniques are crucial for assuring data validity. The infrastructure also provides reports and analyses based on the data and easy-to-use tools for exploring and graphing the data.