High and Far: Biases in the Location of Protected Areas

BACKGROUND: About an eighth of the earth's land surface is in protected areas (hereafter "PAs"), most created during the 20(th) century. Natural landscapes are critical for species persistence and PAs can play a major role in conservation and in climate policy. Such contributions may be harder than expected to implement if new PAs are constrained to the same kinds of locations that PAs currently occupy. METHODOLOGY/PRINCIPAL FINDINGS: Quantitatively extending the perception that PAs occupy "rock and ice", we show that across 147 nations PA networks are biased towards places that are unlikely to face land conversion pressures even in the absence of protection. We test each country's PA network for bias in elevation, slope, distances to roads and cities, and suitability for agriculture. Further, within each country's set of PAs, we also ask if the level of protection is biased in these ways. We find that the significant majority of national PA networks are biased to higher elevations, steeper slopes and greater distances to roads and cities. Also, within a country, PAs with higher protection status are more biased than are the PAs with lower protection statuses. CONCLUSIONS/SIGNIFICANCE: In sum, PAs are biased towards where they can least prevent land conversion (even if they offer perfect protection). These globally comprehensive results extend findings from nation-level analyses. They imply that siting rules such as the Convention on Biological Diversity's 2010 Target [to protect 10% of all ecoregions] might raise PA impacts if applied at the country level. In light of the potential for global carbon-based payments for avoided deforestation or REDD, these results suggest that attention to threat could improve outcomes from the creation and management of PAs

How many species of flowering plants are there?

We estimate the probable number of flowering plants. First, we apply a model that explicitly incorporates taxonomic effort over time to estimate the number of as-yet-unknown species. Second, we ask taxonomic experts their opinions on how many species are likely to be missing, on a family-by-family basis. The results are broadly comparable. We show that the current number of species should grow by between 10 and 20 per cent. There are, however, interesting discrepancies between expert and model estimates for some families, suggesting that our model does not always completely capture patterns of taxonomic activity. The as-yet-unknown species are probably similar to those taxonomists have described recently—overwhelmingly rare and local, and disproportionately in biodiversity hotspots, where there are high levels of habitat destruction

Sentiment Analysis of Conservation Studies Captures Successes of Species Reintroductions

Learning from the rapidly growing body of scientific articles is constrained by human bandwidth. Existing methods in machine learning have been developed to extract knowledge from human language and may automate this process. Here, we apply sentiment analysis, a type of natural language processing, to facilitate a literature review in reintroduction biology. We analyzed 1,030,558 words from 4,313 scientific abstracts published over four decades using four previously trained lexicon-based models and one recursive neural tensor network model. We find frequently used terms share both a general and a domain-specific value, with either positive (success, protect, growth) or negative (threaten, loss, risk) sentiment. Sentiment trends suggest that reintroduction studies have become less variable and increasingly successful over time and seem to capture known successes and challenges for conservation biology. This approach offers promise for rapidly extracting explicit and latent information from a large corpus of scientific texts

On Population Growth Near Protected Areas

Background: Protected areas are the first, and often only, line of defense in efforts to conserve biodiversity. They might be detrimental or beneficial to rural communities depending on how they alter economic opportunities and access to natural resources. As such, protected areas may attract or repel human settlement. Disproportionate increases in population growth near protected area boundaries may threaten their ability to conserve biodiversity. Methodology/Principal Findings: Using decadal population datasets, we analyze population growth across 45 countries and 304 protected areas. We find no evidence for population growth near protected areas to be greater than growth of rural areas in the same country. Furthermore, we argue that what growth does occur near protected areas likely results from a general expansion of nearby population centers. Conclusions/Significance: Our results contradict those from a recent study by Wittemyer et al., who claim overwhelming evidence for increased human population growth near protected areas. To understand the disagreement, we re-analyzed the protected areas in Wittemyer et al.’s paper. Their results are simply artifacts of mixing two incompatible datasets. Protected areas may experience unusual population pressures near their edges; indeed, individual case studies provid

Biophysical suitability, economic pressure and land-cover change: a global probabilistic approach and insights for REDD+

There has been a concerted effort by the international scientific community to understand the multiple causes and patterns of land-cover change to support sustainable land management. Here, we examined biophysical suitability, and a novel integrated index of “Economic Pressure on Land” (EPL) to explain land cover in the year 2000, and estimated the likelihood of future land-cover change through 2050, including protected area effectiveness. Biophysical suitability and EPL explained almost half of the global pattern of land cover (R 2 = 0.45), increasing to almost two-thirds in areas where a long-term equilibrium is likely to have been reached (e.g. R 2 = 0.64 in Europe). We identify a high likelihood of future land-cover change in vast areas with relatively lower current and past deforestation (e.g. the Congo Basin). Further, we simulated emissions arising from a “business as usual” and two reducing emissions from deforestation and forest degradation (REDD) scenarios by incorporating data on biomass carbon. As our model incorporates all biome types, it highlights a crucial aspect of the ongoing REDD + debate: if restricted to forests, “cross-biome leakage” would severely reduce REDD + effectiveness for climate change mitigation. If forests were protected from deforestation yet without measures to tackle the drivers of land-cover change, REDD + would only reduce 30 % of total emissions from land-cover change. Fifty-five percent of emissions reductions from forests would be compensated by increased emissions in other biomes. These results suggest that, although REDD + remains a very promising mitigation tool, implementation of complementary measures to reduce land demand is necessary to prevent this leakage

More than a meal… integrating non-feeding interactions into food webs

Organisms eating each other are only one of many types of well documented and important interactions among species. Other such types include habitat modification, predator interference and facilitation. However, ecological network research has been typically limited to either pure food webs or to networks of only a few (<3) interaction types. The great diversity of non-trophic interactions observed in nature has been poorly addressed by ecologists and largely excluded from network theory. Herein, we propose a conceptual framework that organises this diversity into three main functional classes defined by how they modify specific parameters in a dynamic food web model. This approach provides a path forward for incorporating non-trophic interactions in traditional food web models and offers a new perspective on tackling ecological complexity that should stimulate both theoretical and empirical approaches to understanding the patterns and dynamics of diverse species interactions in nature.Keywords: Ecosystem engineering, Non-trophic interactions, Ecological network, Food web, Interaction modification, Facilitation, Trophic interaction

Working paper analysing the economic implications of the proposed 30% target for areal protection in the draft post-2020 Global Biodiversity Framewor

58 pages, 5 figures, 3 tables- The World Economic Forum now ranks biodiversity loss as a top-five risk to the global economy, and the draft post-2020 Global Biodiversity Framework proposes an expansion of conservation areas to 30% of the earth’s surface by 2030 (hereafter the “30% target”), using protected areas (PAs) and other effective area-based conservation measures (OECMs). - Two immediate concerns are how much a 30% target might cost and whether it will cause economic losses to the agriculture, forestry and fisheries sectors. - Conservation areas also generate economic benefits (e.g. revenue from nature tourism and ecosystem services), making PAs/Nature an economic sector in their own right. - If some economic sectors benefit but others experience a loss, high-level policy makers need to know the net impact on the wider economy, as well as on individual sectors. [...]A. Waldron, K. Nakamura, J. Sze, T. Vilela, A. Escobedo, P. Negret Torres, R. Button, K. Swinnerton, A. Toledo, P. Madgwick, N. Mukherjee were supported by National Geographic and the Resources Legacy Fund. V. Christensen was supported by NSERC Discovery Grant RGPIN-2019-04901. M. Coll and J. Steenbeek were supported by EU Horizon 2020 research and innovation programme under grant agreement No 817578 (TRIATLAS). D. Leclere was supported by TradeHub UKRI CGRF project. R. Heneghan was supported by Spanish Ministry of Science, Innovation and Universities, Acciones de Programacion Conjunta Internacional (PCIN-2017-115). M. di Marco was supported by MIUR Rita Levi Montalcini programme. A. Fernandez-Llamazares was supported by Academy of Finland (grant nr. 311176). S. Fujimori and T. Hawegawa were supported by The Environment Research and Technology Development Fund (2-2002) of the Environmental Restoration and Conservation Agency of Japan and the Sumitomo Foundation. V. Heikinheimo was supported by Kone Foundation, Social Media for Conservation project. K. Scherrer was supported by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme under grant agreement No 682602. U. Rashid Sumaila acknowledges the OceanCanada Partnership, which funded by the Social Sciences and Humanities Research Council of Canada (SSHRC). T. Toivonen was supported by Osk. Huttunen Foundation & Clare Hall college, Cambridge. W. Wu was supported by The Environment Research and Technology Development Fund (2-2002) of the Environmental Restoration and Conservation Agency of Japan. Z. Yuchen was supported by a Ministry of Education of Singapore Research Scholarship Block (RSB) Research FellowshipPeer reviewe

Broad Scale Conservation: Protected Areas and Species Interactions

<p>This dissertation consists of four chapters. The first three chapters examine protected areas (or parks) from multiple perspectives. Parks are the first, and often only, line of defense in efforts to conserve biodiversity. Understanding of their promise and problems is necessary to achieve conservation outcomes. Chapter One determines vegetation patterns in and around parks of differing management categories across the Amazon, Congo, South American Atlantic Coast, and West African forests. Within these forests, protected areas are the principle defense against forest loss and species extinctions. In the Amazon and Congo, parks are generally large and retain high levels of forest cover, as do their surroundings. In contrast, parks in the Atlantic Coast forest and West Africa show sharp boundaries in forest cover at their edges. This effective protection of forest cover is partially offset by their very small size: little area is deep inside park boundaries. Compared to West Africa, areas outside parks in the Atlantic Coast forest are unusually fragmented. </p><p>Chapter Two addresses a human dimension of protected areas. Given certain characteristics, parks areas may either attract or repel human settlement. Disproportionate increases in population growth near park boundaries may threaten their ability to conserve biodiversity. Using decadal population datasets, we analyze population growth across 45 countries and 304 parks. We find no evidence for population growth near parks to be greater than growth of rural areas in the same country. Furthermore, we argue that what growth does occur near parks likely results from a general expansion of nearby population centers. Parks may experience unusual population pressures near their edges; indeed, individual case studies provide examples. There is no evidence, however, of a general pattern of disproportionate population growth near their boundaries.</p><p>Chapter Three provides a review of common approaches to evaluating protection's impact on deforestation, identifies three hurdles to empirical evaluation, and notes that matching techniques from economic impact evaluation address those hurdles. The central hurdle derives from the fact that protected areas are distributed non-randomly across landscapes. Matching controls for landscape characteristics when inferring the impact of protection. Applications of matching have revealed considerably lower impact estimates of forest protection than produced by other methods. These results indicate the importance of variation across locations in how much impact protection could possibly have on rates of deforestation.</p><p>Chapter Four departs from the focus of protected areas and instead addresses a more theoretical aspect of community ecology. Ecological theories suggest that food webs might consist of groups of species forming blocks, compartments or guilds. Chapter Four considers ecological networks (subsets of complete food webs) involving species at adjacent trophic levels. Reciprocal specializations occur when (say) a pollinator (or group of pollinators) specializes on a particular flower species (or group of such species) and vice versa. We characterize the level of reciprocal specialization for various classes of networks. Our analyses include both antagonistic interactions (particularly parasitoids and their hosts), and mutualistic ones (such as insects and the flowers that they pollinate). We also examine whether trophic patterns might be palimpsests. That is, there might be reciprocal specialization within taxonomically related species within a network, but these might be obscured when these relationships are combined. Reciprocal specializations are rare in all these systems even when tested using the most conservative null model.</p>Dissertatio

How many endangered species remain to be discovered in Brazil?

How many species are likely as-yet unknown to science? Even in relatively well-known groups, there may be substantial numbers of such species. It seems likely that these unknown species will be rare and threatened with extinction. Indeed, science may not discover them before they go extinct. We address these issues for a sample of endemic flowering plants and three vertebrate groups: amphibians, birds, and mammals, all from Brazil. We predict the likely numbers of missing species from models of the declining numbers of species described per five-year interval. The raw numbers increase over time, so we must scale these by the taxonomic effort. We show that while the catalogues of birds and mammals are nearly complete, the numbers of amphibians may increase by 15% and the numbers of endemic plants by ~10 to ~50% depending on region. These percentages may still seem encouragingly low, given the complexities of studying a country as large as Brazil, with its extraordinary diversity, and with many of its regions large and still poorly explored. What is more worrying is that these numbers of as-yet unknown species are broadly the same as the percentages of species that are presently considered threatened with extinction. That is, we know only half of the species in danger of extinction - and our knowledge of even those species has mostly been acquired in the last three decades. © 2010 ABECO

Modeling the building blocks of biodiversity.

BACKGROUND: Networks of single interaction types, such as plant-pollinator mutualisms, are biodiversity's "building blocks". Yet, the structure of mutualistic and antagonistic networks differs, leaving no unified modeling framework across biodiversity's component pieces. METHODS/PRINCIPAL FINDINGS: We use a one-dimensional "niche model" to predict antagonistic and mutualistic species interactions, finding that accuracy decreases with the size of the network. We show that properties of the modeled network structure closely approximate empirical properties even where individual interactions are poorly predicted. Further, some aspects of the structure of the niche space were consistently different between network classes. CONCLUSIONS/SIGNIFICANCE: These novel results reveal fundamental differences between the ability to predict ecologically important features of the overall structure of a network and the ability to predict pair-wise species interactions