A practical guide to the application of the IUCN Red List of Ecosystems criteria

A case for stronger integration of physical landscape processes in conservation science and practice

I argue that the dynamic nature of contemporary, landscape-shaping (geomorphic) processes deserves more consideration in conservation science and practice. In an analysis of a sample of fundamental terms related to geomorphology and area-based conservation in the Web of Science, I found that the terms co-occurred in <2% of the analyzed entries (titles, abstracts, and keywords) from 2000 to 2020. This result is indicative of the rather peripheral attention that, more broadly, landscape-shaping processes seem to receive in the conservation literature. Among conservation scientists and practitioners, landforms that define the physical structure of habitat are often perceived as largely static, whereas the consideration of their dynamic adjustments to geomorphic processes is often limited to extreme events. I use examples derived from river-floodplain environments to illustrate strong, multifaceted, and reciprocal interactions between biota and various erosional and depositional processes. These ubiquitous interdependencies clearly demonstrate that geomorphic processes are an integral part of ecosystem dynamics at time scales relevant for conservation. Crucially, erosional and depositional processes modulate many environmental impacts of past and current anthropogenic activities. I conclude that the absence of a more explicit and widespread consideration of geomorphic processes in conservation science and practice is surprising and detrimental to their effectiveness. I call for bolstered efforts among the conservation and geoscience communities to better integrate landscape dynamics within the field of conservation. The rise of the ecosystem-based and social-ecological systems approaches to conservation and the growth of interdisciplinary geoscience branches (e.g., biogeomorphology, ecohydraulics, and geoconservation) will facilitate such an integration.

Systematic review of the uncertainty of coral reef futures under climate change

Climate change impact syntheses, such as those by the Intergovernmental Panel on Climate Change, consistently assert that limiting global warming to 1.5 °C is unlikely to safeguard most of the world's coral reefs. This prognosis is primarily based on a small subset of available models that apply similar 'excess heat' threshold methodologies. Our systematic review of 79 articles projecting coral reef responses to climate change revealed five main methods. 'Excess heat' models constituted one third (32%) of all studies but attracted a disproportionate share (68%) of citations in the field. Most methods relied on deterministic cause-and-effect rules rather than probabilistic relationships, impeding the field's ability to estimate uncertainty. To synthesize the available projections, we aimed to identify models with comparable outputs. However, divergent choices in model outputs and scenarios limited the analysis to a fraction of available studies. We found substantial discrepancies in the projected impacts, indicating that the subset of articles serving as a basis for climate change syntheses may project more severe consequences than other studies and methodologies. Drawing on insights from other fields, we propose methods to incorporate uncertainty into deterministic modeling approaches and propose a multi-model ensemble approach to generating probabilistic projections for coral reef futures.

Beyond central-tendency: If we agree discrete vegetation communities do not exist, should we investigate other methods of clustering?

Clustering is indispensable in the quest for robust vegetation classification schemes that aim to partition, summarise and communicate patterns. However, clustering solutions are sensitive to methods and data and are therefore unstable, a feature that is usually attributed to noise. Viewed through a central-tendency lens, noise is defined as the degree of departure from type, which is problematic since vegetation types are abstractions of continua, and so noise can only be quantified relative to the particular solution at hand. Graph theory models the structure of vegetation data based on the interconnectivity of samples. Through a graph-theoretic lens, the causes of instability can be quantified in absolute terms via the degree of connectivity among objects. We simulated incremental increases in sampling intensity in a dataset over five iterations and assessed classification stability across successive solutions derived using algorithms implementing, respectively, models of central-tendency and interconnectivity. We used logistic regression to model the likelihood of a sample changing groups between iterations as a function of distance to the centroid and degree of interconnectivity. Our results show that the degree to which samples are interconnected is a more powerful predictor of instability than the degree to which they deviate from their nearest centroid. The removal of weakly interconnected samples resulted in more stable classifications, although solutions with many clusters were apparently inherently less stable than those with few clusters, and improvements in stability flowing from the removal of outliers declined as the number of clusters increased. Our results reinforce the fact that clusters abstracted from continuous data are inherently unstable and that the quest for stable, fine-scale classifications from large regional datasets is illusory. Nevertheless, our results show that using models better suited to the analysis of continuous data may yield more stable classifications of the available data.

Multi-temporal ecological niche modeling for bird conservation in the face of climate change scenarios in Caatinga, Brazil

Background

Global shifts in climatic patterns have been recorded over the last decades. Such modifications mainly correspond to increased temperatures and rainfall regime changes, which are becoming more variable and extreme.

Methods

We aimed to evaluate the impact of future changes in climatic patterns on the distribution of 19 endemic or threatened bird taxa of the Caatinga. We assessed whether current protected areas (PAs) are adequate and whether they will maintain their effectiveness in the future. Also, we identified climatically stable areas that might work as refugia for an array of species.

Results

We observed that 84% and 87% of the bird species of Caatinga analyzed in this study will face high area losses in their predicted range distribution areas in future scenarios (RCP4.5 and RCP8.5, respectively). We also observed that the current PAs in Caatinga are ineffective in protecting these species in both present and future scenarios, even when considering all protection area categories. However, several suitable areas can still be allocated for conservation, where there are vegetation remnants and a high amount of species. Therefore, our study paves a path for conservation actions to mitigate current and future extinctions due to climate change by choosing more suitable protection areas.

High-resolution global maps of tidal flat ecosystems from 1984 to 2019

Assessments of the status of tidal flats, one of the most extensive coastal ecosystems, have been hampered by a lack of data on their global distribution and change. Here we present globally consistent, spatially-explicit data of the occurrence of tidal flats, defined as sand, rock or mud flats that undergo regular tidal inundation. More than 1.3 million Landsat images were processed to 54 composite metrics for twelve 3-year periods, spanning four decades (1984–1986 to 2017–2019). The composite metrics were used as predictor variables in a machine-learning classification trained with more than 10,000 globally distributed training samples. We assessed accuracy of the classification with 1,348 stratified random samples across the mapped area, which indicated overall map accuracies of 82.2% (80.0–84.3%, 95% confidence interval) and 86.1% (84.2–86.8%, 95% CI) for version 1.1 and 1.2 of the data, respectively. We expect these maps will provide a means to measure and monitor a range of processes that are affecting coastal ecosystems, including the impacts of human population growth and sea level rise.

Measurement(s)	ecosystem occurrence
Technology Type(s)	earth observation
Sample Characteristic - Environment	tidal flats • coastal wetlands
Sample Characteristic - Location	global

Effects of forest cover on richness of threatened fish species in Japan

Estuaries--one of the most vulnerable ecosystems globally--face anthropogenic threats, including biodiversity loss and the collapse of sustainable fisheries. Determining the factors contributing to the maintenance of estuarine biodiversity, especially that of fish, is vital for promoting estuarine conservation and sustainability. We used environmental DNA metabarcoding analysis to determine fish species composition in 22 estuaries around Japan and measured watershed-scale land-use factors (e.g., population size, urban area percentage, and forest area percentage). We sought to test the hypothesis that the richness of the most vulnerable estuarine fish species (i.e., registered by the Japanese Ministry of the Environment in the national species red-list) is determined by watershed-scale land-use factors. The richness of such species was greater, where forest cover was highest; thus, forest cover contributes to their conservation. The proportion of agriculture cover was associated with low species richness of red-listed fishes (redundancy analysis, adjusted R² = 43.9% of total variance, df = 5, F = 5.3843, p = 0.0001). The number of red-listed species increased from 3 to 11 along a watershed land-use gradient ranging from a high proportion of agriculture cover to a large proportion of forest cover. Furthermore, the results showed that throughout Japan all the examined watersheds that were covered by >74.8% forest had more than the average (6.7 species per site) richness of red-listed fish species. This result can be attributed to the already high average forest cover in Japan of 67.2%. Our results demonstrate how the land use of watersheds can affect the coastal sea environment and its biodiversity and suggest that proper forest management in conjunction with land-use management may be of prime importance for threatened fish species and coastal ecosystems in general.

Forest Ecosystem Fragmentation in Ecuador: Challenges for Sustainable Land Use in the Tropical Andean

Natural ecosystems are declining and fragmenting globally at unprecedented rates. Fragmentation of natural ecosystems leads to decline in functions and services with severe impact on people. In Ecuador, despite establishment of the nationwide ecosystem classification, this baseline information has not been fully exploited to generate a monitoring system for ecosystem changes. Forest ecosystems are altered daily in Ecuador by human impact, but the relationship between forest fragmentation and human land use has not been adequately explored. To provide an overview of how recent forest fragmentation at the national and ecosystem level was affected by practices in human land use, we quantified the degree of forest fragmentation using the forest fragmentation index (FFI). The relationship between the degree of forest ecosystem fragmentation and human land use of 64 natural forest ecosystems was analyzed during the time period 1990 to 2014. At the national level, the expansion of pasture and inhabited area significantly increased forest fragmentation. The regression models based on the FFI value indicated that the forest fragmentation was highly correlated to pastures in forest ecosystems with low, moderate, and high fragmentation in 2014 due to a progressive increase in pastures. This study showed the critical gaps between forest conservation strategies and actual practices in human land use.

A guide to ecosystem models and their environmental applications

Applied ecology has traditionally approached management problems through a simplified, single-species lens. Repeated failures of single-species management have led us to a new paradigm - managing at the ecosystem level. Ecosystem management involves a complex array of interacting organisms, processes and scientific disciplines. Accounting for interactions, feedback loops and dependencies between ecosystem components is therefore fundamental to understanding and managing ecosystems. We provide an overview of the main types of ecosystem models and their uses, and discuss challenges related to modelling complex ecological systems. Existing modelling approaches typically attempt to do one or more of the following: describe and disentangle ecosystem components and interactions; make predictions about future ecosystem states; and inform decision making by comparing alternative strategies and identifying important uncertainties. Modelling ecosystems is challenging, particularly when balancing the desire to represent many components of an ecosystem with the limitations of available data and the modelling objective. Explicitly considering different forms of uncertainty is therefore a primary concern. We provide some recommended strategies (such as ensemble ecosystem models and multi-model approaches) to aid the explicit consideration of uncertainty while also meeting the challenges of modelling ecosystems.

Revised criteria system for a national assessment of threatened habitats in Germany

The Red List of threatened habitat types in Germany was first published in 1994 and it is updated approximately every ten years. In 2017 the third version was published by the German Federal Agency for Nature Conservation. In the course of the revision, the criteria system was also extended. In doing so, an attempt was made to find a compromise between the consideration of international developments that had taken place and existing national requirements. In particular, short-term developments should become visible through the German Red List status. In addition to ‘National long-term Threat’, the valuation now also includes ‘Current Trend’ and ‘Rarity’. Following the IUCN’s approach, the collapse risk is now represented on the basis of several criteria. However, in contrast to the IUCN procedure, where the worst evaluated criterion is determinative for Red List status, in our procedure all criteria are included in the evaluation. To counteract misleading signal-effects for management decisions, all significant criteria have an influence on the resulting German Red List status (RLG). They are combined in an assessment scheme. In order to map the overall risk of loss, both the long-term threat as a historical reference value and furthermore the current trend must have an influence on RLG. As a result, 65% of habitat types have differing risk of loss.

Shifting headlines? Size trends of newsworthy fishes

The shifting baseline syndrome describes a gradual lowering of human cognitive baselines, as each generation accepts a lower standard of resource abundance or size as the new norm. There is strong empirical evidence of declining trends of abundance and body sizes of marine fish species reported from docks and markets. We asked whether these widespread trends in shrinking marine fish are detectable in popular English-language media, or whether news writers, like many marine stakeholders, are captive to shifting baselines. We collected 266 English-language news articles, printed between 1869 and 2015, which featured headlines that used a superlative adjective, such as 'giant', 'huge', or 'monster', to describe an individual fish caught. We combined the reported sizes of the captured fish with information on maximum species-specific recorded sizes to reconstruct trends of relative size (reported size divided by maximum size) of newsworthy fishes over time. We found some evidence of a shifting baseline syndrome in news media over the last 140 years: overall, the relative length of the largest fish worthy of a headline has declined over time. This pattern held for charismatic fish species (e.g. basking sharks, whale sharks, giant mantas), which are now reported in the media at smaller relative lengths than they were near the turn of the 20th century, and for the largest species under high risk of extinction. In contrast, there was no similar trend for pelagic gamefish and oceanic sharks, or for species under lower risk of extinction. While landing any individual of the large-bodied 'megafish' may be newsworthy in part because of their large size relative to other fish species, the 'megafish' covered in our dataset were small relative to their own species-on average only 56% of the species-specific maximum length. The continued use in the English-language media of superlatives to describe fish that are now a fraction of the maximum size they could reach, or a fraction of the size they used to be, does reflect a shifting baseline for some species. Given that media outlets are a powerful tool for shaping public perception and awareness of environmental issues, there is a real concern that such stories might be interpreted as meaning that superlatively large fish still abound.

The role of satellite remote sensing in structured ecosystem risk assessments

The current set of global conservation targets requires methods for monitoring the changing status of ecosystems. Protocols for ecosystem risk assessment are uniquely suited to this task, providing objective syntheses of a wide range of data to estimate the likelihood of ecosystem collapse. Satellite remote sensing can deliver ecologically relevant, long-term datasets suitable for analysing changes in ecosystem area, structure and function at temporal and spatial scales relevant to risk assessment protocols. However, there is considerable uncertainty about how to select and effectively utilise remotely sensed variables for risk assessment. Here, we review the use of satellite remote sensing for assessing spatial and functional changes of ecosystems, with the aim of providing guidance on the use of these data in ecosystem risk assessment. We suggest that decisions on the use of satellite remote sensing should be made a priori and deductively with the assistance of conceptual ecosystem models that identify the primary indicators representing the dynamics of a focal ecosystem.

Diospyros, an under-utilized, multi-purpose plant genus: A review

The genus Diospyros from family Ebenaceae has versatile uses including edible fruits, valuable timber, and ornamental uses. The plant parts of numerous species have been in use as remedies in various folk healing practices, which include therapy for hemorrhage, incontinence, insomnia, hiccough, diarrhea etc. Phytochemical constituents such as terpenoids, ursanes, lupanes, polyphenols, tannins, hydrocarbons, and lipids, benzopyrones, naphthoquinones, oleananes, and taraxeranes have been isolated from different species of this genus. The biological activities of these plants such as antioxidant, anti-inflammatory, analgesic, antipyretic, anti-diabetic, antibacterial, anthelmintic, antihypertensive, cosmeceutical, enzyme-inhibitory etc. have been validated by means of an in vitro, in vivo, and clinical tests. As a rich reserve of pharmacologically important components, this genus can accelerate the pace of drug discovery. Accordingly, the aim of the present review is to survey and summarize the recent literature pertaining to the medicinal and pharmacological uses of Diospyros, and to select experimental evidence on the pharmacological properties of this genus. In addition, the review also aims at identifying areas that need development to make use of this genus, especially its fruit and phytochemicals as means for economic development and for drug discovery.

Assessing the Cost of Global Biodiversity and Conservation Knowledge

Knowledge products comprise assessments of authoritative information supported by standards, governance, quality control, data, tools, and capacity building mechanisms. Considerable resources are dedicated to developing and maintaining knowledge products for biodiversity conservation, and they are widely used to inform policy and advise decision makers and practitioners. However, the financial cost of delivering this information is largely undocumented. We evaluated the costs and funding sources for developing and maintaining four global biodiversity and conservation knowledge products: The IUCN Red List of Threatened Species, the IUCN Red List of Ecosystems, Protected Planet, and the World Database of Key Biodiversity Areas. These are secondary data sets, built on primary data collected by extensive networks of expert contributors worldwide. We estimate that US$160 million (range: US$116–204 million), plus 293 person-years of volunteer time (range: 278–308 person-years) valued at US$ 14 million (range US$12–16 million), were invested in these four knowledge products between 1979 and 2013. More than half of this financing was provided through philanthropy, and nearly three-quarters was spent on personnel costs. The estimated annual cost of maintaining data and platforms for three of these knowledge products (excluding the IUCN Red List of Ecosystems for which annual costs were not possible to estimate for 2013) is US$6.5 million in total (range: US$6.2–6.7 million). We estimated that an additional US$114 million will be needed to reach pre-defined baselines of data coverage for all the four knowledge products, and that once achieved, annual maintenance costs will be approximately US$12 million. These costs are much lower than those to maintain many other, similarly important, global knowledge products. Ensuring that biodiversity and conservation knowledge products are sufficiently up to date, comprehensive and accurate is fundamental to inform decision-making for biodiversity conservation and sustainable development. Thus, the development and implementation of plans for sustainable long-term financing for them is critical.