More than just a (red) list: Over a decade of using South Africa's threatened ecosystems in policy and practice

Botts, Emily A.; Skowno, Andrew; Driver, Amanda; Holness, Stephen; Maze, Kristal; Smith, Tammy; Daniels, Fahiema; Desmet, Philip; Sink, Kerry; Botha, Mark; Nel, Jeanne; Manuel, Jeffrey

doi:10.1016/j.biocon.2020.108559

Cited by 22 publications

(35 citation statements)

References 27 publications

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“…The extensive commercial croplands and urban centers of the central Highveld grasslands, the large rural population (and associated settlements and subsistence croplands) along the east coast, and the croplands of the lowlands of the Western Cape [10] have reduced the geographical extent of many ecosystem types, and introduced a range of threatening processes and biotic disruption. Despite the acknowledged lack of detailed spatial data on ecosystem integrity (which, if available, would certainly improve the assessment of the arid interior rangelands), the overall pattern aligns with the findings of previous ecosystem threat assessments' efforts [9].…”

Section: Threatened Ecosystems In South Africasupporting

confidence: 71%

“…A set of regulations are followed for planning (Guidelines for the development of bioregional plans, 2009), for reactive decision making (Environmental Impact Assessment Regulations, 2010), and for management (Environmental Management Framework Regulations, 2011). The first list of threatened ecosystems was published in 2011, and the Critically Endangered and Endangered ecosystems on the list started receiving additional protection through the requirement that developments affecting these types required additional and costly specialist studies [9]. The 2011 list included 53 CR and 64 EN types, which is similar to the number identified in 2021 (51 and 55) but with substantial differences in spatial patterns.…”

Section: Moving From a Technical Assessment To A Policy-relevant Conservation Toolmentioning

confidence: 99%

“…Prior to the development of the IUCN RLE, the South African list of threatened ecosystems was conceptualised as a national indicator of ecosystem conservation status in the early 2000s. From its early applications as a project-based indicator, it progressed into a legislated national listing of threatened terrestrial ecosystems [8,9], which entrenched its use in land-use planning and decision-making (e.g., through the Environmental Impact Assessment processes). The National Environmental Management: Biodiversity Act (Act No.…”

Section: Introductionmentioning

confidence: 99%

“…This is equivalent to species extinction in the Red List of Species, and is defined operationally as a 'transformation of identity, loss of defining abiotic or biotic features and characteristic native biota are no longer sustained' [2,13]. The South African ecosystem threat status indicator, which preceded the RLE [9], shared these concepts and as a result, the lists of threatened ecosystems are broadly comparable.…”

Section: Introductionmentioning

confidence: 99%

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South Africa’s Red List of Terrestrial Ecosystems (RLEs)

Skowno

Monyeki

2021

Land

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Ecosystem level indicators are emerging as important pillars of the post-2020 global biodiversity framework of the Convention on Biological Diversity; at the same time, the IUCN Red List of Ecosystems (RLEs) is experiencing rapid global uptake. We applied a systematic RLE assessment to 456 terrestrial ecosystems in South Africa between 2017 and 2021. What sets South Africa apart in this endeavour is that an independently formulated ecosystem threat status indicator was developed between 2004 and 2008 and the list of threatened ecosystems (effectively a proto RLE) was integrated into the national environmental regulatory framework in 2011. Through this, Critically Endangered and Endangered types were afforded a form of statutory protection through increased regulation of land-use change activities. We describe the transition to the IUCN RLE framework and focus on both the technical steps of incorporating the best available data into a credible assessment, and the unique social and legal processes to ensure that the biodiversity conservation sector in South Africa understood and supported the proposed replacement of the existing list of threatened ecosystems (2011) with the RLE (2021). We discuss the policy development steps required in South Africa, and the pros and cons of maintaining a legislative link for RLE implementation.

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Section: Threatened Ecosystems In South Africasupporting

confidence: 71%

Section: Moving From a Technical Assessment To A Policy-relevant Conservation Toolmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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South Africa’s Red List of Terrestrial Ecosystems (RLEs)

Skowno

Monyeki

2021

Land

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“…This additional information provides valuable insights which are useful for managing threats and promoting ecosystem function in threatened ecosystems, and thus should not be ignored as ecosystem threat assessments are often used to inform policy and management of ecosystems (Botts et al . 2020).…”

Section: Discussionmentioning

confidence: 99%

Assessing the threat of landscape transformation and habitat fragmentation in a global biodiversity hotspot

2021

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Habitat loss and habitat fragmentation are amongst the major drivers of biodiversity loss globally. Although habitat fragmentation poses additional threats to biodiversity beyond habitat loss alone, the IUCN’s Red List of Ecosystems (RLE) does not provide guidance on how to assess these threats. This study develops an approach for incorporating habitat fragmentation into the RLE threat assessment and investigates additional insights such an analysis could provide beyond the analysis of distribution trends. This is achieved by quantifying RLE criteria A and B (distribution reduction, restricted distribution and decline) and comparing outcomes with indices of habitat fragmentation (core area, Largest Patch Index, Patch Cohesion Index and Aggregation Index) in the Cape Floristic Region of South Africa. Results revealed that much of the Cape Floristic Region is severely threatened by both landscape transformation and habitat fragmentation, but that treating the habitat fragmentation indices as additional RLE criteria did not alter the ecosystem threat assessment outcomes. Whilst this suggests that the existing RLE criteria implicitly account for habitat fragmentation, the relationship between fragmentation indices and RLE criteria were weak and highly variable in some cases, indicating that the RLE criteria alone do not sufficiently account for the threat of habitat fragmentation. Supplementing the RLE with habitat fragmentation measures highlights additional, unique information on threats to ecosystems. This simple approach has the potential to assist in setting conservation priorities and management goals, particularly in fragmented ecosystems.

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

Tozer,

Keith

2023

Ecology and Evolution

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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.

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More than just a (red) list: Over a decade of using South Africa's threatened ecosystems in policy and practice

Cited by 22 publications

References 27 publications

South Africa’s Red List of Terrestrial Ecosystems (RLEs)

South Africa’s Red List of Terrestrial Ecosystems (RLEs)

Assessing the threat of landscape transformation and habitat fragmentation in a global biodiversity hotspot

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

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