Red List of Ecosystems assessment 743


TABLE 2(Cont.) Indicator data & analysis applied


Criterion E Ice mass balance projections from a global glacier evolution model (Rounce et al., 2022). We calculated the cumu- lative distribution of predicted year of collapse (first year when ice mass reaches zero) for 48 combinations of models & scenarios


Estimates & uncertainty


Probability of collapse during 2020–2070: 79%


Rationale


Uncertainty in mass estimates from replicates does not have a significant effect on the estimated year of col- lapse. The proportion of models that predict collapse by 2070 is higher than 50% in three out of four scenarios


Category of risk


CR (EN-CR)


uncertainty because of the use of indirect indicators and glo- bal instead of local data. During the last 100 years, the freez- ing level height and equilibrium-line altitude have increased close to the point of collapse, and permanent ice has com- pletely disappeared from all previously glaciated peaks ex- cept Humboldt (sub-criteria A1,A3 and C1). The current distribution of glaciated areas ismuch reduced and exposed (sub-criteria B1 and B2), is undergoing rapid decline at a rate similar to the recently disappeared Bolívar glacier and is un- likely to recover mass before its complete collapse (sub- criterion C2a and criterion E). This is the first Red List of Ecosystems assessment of a


tropical glacier ecosystem. Cryogenic ecosystems are often under-represented in national assessments that focus on vegetation units, but despite differences in processes and functions they can be assessed using the same criteria and assigned to comparable categories of risk (Keith et al., 2013). Risk assessments and long-term monitoring of all ecosystems in tropical mountains can provide valuable in- formation for comprehensive conservation planning and ecosystem management in these complex landscapes (Cuesta et al., 2019; Llambí et al., 2020). This quantitative assessment of several symptoms of


collapse illustrates how the Red List of Ecosystems protocol can be applied to other tropical glaciers (and cryogenic ecosystems outside tropical areas) by combining all available evidence within a common framework. We anticipate that similarly isolated and exposed tropical glaciers in Indonesia, East Africa, Mexico and some Andean regions (e.g. Santa Isabel in Colombia, Carihuairazo in Ecuador) will also be at extreme risk of collapse, and the larger region- al units in the tropical Andes may experience widespread decline and degradation (Ceballos et al., 2006; Rabatel et al., 2018; Veettil & Kamp, 2019; Ferrer-Paris & Keith, 2024). The Red List of Ecosystems protocol provides a valuable framework for consistent and comparable assess- ments across all continents that synthesizes local and regional data from geology, climatology, palaeontology/ palynology, microbiology, entomology and soil and vegeta- tion ecology to describe ecosystems and diagnose the threats that they face.


The Red List of Ecosystems assessment explores different


pathways towards collapse, and the associated uncertainty of methods and projections is consolidated within the cat- egories of risk and their plausible bounds. Here we fully exploited this versatility, assessing spatial and functional symptoms, undertaking quantitative risk analysis and con- sidering alternative interpretations of collapse thresholds. Our study shows that the multiple lines of evidence offer a broad picture of threatening processes and pathways to- wards collapse and that the assessment protocol handles several sources of uncertainty (Keith et al., 2013; Bland et al., 2017). Sufficient data are available for the comprehen- sive risk assessment of tropical glacier ecosystems in differ- ent regions of the world, and global datasets and analyses can be used as informative indicators of the climate and cryosphere dynamics that have not been studied locally, with the caveat of the limited ground validation and poten- tial bias of these sources (Sagredo & Lowell, 2012; Rounce et al., 2023). Because of the rapid decline of the icy substrate in recent


decades, the small remnants of ice in Venezuela and on other tropical mountains are often considered static or ex- tinct glaciers because dynamic processes of ice accumula- tion no longer operate and ice loss is accelerated by scale and edge effects (Ceballos et al., 2006; Braun & Bezada, 2013; Rabatel et al., 2018; Ramírez et al., 2020). Despite rapid contraction, the little remaining ice substrate could sustain much of its original microbiota (Ball et al., 2014; Balcazar et al., 2015; Rondón et al., 2016). Studies of the gla- cier forefield at Humboldt Peak provide insights into the postglacial chronosequence: pioneer lichens, mosses and vascular vegetation are already present 10 years after the re- treat of the glacier. However, vascular plants only increase slowly in cover, species and functional diversity during the first 100 years of primary succession, and soil properties (e.g. soil organic matter, total nitrogen and exchangeable bases) change significantly after 21 and 60 years (Llambí et al., 2021).


Although collapse seems imminent and is probably un-


avoidable, we can still learn much from inventories of native biota and monitoring of ecosystem transitions. Multiple


Oryx, 2024, 58(6), 735–745 © The Author(s), 2024. Published by Cambridge University Press on behalf of Fauna & Flora International doi:10.1017/S0030605323001771


Page 1  |  Page 2  |  Page 3  |  Page 4  |  Page 5  |  Page 6  |  Page 7  |  Page 8  |  Page 9  |  Page 10  |  Page 11  |  Page 12  |  Page 13  |  Page 14  |  Page 15  |  Page 16  |  Page 17  |  Page 18  |  Page 19  |  Page 20  |  Page 21  |  Page 22  |  Page 23  |  Page 24  |  Page 25  |  Page 26  |  Page 27  |  Page 28  |  Page 29  |  Page 30  |  Page 31  |  Page 32  |  Page 33  |  Page 34  |  Page 35  |  Page 36  |  Page 37  |  Page 38  |  Page 39  |  Page 40  |  Page 41  |  Page 42  |  Page 43  |  Page 44  |  Page 45  |  Page 46  |  Page 47  |  Page 48  |  Page 49  |  Page 50  |  Page 51  |  Page 52  |  Page 53  |  Page 54  |  Page 55  |  Page 56  |  Page 57  |  Page 58  |  Page 59  |  Page 60  |  Page 61  |  Page 62  |  Page 63  |  Page 64  |  Page 65  |  Page 66  |  Page 67  |  Page 68  |  Page 69  |  Page 70  |  Page 71  |  Page 72  |  Page 73  |  Page 74  |  Page 75  |  Page 76  |  Page 77  |  Page 78  |  Page 79  |  Page 80  |  Page 81  |  Page 82  |  Page 83  |  Page 84  |  Page 85  |  Page 86  |  Page 87  |  Page 88  |  Page 89  |  Page 90  |  Page 91  |  Page 92  |  Page 93  |  Page 94  |  Page 95  |  Page 96  |  Page 97  |  Page 98  |  Page 99  |  Page 100  |  Page 101  |  Page 102  |  Page 103  |  Page 104  |  Page 105  |  Page 106  |  Page 107  |  Page 108  |  Page 109  |  Page 110  |  Page 111  |  Page 112  |  Page 113  |  Page 114  |  Page 115  |  Page 116  |  Page 117  |  Page 118  |  Page 119  |  Page 120  |  Page 121  |  Page 122  |  Page 123  |  Page 124  |  Page 125  |  Page 126  |  Page 127  |  Page 128  |  Page 129  |  Page 130  |  Page 131  |  Page 132  |  Page 133  |  Page 134  |  Page 135  |  Page 136  |  Page 137  |  Page 138  |  Page 139  |  Page 140