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Language editing: Will Simonson (Cambridge), and Proofreading Pal Translation of abstracts to Portuguese: Ana Filipa Guerra Silva Gomes da Piedade Page desing & layout: Marit Arnold, Klaus A. Hess, Ria Henning-Lohmann Cover photographs: front: Thunderstorm approaching a village on the Angolan Central Plateau (Rasmus Revermann) back: Fire in the miombo woodlands, Zambia (David Parduhn) Cover Design: Ria Henning-Lohmann

ISSN 1613-9801

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Suggestion for citations: Volume: Revermann, R., Krewenka, K.M., Schmiedel, U., Olwoch, J.M., Helmschrot, J. & Jürgens, N. (eds.) (2018) Climate change and adaptive land management in southern Africa – assessments, changes, challenges, and solutions. Biodiversity & Ecology, 6, Klaus Hess Publishers, Göttingen & Windhoek.

Articles (example): Archer, E., Engelbrecht, F., Hänsler, A., Landman, W., Tadross, M. & Helmschrot, J. (2018) Seasonal prediction and regional climate projections for southern Africa. In: Climate change and adaptive land management in southern Africa – assessments, changes, challenges, and solutions (ed. by Revermann, R., Krewenka, K.M., Schmiedel, U., Olwoch, J.M., Helmschrot, J. & Jürgens, N.), pp. 14–21, Biodiversity & Ecology, 6, Klaus Hess Publishers, Göttingen & Windhoek.

Corrections brought to our attention will be published at the following location: http://www.biodiversity-plants.de/biodivers_ecol/biodivers_ecol .php Biodiversity & Ecology

Journal of the Division Biodiversity, Evolution and Ecology of Plants, Institute for Plant Science and Microbiology, University of Hamburg

Volume 6:

Climate change and adaptive land management in southern Africa

Assessments, changes, challenges, and solutions

Edited by

Rasmus Revermann1, Kristin M. Krewenka1, Ute Schmiedel1, Jane M. Olwoch2, Jörg Helmschrot2,3, Norbert Jürgens1

1 Institute for Plant Science and Microbiology, University of Hamburg 2 Southern African Science Service Centre for Climate Change and Adaptive Land Management 3 Department of Soil Science, Faculty of AgriSciences, Stellenbosch University

Hamburg 2018

RPlease cite the article as follows:

Jürgens, N., Strohbach, B., Lages, F., Schmiedel, U., Finckh, M., Sichone, P., Hahn, L.-M. & Zigelski, P. (2018) Biodiversity observation – an overview of the current state and first results of biodiversity monitoring studies. In: Climate change and adaptive land management in southern Africa – assessments, changes, challenges, and solutions (ed. by Revermann, R., Krewenka, K.M., Schmiedel, U., Olwoch, J.M., Helmschrot, J. & Jürgens, N.), pp. 382-396, Biodiversity & Ecology, 6, Klaus Hess Publishers, Göttingen & Windhoek. doi:10.7809/b-e.00350 Biodiversity observation – an overview of the current state and fi rst results of biodiversity monitoring studies

Norbert Jürgens1*, Ben Strohbach2, Fernanda Lages3, Ute Schmiedel1, Manfred Finckh1, Priscilla Sichone1, Lisa-Marie Hahn1 and Paulina Zigelski1 1 Institute for Plant Science and Microbiology, University of Hamburg, Ohnhorststraße 18, 22609 Hamburg, Germany 2 Faculty of Natural Resources and Spatial Sciences, Namibia University of Science and Technology, Private Bag 13388, Windhoek, Namibia 3 Instituto Superior de Ciências de Educação da Huíla, Herbário do Lubango, Rua Sarmento Rodrigues, Lubango, Angola Biodiversity * Corresponding author: [email protected]

Abstract: Th e SASSCAL region is home to a very rich biodiversity, which provides signifi cant economic and intrinsic value to human society. Th is biodiversity, however, is subject to multiple stresses emerging from human land use and climate change, which leads to biodiversity loss at substantial scale. To assess the current state and changes in biodiversity in the SASSCAL region, a standardised biodiversity observation network has been established. Th e network comprises 47 biodi- versity observatories and 10 auxiliary observatories, where biodiversity change is monitored according to a standardised approach. Th e network currently covers the countries of Angola, Namibia, Zambia, and South Africa. The newly established observatories in Angola and Zambia provided urgently needed baseline inventory data on fl ora and faunal species for the study areas. The observatories in Namibia and South Africa already extend up to 17 or even 30 years and provide important insights into the complexity of the biodiverse systems and their drivers. We provide an overview of the outcomes of the biodiversity assessment and monitoring work at the observatories. We dis- cuss the contribution of these fi ndings for the understanding of the systems and their changes over time. We also outline new approaches (e.g. experiments, monitoring of key ecological processes like the water pathways in the vegetation, as well as automatised monitoring) to be applied in the ongoing monitoring activities.

Resumo: A região do SASSCAL é o lar de uma biodiversidade muito rica, a qual fornece um valor económico e intrínseco signifi cativo à sociedade humana. No entanto, esta biodiversidade está sujeita a múltiplas pressões emergentes do uso da terra pelo Homem e das alterações climáticas, o que leva à perda da biodiversidade a uma escala substancial. Para avaliar o estado actual e as alterações da biodiversidade na região do SASSCAL, foi implementada uma rede de observação de biodiversidade padronizada. A rede é composta por 47 observatórios de biodiversidade e 10 observatórios auxiliares, onde as mudanças da biodiversidade são monitorizadas no contexto de uma abordagem padronizada. A rede cobre actualmente Angola, Namíbia, Zâmbia e África do Sul. Os observatórios recém-estabelecidos em Angola e na Zâmbia forneceram dados de referência urgentemente necessários sobre os inventários das espécies de fl ora e fauna para as áreas de estudo. Os observatórios na Namíbia e África do Sul já existem há 17 ou até mesmo 30 anos, e fornecem informações importantes sobre a complexidade dos sistemas biodiversos e os seus catalizadores. Fornecemos uma visão geral dos resultados da avaliação da biodiversidade e do trabalho de monitorização nos observatórios. Discutimos o contributo destas descobertas para a compreensão dos sistemas e suas alterações ao longo do tempo. Descre- vemos também novas abordagens (e.x.: experiências, monitorização de processos ecológicos chave, tais como percursos da água na vegetação, bem como monitorização automatizada) para serem aplicadas nas actividades de monitorização em curso.

382 C A Preface In awareness of the importance of the Unpacking monitoring: various ecosystem services which depend the fi rst step towards mon- This article deals primarily with the bio- on biodiversity, all SASSCAL countries itoring is the assessment diversity monitoring activities in the ge- are signatories to the Convention on Bio- of baseline knowledge ographical space encompassing Angola, logical Diversity (CBD). The Ministries Zambia, and Namibia. For South Africa, of Environment of these countries lead When dealing with biodiversity and its only activities in the Succulent Karoo action to protect their country’s biodi- long-term changes, it is important fi rst of Biome of Namaqualand are described; versity. There are also a large number of all to have an overview of what exists, it would be too ambitious to review the international institutions and NGOs that in what quantity and quality, and where wealth of monitoring projects and pub- contribute to the conservation and man- it occurs. Although southern Africa has lications produced by the South African agement of biodiversity in the region. been subject to early scientifi c explora- scientifi c community for the Republic as The above-mentioned economic and tions (e.g. Baum 1903; Dinter, 1927; Pole a whole. intrinsic values of biodiversity underline Evans, 1948) followed by modern check- the need to keep stock of these values lists and taxonomic studies, we are still a and to monitor changes in their quantity long way from having a holistic picture and quality. Due to their very diff erent of the region and how it has changed over Biodiversity Introduction – the many purposes and uses, diff erent approaches time. While South Africa plays a special needs and demands for are needed to monitor the state of biodi- role and has been explored relatively sys- biodiversity monitoring versity. It makes a diff erence whether a tematically (e.g. Acocks, 1988; Mucina farmer community assesses the number & Rutherford, 2006), other parts of the The SASSCAL region houses a rich bio- of valuable timber trees within their con- region are still under-researched, some of diversity and the value of biodiversity is versancy in order to defi ne the number of them very much so. acknowledged in many ways. The spe- trees that can be harvested in a sustain- Basic information on biodiversity is cies richness of charismatic mammals able land use system. It also matters that provided by simple checklists based on and birds is the foundation of a large and a country fulfi ls its reporting duties to the thorough assessments. They are essential still growing ecotourism industry. The di- Convention on Biodiversity. However, tools in biodiversity research. A check- versity of plants and insects drives many in order to carry out these diff erent ac- list provides an inventory of a particular ecosystem functions and services that tivities, whether at local or national scale, taxonomic group for a given area. Taking support a diversity of agricultural land it is required that a number of diff erent the example of plants, the fi rst checklist uses. There is also a diversity of bacte- variables need to be recorded accurately. for Angola was published only in 2008: ria, fungi, and algae that contribute to In addition to all the above-mentioned Plants of Angola – Plantas de Angola by soil fertility and nutrient cycling. A wide aspects of biodiversity and its changes, Figueiredo & Smith. For other taxonomic range of plant and animal species are used we now also have to consider the role that groups and regions, such checklists are commercially. The traditional market rapid anthropogenic climate change plays still unavailable or are currently in the products like meat and timber are further as an important driver of changes to eco- process of being compiled or amended, complemented by a growing number of system properties as well as biodiversity. for example on herpetofauna (Baptista new and specialised medicinal, cosmetic, Therefore, it is important to establish et al., 2018, this volume) and Check- artisanal, and other products. standardised methods for long-term mon- list Zambia Baltodea (Mbata, 2018, this From a species conservation perspec- itoring of biodiversity and ecosystems. volume). tive, the SASSCAL region is home to Together with existing meteorological Similarly, a full understanding of the many important and/or threatened wild- recording, this monitoring will allow for spatial extension of vegetation units also life species like African bush elephant, the impact of climate change to be as- provides a baseline assessment that can be African forest elephant, southern giraff e, sessed against other drivers, especially used later to identify spatial changes. In Masai giraff e, cheetah, wild dog, lion, those related to land use. this volume the state of the art with regard and the largest remaining population of With regard to the SASSCAL region to vegetation mapping and classifi cation black rhino and other rare species (West- and its domination by arid ecosystems, is presented for the Huíla Province, An- ern & Vigne, 1985; Emslie & Brooks, the need for long-term monitoring is of gola (Chissingui et al, 2018, this volume) 1999; Fennessy et al., 2016). Evolu- even greater importance. This is because and for south-west Botswana (Thireletso, tionary history has created plants and of the high spatio-temporal variability 2018, this volume). In Namibia, vegeta- animals with many extraordinary adapta- of arid systems, the impact of stochastic tion surveying is well advanced with over tions such as the highly succulent plants processes and rare events, as well as the 12,000 surveyed plots. Also, several re- commonly known as “living stones” or slow response of many of the organisms gional descriptions have been published Psammotermes sand termites that create and ecosystems to environmental change. in this country over the past few years, or “fairy circles”. Furthermore, “living fos- The development of monitoring methods are in the process of being published (e.g. sils” such as Welwitschia mirabilis have that are appropriate for diff erent purposes Strohbach, 2013, 2014, 2017d). Here, the survived until today. is itself a subject of research. work is advancing from making pure

B E 6 2018 383 plore the latter type of scientifi c monitor- ing with a focus on activities in this mil- lennium. We use the current approaches to Essential Biodiversity Variables (EBV, Pereira et al., 2013) and biodiversity in- dicators (Geijzendorff er et al., 2015). We follow Proença et al. (2016) by clas- sifying sources of primary observations into four types: extensive monitoring schemes, intensive ones, ecological fi eld studies, and satellite and drone remote sensing.

Extensive ground-based monitoring Biodiversity Schenck 1884 Extensive monitoring maximises input towards a clear focused goal, while lim- iting sampling eff ort on additional site parameters (see also Couvet et al., 2011, for a more detailed discussion). Such an approach is necessary when the manage- ment of farming systems or conservation areas is the immediate goal of the moni- toring activities. In these cases, focused data that describe the quantity or qual- ity of the managed subject or system are needed. Rapid interpretation of the data allows immediate responses in terms of management decisions. For example, regular game counts from the ground or the air are an important indicator of the eff ectiveness of previous manage- 2016 ment decisions. Modern apps allow the growing dimension of civil society-based monitoring. In response to the intensi- fi ed poaching for animals such as rhino, Figure 1: Repeat photography allows comparison over long periods of time. Welwitschia elephant, and pangolin, targeted moni- population near the Swakop River (1884 and 2016) (Observatory Welwitschia Vlakte (A09). toring with drones and planes has been undertaken in those regions most threat- ened by poachers. Threatened species are baseline descriptions to developing a tool of the origin of the current biodiversity. also monitored with modern tools like for land use planning (Strohbach, 2017c). A vast body of literature describes the GPS collars, camera traps for game, and presence of wildlife during pre-colonial time lapse cameras. Some examples for times. The formerly much wider ranges game count access can be found at the Diff erent approaches to of large mammals makes us aware of the following websites: http://www.land- monitoring extent to which their populations have scapesnamibia.org/sossusvlei-namib/ shrunk as a result of human appropriation game-counts; http://www.nacso.org.na/ In principle, monitoring always aims at of productive ecosystems. Taking photo- resources/game-count-data. detecting, measuring, and understanding graphs as replicates of those in historical The above activities are typically fo- change in time. Most current approaches archives allows us to look backwards in cused on: (a) threatened or iconic larger to managing biodiversity are based on in- time (Fig. 1), and understand slow chang- animals that are important for conser- terpreting temporal changes in biodiver- es driven by land use or climate change. vation and ecotourism, including long sity, although they often diff er in format However, the majority of monitoring distance migratory species; (b) the size and content. approaches do not use a retrospective and number of populations; and often Some approaches to studying temporal view but instead record biodiversity data (c) within geographically or politically changes aim at a historical understanding in the present time. In this article we ex- defi ned management units, for example

384 C A Biodiversity

Figure 2: Location of the 57 current Biodiversity Observatories.

B E 6 2018 385 Table 1: Biodiversity Observatories within the SASSCAL Observation Net. Rainfall regime: S = summer rainfall, W = winter rainfall, MAP = mean annual precipitation (mm)

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Biodiversity KƚũŝŵĂŶŐŽŵďĞ &ĂƌŵŝŶŐǁŝƚŚĐĂƚƚůĞ͕ŐĂŵĞĨŽƌ EĂŵŝďŝĂ ^Ϭϱ ϮϬϬϭ <ĂůĂŚĂƌŝdžĞƌŝĐƐĂǀĂŶŶĂ ϭϰϵϱ ^ ϯϰϲ ;ƌŝĐŚƐĨĞůĚĞͿ ŚƵŶƚŝŶŐ &ĂƌŵŝŶŐǁŝƚŚĐĂƚƚůĞ͕ŐŽĂƚƐĂŶĚ EĂŵŝďŝĂ KŬĂŵďŽƌŽ ^Ϭϲ ϮϬϬϭ <ĂůĂŚĂƌŝdžĞƌŝĐƐĂǀĂŶŶĂ ϭϰϵϬ ^ ΕϰϬϬ ƐŚĞĞƉ EĂŵŝďŝĂ EŝŬŽEŽƌƚŚ ^Ϭϴ ϮϬϬϭ EĂŵŝďŝĂŶƐĂǀĂŶŶĂǁŽŽĚůĂŶĚƐ ϭϬϳϬ &ĂƌŵŝŶŐǁŝƚŚŐŽĂƚƐ ^ ΕϮϬϬ EĂŵŝďŝĂ EŝŬŽ^ŽƵƚŚ ^Ϭϵ ϮϬϬϭ EĂŵŝďŝĂŶƐĂǀĂŶŶĂǁŽŽĚůĂŶĚƐ ϭϬϳϲ &ĂƌŵŝŶŐǁŝƚŚŐŽĂƚƐ ^ ΕϮϬϬ EĂŵŝďŝĂ 'ĞůůĂƉKƐƚ ^ϭϬ ϮϬϬϭ EĂŵŝďŝĂŶƐĂǀĂŶŶĂǁŽŽĚůĂŶĚƐ ϭϬϵϵ &ĂƌŵŝŶŐǁŝƚŚƐŚĞĞƉ͕ĐĂƚƚůĞ͕ŚŽƌƐĞƐ ^ ϭϴϯ &ĂƌŵŝŶŐǁŝƚŚƐŚĞĞƉ͕ŐŽĂƚƐ͕ EĂŵŝďŝĂ EĂďĂŽƐ ^ϭϭ ϮϬϬϭ EĂŵŝďŝĂŶƐĂǀĂŶŶĂǁŽŽĚůĂŶĚƐ ϭϬϰϱ ^ ϭϴϯ ĚŽŶŬĞLJƐ EĂŵŝďŝĂ <ĂƌŝŽƐ ^ϭϮ ϮϬϬϭ EĂŵĂ<ĂƌŽŽ ϵϬϵ ŽŶƐĞƌǀĂƚŝŽŶ ^ ϭϬϯ EĂŵŝďŝĂ tůŽƚnjŬĂƐďĂŬĞŶ ^ϭϲ ϮϬϬϭ EĂŵŝďĚĞƐĞƌƚ ϳϯ ŽŶƐĞƌǀĂƚŝŽŶĂƌĞĂ ^ ΕϭϬ EĂŵŝďŝĂ <ůĞŝŶďĞƌŐ ^ϯϰ ϮϬϬϰ EĂŵŝďĚĞƐĞƌƚ ϭϴϴ ŽŶƐĞƌǀĂƚŝŽŶĂƌĞĂ ^ ΕϭϬ EĂŵŝďŝĂ 'ŽďĂďĞď ^ϯϱ ϮϬϬϰ EĂŵŝďĚĞƐĞƌƚ ϰϭϵ ŽŶƐĞƌǀĂƚŝŽŶĂƌĞĂ ^ ΕϱϬ EĂŵŝďŝĂ 'ĂŶĂď ^ϯϲ ϮϬϬϰ EĂŵŝďŝĂŶƐĂǀĂŶŶĂǁŽŽĚůĂŶĚƐ ϵϵϱ ŽŶƐĞƌǀĂƚŝŽŶĂƌĞĂ ^ ΕϴϬ EĂŵŝďŝĂ ZŽŽŝƐĂŶĚ ^ϯϳ ϮϬϬϰ EĂŵŝďŝĂŶƐĂǀĂŶŶĂǁŽŽĚůĂŶĚƐ ϭϭϲϬ ĂƚƚůĞĨĂƌŵŝŶŐĂŶĚƚŽƵƌŝƐŵ ^ ΕϮϬϬ EĂŵŝďŝĂ ůĂƌĂƚĂů ^ϯϴ ϮϬϬϰ <ĂůĂŚĂƌŝdžĞƌŝĐƐĂǀĂŶŶĂ ϭϴϲϱ &ĂƌŵŝŶŐǁŝƚŚĐĂƚƚůĞĂŶĚŐĂŵĞ ^ ΕϯϬϬ EĂŵŝďŝĂ EĂƌĂŝƐ ^ϯϵ ϮϬϬϰ <ĂůĂŚĂƌŝdžĞƌŝĐƐĂǀĂŶŶĂ ϭϲϮϰ &ĂƌŵŝŶŐǁŝƚŚĐĂƚƚůĞ ^ Ϯϴϵ EĂŵŝďŝĂ ƵƌƵĐŚĂƵƐ ^ϰϬ ϮϬϬϰ <ĂůĂŚĂƌŝdžĞƌŝĐƐĂǀĂŶŶĂ ϭϲϭϰ &ĂƌŵŝŶŐǁŝƚŚĐĂƚƚůĞĂŶĚŐŽĂƚƐ ^ Ϯϴϵ EĂŵŝďŝĂ KŐŽŶŐŽ ^ϰϮ ϮϬϬϳ ŶŐŽůĂŶDŽƉĂŶĞǁŽŽĚůĂŶĚƐ ϭϭϬϯ ĞŵŽŶƐƚƌĂƚŝŽŶĨĂƌŵŝŶŐǁŝƚŚĐĂƚƚůĞ ^ ΕϱϬϬ ƌŽƉƉŝŶŐĂŶĚĐĂƚƚůĞĂŶĚƐŵĂůů EĂŵŝďŝĂ KŵĂŶŽŐŽEĚũĂŵďĂ ^ϰϯ ϮϬϬϳ ŶŐŽůĂŶDŽƉĂŶĞǁŽŽĚůĂŶĚƐ ϭϭϬϬ ΕϱϬϬ ůŝǀĞƐƚŽĐŬ ^ EĂŵŝďŝĂ ^ĂŶĚǀĞůĚ ^ϰϭ ϮϬϬϰ <ĂůĂŚĂƌŝdžĞƌŝĐƐĂǀĂŶŶĂ ϭϱϮϯ džƉĞƌŝŵĞŶƚĂůĨĂƌŵŝŶŐǁŝƚŚĐĂƚƚůĞ ^ ϰϬϰ EĂŵŝďŝĂ ŝĞƉƌŝǀŝĞƌ Ϭϭ ϮϬϬϲ EĂŵŝďĞƐĞƌƚ ϭϬϰϵ dŽƵƌŝƐŵ ^ ϭϬϬ EĂŵŝďŝĂ 'ŝƌŝďĞƐsůĂŬƚĞ ϬϮ ϮϬϬϲ EĂŵŝďĞƐĞƌƚ ϲϮϭ ^ĞŵŝͲŶŽŵĂĚŝĐĨĂƌŵŝŶŐ ^ ϭϬϬ EĂŵŝďŝĂ 'ŝƌŝďĞƐ>ĞŽƉĂƌĚZŽĐŬ Ϭϯ ϮϬϬϲ EĂŵŝďĞƐĞƌƚ ϲϯϯ ^ĞŵŝͲŶŽŵĂĚŝĐĨĂƌŵŝŶŐ ^ ϭϬϬ EĂŵŝďŝĂ &ĞĂƚŚĞƌůŝŽŶ Ϭϰ ϮϬϬϲ EĂŵŝďĞƐĞƌƚ ϱϴϯ ^ĞŵŝͲŶŽŵĂĚŝĐĨĂƌŵŝŶŐ ^ ϮϬϬ EĂŵŝďŝĂ DĂƌŝĞŶĨůƵƐƐsĂůůĞLJ Ϭϱ ϮϬϬϲ EĂŵŝďĞƐĞƌƚ ϱϲϲ ^ĞŵŝͲŶŽŵĂĚŝĐĨĂƌŵŝŶŐ ^ ϮϬϬ EĂŵŝďŝĂ ,ĂƌƚŵĂŶŶWůĂŝŶƐ Ϭϲ ϮϬϬϲ EĂŵŝďĞƐĞƌƚ ϱϱϰ ^ĞŵŝͲŶŽŵĂĚŝĐĨĂƌŵŝŶŐ ^ ϭϬϬ EĂŵŝďŝĂ ,ĂƌŝďĞƐ Ϭϳ ϮϬϭϬ EĂŵĂ<ĂƌŽŽ ϭϭϵϰ ŽŵŵĞƌĐŝĂůĨĂƌŵ ^ ϮϬϬ ϮϬϬϵ EĂŵŝďŝĂ tĞůǁŝƚƐĐŚŝĂWůĂŝŶ Ϭϵ EĂŵŝďĞƐĞƌƚ ϰϯϳ EĂƚŝŽŶĂůWĂƌŬ ^ ϮϬ ;ϭϴϴϰͿ ϮϬϬϵ EĂŵŝďŝĂ ZŽĞƐƐŝŶŐDŽƵŶƚĂŝŶ ϭϬ EĂŵŝďĞƐĞƌƚ ϰϲϳ EĂƚŝŽŶĂůWĂƌŬ ^ ϮϬ ;ϭϵϭϳͿ ^ŽƵƚŚĨƌŝĐĂ ůƉŚĂ ^ϭϳ ϮϬϬϭ <ĂůĂŚĂƌŝdžĞƌŝĐƐĂǀĂŶŶĂ ϴϵϲ 'ĂŵĞĨĂƌŵŝŶŐ͕ĐŽŶƐĞƌǀĂƚŝŽŶ ^ ϭϵϮ ^ŽƵƚŚĨƌŝĐĂ <ŽĞƌŽĞŐĂďsůĂŬƚĞ ^ϭϴ ϮϬϬϭ ^ƵĐĐƵůĞŶƚ<ĂƌŽŽ͕ZŝĐŚƚĞƌƐǀĞůĚ ϲϯϱ ^ĞŵŝͲŶŽŵĂĚŝĐĨĂƌŵŝŶŐ t ϭϯϴ ^ĞŵŝͲŶŽŵĂĚŝĐĨĂƌŵŝŶŐǁŝƚŚŐŽĂƚƐ͕ ^ŽƵƚŚĨƌŝĐĂ EƵŵĞĞƐ ^ϮϬ ϮϬϬϭ ^ƵĐĐƵůĞŶƚ<ĂƌŽŽ͕ZŝĐŚƚĞƌƐǀĞůĚ ϯϲϮ t ϭϭϰ ƐŚĞĞƉ͕ĐĂƚƚůĞ ^ŽƵƚŚĨƌŝĐĂ 'ƌŽŽƚĞƌŵ ^Ϯϭ ϮϬϬϭ ^ƵĐĐƵůĞŶƚ<ĂƌŽŽ͕^ĂŶĚǀĞůĚ ϭϵϯ ŽŵŵƵŶĂůƐŵĂůůͲůŝǀĞƐƚŽĐŬĨĂƌŵŝŶŐ t ϴϰ ^ŽƵƚŚĨƌŝĐĂ ^ŽĞďĂƚƐĨŽŶƚĞŝŶ ^ϮϮ ϮϬϬϭ ^ƵĐĐƵůĞŶƚ<ĂƌŽŽ͕,ĂƌĚĞǀĞůĚ ϯϵϮ ŽŵŵƵŶĂůƐŵĂůůͲůŝǀĞƐƚŽĐŬĨĂƌŵŝŶŐ t ϭϯϭ ^ŽƵƚŚĨƌŝĐĂ ^ŽĞďĂƚƐĨŽŶƚĞŝŶ ^Ϯϯ ϮϬϬϰ ^ƵĐĐƵůĞŶƚ<ĂƌŽŽ͕,ĂƌĚĞǀĞůĚ ϯϵϮ džĐůŽƐƵƌĞ t ϭϯϭ ^ŽƵƚŚĨƌŝĐĂ WĂƵůƐŚŽĞŬ ^Ϯϰ ϮϬϬϭ ^ƵĐĐƵůĞŶƚ<ĂƌŽŽ͕<ĂŵŝĞƐďĞƌŐ ϭϬϰϴ ŽŵŵƵŶĂůƐŵĂůůͲůŝǀĞƐƚŽĐŬĨĂƌŵŝŶŐ t ϭϲϴ ŽŵŵĞƌĐŝĂůƐŵĂůůͲůŝǀĞƐƚŽĐŬ ^ŽƵƚŚĨƌŝĐĂ ZĞŵŚŽŽŐƚĞ ^Ϯϱ ϮϬϬϭ ^ƵĐĐƵůĞŶƚ<ĂƌŽŽ͕<ĂŵŝĞƐďĞƌŐ ϭϬϮϳ t ϭϲϴ ĨĂƌŵŝŶŐ ^ŽƵƚŚĨƌŝĐĂ 'ŽĞĚĞŚŽŽƉ ^Ϯϲ ϮϬϬϭ ^ƵĐĐƵůĞŶƚ<ĂƌŽŽ͕<ŶĞƌƐǀůĂŬƚĞ Ϯϰϱ ŽŶƐĞƌǀĂƚŝŽŶ t ϭϮϰ ^ŽƵƚŚĨƌŝĐĂ ZĂƚĞůŐĂƚ ^Ϯϳ ϮϬϬϭ ^ƵĐĐƵůĞŶƚ<ĂƌŽŽ͕<ŶĞƌƐǀůĂŬƚĞ Ϯϯϵ ŽŶƐĞƌǀĂƚŝŽŶ t ϭϮϰ ^ŽƵƚŚĨƌŝĐĂ DŽĞĚǀĞƌůŽƌĞŶ ^Ϯϴ ϮϬϬϭ ^ƵĐĐƵůĞŶƚ<ĂƌŽŽ͕<ŶĞƌƐǀůĂŬƚĞ ϭϰϬ ŽŶƐĞƌǀĂƚŝŽŶ t ϭϯϭ ^ŽƵƚŚĨƌŝĐĂ ZŽĐŚĞƌƉĂŶ ^Ϯϵ ϮϬϬϭ >ŽǁůĂŶĚĨLJŶďŽƐĂŶĚƌĞŶŽƐƚĞƌǀĞůĚ ϯϱ ŽŶƐĞƌǀĂƚŝŽŶĂƌĞĂ t Ϯϱϭ ^ŽƵƚŚĨƌŝĐĂ ZŝǀĞƌůĂŶĚƐ ^ϯϭ ϮϬϬϭ >ŽǁůĂŶĚĨLJŶďŽƐĂŶĚƌĞŶŽƐƚĞƌǀĞůĚ ϭϰϬ ŽŶƐĞƌǀĂƚŝŽŶĂƌĞĂ t ϰϱϯ ^ŽƵƚŚĨƌŝĐĂ ůĂŶĚƐďĞƌŐ ^ϯϮ ϮϬϬϭ >ŽǁůĂŶĚĨLJŶďŽƐĂŶĚƌĞŶŽƐƚĞƌǀĞůĚ ϵϱ ŽŶƐĞƌǀĂƚŝŽŶĂƌĞĂ t ϱϲϬ ^ŽƵƚŚĨƌŝĐĂ ĂƉĞŽĨ'ŽŽĚ,ŽƉĞ ^ϯϯ ϮϬϬϭ DŽŶƚĂŶĞĨLJŶďŽƐĂŶĚƌĞŶŽƐƚĞƌǀĞůĚ ϴϯ ŽŶƐĞƌǀĂƚŝŽŶĂƌĞĂ t ϲϴϵ ^ŽƵƚŚĨƌŝĐĂ EŝĞƵǁŽƵĚƚǀŝůůĞ ^ϰϱ ϮϬϬϳ ŽŶƐĞƌǀĂƚŝŽŶĂƌĞĂ ϳϮϮ ŽŶƐĞƌǀĂƚŝŽŶĂƌĞĂ t ϯϬϭ ^ŽƵƚŚĨƌŝĐĂ ŬƐƚĞĞŶĨŽŶƚĞŝŶ Ϭϴ ϮϬϬϭ ^ƵĐĐƵůĞŶƚ<ĂƌŽŽ͕ZŝĐŚƚĞƌƐǀĞůĚ ϲϮϮ ŽŵŵƵŶĂůƐŵĂůůͲůŝǀĞƐƚŽĐŬĨĂƌŵŝŶŐ t ΕϮϬϬ ĂŵďŝĂ >ƵĂŵƉĂ ^ϱϭ ϮϬϭϰ ĞŶƚƌĂůĂŵďĞnjŝĂŶDŝŽŵďŽtŽŽĚůĂŶĚƐ ϭϭϰϴ &ŽƌĞƐƚƌĞƐĞƌǀĞĂŶĚĐƌŽƉĨĂƌŵŝŶŐ ^ ΕϭϭϱϬ ĂŵďŝĂ ŽŶŐǁĞ ^ϱϮ ϮϬϭϰ ĞŶƚƌĂůĂŵďĞnjŝĂŶDŝŽŵďŽtŽŽĚůĂŶĚƐ ϭϬϲϲ &ŽƌĞƐƚƌĞƐĞƌǀĞĂŶĚĨŽƌĞƐƚƌLJ ^ ΕϭϭϬϬ ĂŵďŝĂ <ĂĨƵĞEĂƚŝŽŶĂůWĂƌŬ ^ϱϯ ϮϬϭϰ ĞŶƚƌĂůĂŵďĞnjŝĂŶDŝŽŵďŽtŽŽĚůĂŶĚƐ ϭϮϭϬ EĂƚŝŽŶĂůWĂƌŬ ^ ΕϭϭϱϬ 



386 C A conservancies. In summary, these moni- toring schemes could be called ‘applied a monitoring’ because data are generated for a concrete and direct management goal within a short timeframe.

Intensive ground-based monitoring Less common than extensive monitor- ing schemes are monitoring schemes that observe changes in: (a) less visible ani- mals such as insects; (b) higher plants; (c) mosses, lichens, fungi, algae or bacteria; (d) communities of particular taxonomic groups (or of all organisms); and (e) eco- system functions and services. In many Biodiversity of the above cases, changes within popu- lations and communities are interpreted as a response to environmental change. These approaches meet the defi nition of intensive monitoring schemes. Again, b following Proença et al. (2016), the goal of these approaches is “to capture ecolog- ical responses to environmental change, by monitoring ecosystem functioning and species interactions”. The outcomes of these approaches will ultimately also allow application and utilisation for management, although in an indirect and more complex way. To some extent, they can also be regarded as pure research be- cause they are driven by a curiosity in the fundamental rules and processes of living ecosystems. One of the largest intensive monitoring schemes, and the only one that is region- ally integrated, is the SASSCAL Obser- vation Net. This presently comprises 47 Figure 3: (a) Species richness at the newly established observatories in Angola and Zambia in the 100 m2 plots and the 1000 m2 plots. Note that the data were collected in diff erent biodiversity observatories and 10 auxil- years. n = 20 plots per observatory, except for the 1000 m2 plots at observatory S74 where iary observatories ranging from central only 6 plots were included. For location and detailed information on the observatories see Angola and western Zambia to the north- Table 1 and Figure 2; (b) mean annual precipitation at the observatories. ern and western Cape of South Africa (see Fig. 2). Here, standardised fi xed-site Ground-based monitoring in Baken) are of particular interest due to the observations are made within real land- Namibia dynamics of the lichen fi elds associated scapes at a size of one square kilometre, In Namibia, a total of 22 biodiversity ob- with the fogs created by the cold Ben- subdivided and permanently marked with servatories and 9 auxiliary observatories guela current around the western coast of metal poles and metal numbers into 100 were established during the BIOTA pro- southern Africa. The remaining 20 biodi- hectare cells. For more detail on the lay- ject (2001–2010) (Jürgens et al., 2010). versity and auxiliary observatories are ar- out of the observatories and sampling de- Of these, eleven are in the extremely arid ranged along a north–south transect, and sign, see Jürgens et al. (2012). In a num- Central Namib and show continuity over two shorter east–west ones, following the ber of landscapes, two of these square the decades due to the rarity of rainfall in predominant rainfall gradients. kilometre observatories are placed next combination with the longevity of species Eleven of the 22 biodiversity observa- to each other but are subject to diff erent like Welwitschia mirabilis (see, for exam- tories in Namibia have been ear-marked land-use practices or intensities, in order ple, Jürgens, 2006; Jürgens et al., 2013) as high-priority observatories, with their to compare their impact on biodiversity (Fig. 1). The two closest observatories to vegetation having been re-surveyed every (Hanke et al., 2014). the west coast (Kleinberg and Wlotskas year since 2001. These are, from north to

B E 6 2018 387 south, the observatory pair Mile 46 (S01) for the Aussaninas, Vogelfederberg, and vatory, at least 12 of which are endemic and Mutompo (S02), Sonop (S03), the Garnet Koppie observatories. to Angola. Figure 3 shows the species pair Toggekry (Omatako Ranch – S04) At the Karios observatory, in addition richness of vascular plants of the newly- and Otjimangombe (Erichsfelde – S05), to the standard protocol, a more detailed, established observatories in Angola and Sandveld (S41), the pair Narais (S39) individual-based monitoring was carried Zambia (for a comparable fi gure for the and Duruchaus (S40), the pair Gellap out at the scales of 1000 m², 100 m², 10 other observatories, see Schmiedel et al., Ost (S10) and Nabaos (S11), and fi nally m², and 1 m². At the auxiliary observato- 2010). The highest number of species Karios (S12) (Tab. 1). The dynamics of ries of Dieprivier, Giribesvlakte, Leopard was recorded in the more mesic miombo the four observatories within the Kalahari Rock, Hartmann Dunes, and Featherlion woodlands (S51–53, S74). basin (Mile 46, Mutompo, Sonop, and Hill/ Marienfl uss Valley, annual vegeta- Sandveld) were compared making use of tion records and automatic soil humidity Animal monitoring the full time series (Shidolo, 2017). The measurement were recorded in combina- In July 2017, a monitoring system for ter- phanerophytic (i.e. woody) vegetation tion with faunal records. In addition to the restrial mammals using photo-trapping proved to be stable overall, but we were annual vegetation monitoring, on the Ka- was implemented in a central part of the able to show considerable shifts in the rios (S12) observatory we annually moni- Bicuar National Park and in the neigh- Biodiversity composition of especially the grass layer, tored the arrival, growth, and death of all bouring observatory (S75). The aim of which appears closely related to annual individuals of perennial plant species. this approach is to evaluate the patterns rainfall fl uctuations and fi re events. Sur- and processes determining the structure prisingly, the more arid Sandveld proved Ground-based monitoring in and functioning of mammalian com- to be far more stable than the moister Angola munities, and the relative importance northern observatories of Sonop, Mile 46, The fi rst biodiversity observatories in of resource availability and predation and Mutompo. Processing of the available Angola, Candelela (S73) and Cusseque on herbivore behaviour and habitat use. long-term data, collected by fi ve diff erent (S74), were installed in 2013. Thereaf- This monitoring system also investigates observers over the past 17 years, showed ter, four others were added following whether seasonal variation in resource a high degree of observer bias. The ob- the BIOTA south–north mega-transect availability regulates herbivore popula- server bias is evident especially in the and integrated with the regional net- tion parameters (CIBIO-UP partnership). identifi cation of minor species, but also work of biodiversity observatories (see In the central area of the park, 49 cameras in the abundance ratings of the dominant Tab. 1). All are located in the southern were arranged in a regular grid of 7 by species. Thus, the thorough documenta- part of the country (between -11.5° S 7 cameras with a distance between cam- tion of all observed taxa underpinned and -16.8° S latitude and 20.9° E and era locations of ca. 2 km. This allows for by herbarium specimen is a necessary 12.4° E longitude), and represent four a wide spatial coverage in the diff erent requirement for meaningful long term diff erent ecological regions (Burgess types of habitats and ensures the spatial monitoring. The abundance rating of the et al., 2014). The altitude varies from independence of sampling points. This dominant species is another parameter about 400 m to more than 2200 m above regular design is directly adjacent to an which seems prone to observer bias. sea level, and mean annual rainfall is in opportunistic sampling scheme of 7 cam- On the main observatories, we also the range 60–100 mm (S71) to 1250– era sites for the 1 km² observatory. Dur- managed to undertake a survey of tortois- 1500 mm (S72). ing the dry season in 2017, 33 mammal es as part of the ongoing eff ort to collect Annual visits to the observatories have species were identifi ed with this com- baseline data on additional taxonomic been made in the dry and rainy seasons to bined approach. This monitoring scheme groups (Amutenya, 2016). In addition record the vascular plant species occur- continued during the rainy season of to these regular surveys, we resurveyed ring in the selected plots including their 2017/2018. the Gobabeb observatory in 2017. This estimated cover, following the BIOTA The Tundavala observatory (S72) is was done in collaboration with Gobabeb protocols. Vegetation surveys were car- located in a key region of the Angolan Research and Training Centre, in sup- ried out, with all vascular plants being escarpment where high animal and plant port of their FogNet initiative. As part recorded, respective checklists prepared, endemism is recognised (Hall, 1960; of the drone surveying (see below), we and data stored in BIOTAbase. Speci- Huntley & Matos, 1994). The herpeto- identifi ed at each FogNet weather station mens are deposited in the herbaria of fauna has been monitored since April a square kilometre that can be used as a Lubango (LUB) and Hamburg (HBG), in 2016 using traplines with pitfalls and biodiversity observatory. Using drone some cases still awaiting identifi cation. funneltraps, as well as visual encounter imagery, we were able to demarcate We are currently building a photographic surveys. Several scientifi cally interesting habitats, subdivide the square kilometre database of all vascular plants occurring species have been registered, some be- into 100 one hectare plots, and rank these at Tundavala Biodiversity Observatory ing new records for Angola and species according to the regular ranking scheme. (S72), with the aim of producing a guide not sighted for decades. The specimens No physical on-the-ground demarcation to the plants from the Huíla escarpment are being deposited in ISCED’s new her- has yet been undertaken, but we also col- area. To date, more than 300 diff erent petological collection. In Bicuar (S75) lected aerial imagery for baseline data species have been recorded in this obser- and Cusseque (S74), the survey so far

388 C A comprises a number of non-standardised falls during the cool winter season be- pressure at the beginning of the monitor- sampling seasons and opportunistic re- tween May and August. The mean an- ing activity varied with habitat type, the cords. In the Cameia (S76) and Cande- nual rainfall along the transect ranges particular environmental conditions of lela (S73) observatories, the records of from 700 mm at the Cape Peninsula to the plot, and the species that dominated herpetofauna are based on opportunistic <100 mm in the Richtersveld (Jürgens et the vegetation (Schmiedel & Oldeland, sampling. Information on the herpeto- al., 2010). Only one of the South African 2018). Further investigations into the fauna of the Angolan biodiversity obser- observatories is located in the summer species-specifi c response to the inter- vatories is accessible vía the website of rainfall region of South Africa, namely at annual variation in seasonal and total an- the SASSCAL Observation Net (www. the southern fringe of the Kalahari. For nual rainfall revealed that the total annual sasscalobservationnet.org; see infobox the SASSCAL research activities, special rainfall did not aff ect the abundance of by Hillmann et al., 2018). attention has been paid to the ten obser- individuals per species for a given year. vatories in the semi-arid and arid part of Instead, the abundance of individuals per Ground-based monitoring in the winter rainfall gradient of the country, species depended on the rainfall amount Zambia and on the observatory in the southern received during certain seasons. Rainfall To extend the existing network of stand- Kalahari. The winter rainfall observato- during the late summer (between January ardised biodiversity observatories in ries represent fi ve bioregions (Tab. 1). and March) turned out to be critical in de- Biodiversity southern Africa, three biodiversity ob- The observatories in the semi-arid to termining the abundance of many of the servatories were established in western arid winter rainfall region of South Africa perennial species. It is assumed that the Zambia in 2014, following the spatial de- fall within the Succulent Karoo biome, amount of rainfall received towards the sign and methodology of the BIOTA pro- which is a renowned biodiversity hotspot end of the dry period in the winter-rain- tocol (Jürgens et al., 2010). All the sites (Mucina et al., 2006). It is therefore not fall region is critical for the survival, in fall within the Miombo Woodland sensu surprising that the number of species per particular, of the newly established indi- White (1983) and extend over latitudes 100 m² plot of our Succulent Karoo ob- viduals of many of the species (Schmie- S 14°–16° and longitudes E 24°–26° at servatories can reach 50 to 60, and that del, unpublished data). The analysis of an elevation ranging from 1068 to 1210 the cumulative species number per ob- the vegetation monitoring data of the metres above sea level (Tab. 1; Fig. 2). servatory over a period of 17 years lies South African Kalahari observatory at The three observatories diff er in their well above 350 species for most of the the game farm Alpha (S17) showed the land-use type and intensity. observatories (e.g. 398 spp. for obser- joint eff ect of annual rainfall and game These observatories were installed vatory Remhoogte (S25)). Many of the density on total vegetation cover, grass and assessed during the growing season species are cryptic in nature, being tiny, and shrub/ tree cover, and species rich- of 2014 with the intention of providing well-camoufl aged (like the popular “liv- ness (Jacke, 2016). benchmark data on vascular plant diver- ing stones”), found growing inside other Complete vegetation surveys were also sity from each site. For each of the plots, plants, and/or strongly resembling each carried for the northern-most observato- the presence of vascular plant species, other morphologically. The monitoring ries within the Succulent Karoo biome their cover, and their abundances were of the observatories was hence done on in South Africa, Numees (S20) and Ko- recorded. Additionally, of tree height and the ground and involved annual visits to eroegab Vlakte (S18) and Groot Derm diameter at breast height (DBH) biomet- each plot to record the cover and (for the (S21). However, in this region the annual ric data were collected for all tree species 100 m² plots) abundance of individuals monitoring scheme deviates from the with DBH >5 cm, with the aim of esti- of all vascular plant species present in the standardised design and focuses on 45 mating the above-ground tree biomass. plot. Two local citizens, who have been permanent plots of 10 m x 10 m (100 m²) When the species identifi cation is com- trained over several years as para-ecolo- as well as experimental exclosures (pro- pleted, voucher specimens will be lodged gists (Schmiedel et al., 2016), supported tected from grazing) that have been es- at the Herbarium Hamburgense (HBG) the time-consuming annual fi eld work by tablished here and have been monitored and at the Herbarium of the University of counting and recording the abundance of intermittently since 1980. These are re- Zambia (UZL). individuals per species. garded as being of high value because We analysed the monitoring data of the of their age, warranting the diff erent de- Ground-based vegetation moni- observatories for patterns of vegetation sign. These plots showed recovery after a toring in South Africa dynamics in response to inter-annual var- drought in 1979/1980 and high continui- The 16 biodiversity observatories and iation in weather conditions and land use. ty during the subsequent 30+ years. Since one auxiliary observatory in South Af- The current state of the analysis already 2016, however, there has been a drastic rica are located along a north–south tran- highlights the complexity of the veg- decline in the composition and cover of sect from the Cape of Good Hope to the etation dynamics and its drivers in these vegetation in the plots due to a major Richtersveld in the north-west of South diverse systems. At the Soebatsfontein drought. In 2017, the winter rainfall was Africa. The transect describes a gradient observatory (S22) in the Namaqualand completely absent from the Richtersveld of decreasing annual rainfall, which in Hardeveld bioregion, the vegetation re- and many of the permanent observation this western part of South Africa mainly sponse to the release from high land-use plots lost all their vegetation. This is the

B E 6 2018 389 harshest drought of the last half century and it is scientifi cally very interesting to record the longest surviving plant species and the response of the animals and the stock farmers. In addition to the annual vegetation monitoring, on four observatories in Namaqualand we selected fi ve 100 m² plots where we annually monitored the ar- rival, growth, and death of all individuals of perennial plant species. This was also performed at all of the 100 m² sites in the Richtersveld. For this purpose, each indi- vidual has an identifi cation number and its coordinates locate the plant on the plot Biodiversity map. The individual-based monitoring provides critical information on the year Figure 4: An erosion feature on the Farm Krumhuk outside Windhoek, with a brush fi lter of arrival of the newly-established indi- as counter measure along its head (April 2016). With the calculated DSM we are able to viduals, their growth rates, year of death, illustrate sub-metre height diff erences. and thus life span. In this way, we get a better understanding of the population dy- namics, and can deduce which climatic or other events facilitate the establishment and cause the die-back of individuals of diff erent species. Such detailed data on population dynamics are extremely scarce even though they are also extremely valu- able for the interpretation of species turn- over and vegetation change under climate change conditions. Previous analyses of long-term individual-based monitoring        !   

Figure 5: Turnover of mounds of Macrotermes michaelsii on the Farm Erichsfelde north of Oka- handja in Namibia between 2007 and 2017 (Lisa- Marie Hahn, unpublished). What does it mean that during this decade new termitaria (green tri- angles) only formed on the non-calcareous soil in the north-east but not on the calcrete in the south centre nor along the river bed in the west? Do the termites respond to bush encroachment? What will the consequence be for future fi re dynamics in the area with fewer termite mounds?

  
       
       
      

        
      
           
       
         

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Figure 6: One of several hundred time series that show the impact of the present extreme drought in the northern and western Cape on vegetation. The green line shows the measured cover of vegetation, while the columns represent the annual rainfall. The variability observed in both rainfall and vegetation cover during the last three decades has recently been replaced by a strong decline in both, and agriculture utilisation has come to an end. (Example from the valley of Numees, Richtersveld National Park). from the Succulent Karoo (Jürgens et al., stations with the exception of Okam- compatibility of current high-resolution 1999; Schmiedel et al., 2012), have al- boro (S06). A basic data processing colour images with old low-resolution, ready provided valuable insight into the routine has been worked out as follows. panchromatic aerial photographs, to drivers of the population dynamics of the From the RGB images, a digital surface monitor bush encroachment trends since endemic fl ora in the Succulent Karoo. model (DSM) is calculated (i.e. provid- the 1950s (Walters, 2016). ing heights of individual features such Monitoring with drone-based aerial Drone-based remote sensing as trees and termite mounds), as well as imagery is not limited to tree and shrub observation regular orthophotos (rectifi ed aerial pho- species. We are able to monitor the den- Because of the obvious diffi culties in re- tographs), in GeoTiff and even Google sity and vigour of the grass sward, an im- surveying all observatories, we decided Earth tiles. From both the RGB and the portant requirement for grazing monitor- to at least obtain a regular (annual) pho- NIR images, a variety of indices can be ing, using remote sensing data. This, in tographic record of the observatories. For calculated, which in turn can be used to turn, feeds into the ongoing programme to this reason, a pair of eBee drones (Sense- identify specifi c features on the ground restore Namibian Rangelands (see http:// Fly) were purchased, equipped with Can- (see, for example, Oldeland et al., 2017; www.nrmps.org, http://www.agra.com. on G9X colour cameras (taking photos Strohbach, 2018). The vegetation indi- na/news/rangeland-monitoring-project. which can be separated into the three ba- ces being calculated as standard are the php and http://www.namibiarangelands. sic bands of red, green, and blue – RGB). excessive green, normalised excessive com/). Furthermore, erosion features Near-infrared (NIR) capability was origi- green, and excessive red indices derived are both clearly visible and measurable nally provided by a Canon S110 camera from RGB images (Meyer & Neto, 2008; in drone imagery (Fig. 4). Even the re- modifi ed with a NIR fi lter, but we found Rasmussen et al., 2016), whilst a NDVI sponse of vegetation and soils to resto- that these cameras are highly dust sensi- and Modifi ed SAVI are also calculated ration measures can be made visible on tive and were destroyed by regular land- (Huete, 1988; Huete et al., 1992) from NIR imagery. ings in the Namib and the Kalahari. The the NIR images if available. We are also measuring the success of NIR capability is planned to be replaced First attempts to map tree species to rehabilitation measures at the B2Gold with more robust Sequoia cameras. A species level are promising (Oldeland et Oshikoto mine (Strohbach & Haupt- large amount of practical experience has al., 2017), but require more ground-truth fl eisch, in prep.), mapping the endemic been compiled in a short practical guide data. The aerial images were also success- Neoluederitzia sericeocarpa popula- on the use of such drones for biodiversity fully used to determine the degree of for- tions in the lower Fish River (Hakalume, surveying (Strohbach, 2017 a,b). est degradation and deforestation in the 2018), determining location, height and Aerial survey data are available for Mopane savanna in Namibia (Strohbach, health of termite mounds in savanna eco- 2016 for 17 observatories as well as the 2018), as well as the woodland structure systems (Fig. 5), as well as determining seven additional FogNet stations, and for of the Kavango woodlands (Knox et al. regrowth of alien invasive Prosopis spe- 2017 for all observatories and FogNet 2018). We are also busy determining the cies at Gibeon. Trials are also undertaken

B E 6 2018 391 Biodiversity

Figure 7: Experimental fi re plot (“Purgatory”) at observatory S75 Bicuar National Park on the 12 September 2017. The experimental design comprises thirty-six 15 m x 15 m plots and a 5 m fi rebreak around the outer border of the experimental site. Early and late fi re treatments are recognisable by green vs. dark brown patches. Controls (fi re exclosure) are perfectly visible due to the bright orange colour of the mature grass sward.

to determine the number and density low, some key messages are briefl y out- transitions between savanna and forest of burrows of ground-dwelling mam- lined, without pre-empting careful data states, to support conservation plan- mals, and their eff ects on grass dynamics analyses in more extensive publications: ning eff orts, and to optimise agricul- (Hauptfl eisch et al., 2017; Rodgers et al., • In none of the observatories has a dras- tural land-use decisions. 2017), as well as using the drone-based tic invasion of exotic organisms been • As well as the dominant control by cli- aerial imagery to undertake less-intru- observed to date. matic oscillations and land use, biotic sive, automated game counts. • In the observatories located in Kala- interactions also play a major role and hari sands, there is a continuous gradi- may cause cascading eff ects over many ent from rich woodland to much less years. Current key messages productive sparse arid vegetation types • Termites, and especially the genus from the observatory with fewer perennial grasses, and this Macrotermes, are very important eco- network may refl ect a slow degradation process system engineers in savanna ecosys- in time. tems. The role of their foraging of dead Over the past several years, a substantial ef- • During the observation period the ma- wood should be studied with regard fort has been invested in the establishment jority of observatories have showed to the management of bush encroach- of the observation network. So far, some only minor changes. However, the ment/clearing and fi re. of the older time series already cover two droughts in parts of Namibia in 2015 • Fire plays an important role for the or even three decades (e.g. from some ob- and 2016 and in the Richtersveld and vegetation dynamics of the observa- servatories in the arid ecosystems of South Namaqualand in 2017 and 2018 have tories in the Miombo belt. So far, at Africa), which is suffi cient for meaningful caused a most dramatic – in many plac- least in the Angolan observatories, all analyses (see references mentioned above es complete – die-back of the vegeta- observed fi res have been of human ori- and contributions in this book). Continu- tion, which has turned previously veg- gin and for land management purposes. ous monitoring of the newer observatories etated landscapes into desert (Fig. 6). Grassland management for hunting or in Angola and Zambia will produce simi- • In addition to a general increase or de- grazing, and slash-and-burn of wood- larly valuable data in the future. crease of rainfall, seasonal changes in land and forest ecosystems, are among With the funding provided through the rainfall amounts have a major impact the most frequent causes of fi res. Thus, BIOTA, TFO, and SASSCAL initiatives, on species composition, especially in the seasonality and intensity of fi res in it was possible to establish and maintain Namaqualand. the observatories are controlled by hu- the Observation Network as an impor- • Frost seems to be a neglected but rel- man land use and not by natural causes. tant science infrastructure. Meanwhile, evant factor controlling the spatial ar- • The newly developed remote sensing numerous important results have been ray of the forest and grassland mosaic tools to detect ignition points and map achieved and presented at international on the Central Angolan Plateau. Topo- spatio-temporal footprints of individu- conferences like the GEOSS GEO BON climatic eff ects need much stronger al fi res (see Röder et al, 2018) should be Open Science Conference in 2016. Be- attention in order to understand past coupled to the SASSCAL Observation

392 C A Biodiversity

Figure 8: Smart monitoring devices and new experimental approaches for intensive and automatic biodiversity monitoring already in use or planned for SASSCAL Biodiversity Observatories. 1: Imagery/data transfer via satellite; 2: Arial imagery via drones; 3: Climate station; 4: GPS collars; 5: Phenocam; 6: “Purgatory”; 7: Insect trap nests; 8: Tree tagging/permanent marking; 9: Sound recording/bird calls; 10: Camera traps; 11: Photo sensor insect counter; 12: Herpetofauna trapping; 13: Soil water measurements; 14: Temperature loggers; 15: Binoculars/observations; 16: Tree height measurements; 17: Vegetation surveys; 18: Decay monitoring/litter bags; 19: Small mammal monitoring.

Net. They off er new potential for near sary to integrate more monitoring of (a) (b) Organismic interactions real-time analyses of fi re dynamics and key ecological processes and (b) organ- The decline of insects in Europe has re- fi re impacts on forest and savanna eco- ismic interactions, and to (c) integrate a cently increased awareness of how impor- systems. stronger experimental component. To do tant insects and birds are for ecosystem • Several of the newly established An- the monitoring work more effi ciently, we functions and services. The key services golan observatories have lost most also aim for (d) a stronger use of auto- of insects and birds are not only related to of their larger fauna over the last few matic measuring systems that are made plant pollination and seed dispersal, but decades. The extent of faunal deple- available by technological innovation. also the ecosystem engineering functions tion and its consequences for veg- of termites and ants, which drive soil fertil- etation dynamics, fi re behaviour and (a) Key ecological process monitoring ity and productivity and, in so doing, infl u- fuel loads, nutrient cycles and spatial In addition to the already established ence the fi re regimes of African savannas. nutrient translocation, and ecosystem monitoring of variables that describe the services for local communities, need quantity and quality of biological organ- (c) Experiments urgently scientifi c attention. isms, in future we should enhance and in- Apart from the original grazing exclo- tegrate the monitoring of environmental sures and range management experi- variables and processes. Ecohydrological ments, which were included at the start of The road ahead monitoring, which includes the monitor- our activities in the region, additional ex- ing of water in the topsoil and how it is perimental approaches have already been For the future we will need a more func- used by vegetation, could quite easily be integrated in the Observation System to a tional understanding of the processes of established at many of the arid and semi- certain extent. Dantas et al. (2016) point- change in order to propose adequate re- arid observatories. ed to the role of fi re as a key mechanism sponses. Therefore, we regard it as neces- in maintaining the balance between alter-

B E 6 2018 393 nate biome states in tropical ecosystems in the past, and can even link up with re- individual tree species in order to make of West Africa. If fi re is indeed a tipping motely sensed data (Fig. 8). the most of drone imagery. However, the mechanism between savannas and wood- potential of this imagery as part of an in- lands, we need a sound understanding of The following country-specifi c perspec- tegrated long-term monitoring system is the diff erences between man-made and tives can be formulated for the biodiver- excellent. Of particular interest will be natural fi re regimes in terms of seasonal sity monitoring activities in Angola, Na- an extended use of Near Infrared (NIR) timing, return period, fi re intensity, and mibia, and South Africa: and Red Edge imagery available from fi re patterns. We also need to understand the Sequoia sensors, once these are avail- what the respective consequences of a) Angola: The fi rst few years of imple- able. Here we hope to greatly improve the human-dominated fi re regimes might be mentation of the standardised biodiversity monitoring of erosion rehabilitation and for the resilience of Africa’s forest and observatories have enabled us to establish of lichen fi eld dynamics after highly de- woodland ecosystems. At present, well a monitoring network and to build a base- structive disturbance events such as off - documented long term fi re experiments line to carry out essential analyses to un- road driving and the impact of fi lm sets. from Afrotropical grasslands are rather derstand the current status of biodiversity scarce, the long term fi re plots in South in the country. The way ahead consists of c) South Africa: The analyses of moni- Biodiversity Africas Kruger National Park being the the analysis of already-accumulated mon- toring data from the dry regions of South most prominent example (van Wilgen et itoring data in order to provide a better un- Africa have so far revealed the complex- al. 2007). derstanding of the dynamics of plant and ity of the interaction between changes in So far, we have established systematic animal communities, the environmental plant species composition of the vegeta- fi re experiments in the geoxylic grass- factors aff ecting species composition and tion, the population dynamics of individ- lands of the Angolan observatories Cuss- habitat conditions, and to create compara- ual species, and the environmental driv- eque (S74) and Bicuar National Park ble data layers on biodiversity status and ers such as climate, herbivory, and habitat (S75), which are located in direct prox- trends within the region. conditions. Current analyses of time-se- imity to woodland habitats. The experi- We must highlight that Angola faces ries data from the Succulent Karoo has ments follow a randomised block design a number of challenges in making a na- revealed that the commonly used classi- with three diff erent treatments – early dry tional biodiversity monitoring system op- fi cation of plants into so-called life-form season fi re (“cold fi re”), late dry season erational. The monitoring system needs types sensu Raunkiaer as plant strategy fi re (“hot fi re”), fi re exclosure (“control”) to secure the long-term sustainability of types is not suffi cient to explain the spe- – and 12 repetitions for each treatment. the observatory network that is already in cies’ responses to the rainfall patterns. We The experiment is carried out in a 1 ha place. The eff ective institutionalisation will therefore further refi ne the classifi ca- plot with 36 permanently marked sub- of the system is needed, as is a compre- tion of life form types for the Succulent plots of 15 m x 15 m each and a 5 m fi re- hensive program to maintain, strengthen, Karoo by taking into account traits that are break around the outer edge (Fig. 7). and expand Angola’s system of observa- related to the life span of the species and The experimental design allows for tories. As local capacity to conduct moni- to the strategies of resource allocation. analyses of selected functional traits of toring and the processing and analysing of For example, a quick response to high perennial plants, as well as of performance data is still our Achilles’ heel, we remain rainfall events versus protection of the indicators and species dynamics. Temper- committed to continue the empowerment water-storing organs against evaporation ature loggers are installed to measure mi- of a new generation of researchers able to or herbivory are two extremes along the croclimatic patterns and fi re heat. Changes address the scientifi c and technical needs continuum of traits. With regard to the en- in vegetation pattern will be documented for long-term biodiversity monitoring in vironmental drivers, we will place greater at regular intervals with drone photogra- the country. emphasis on understanding the seasonal- phy. In the future, we plan to extend this ity of rainfall and the number of rainfall experimental approach to additional ob- b) Namibia: Although drone survey- events that have an eff ect on plant growth servatories in the Miombo Biome. ing proved to be a fast and cost-eff ective (> 6 mm per rainfall event, Hanke et al., method to obtain baseline data, at best 2011) as well as the duration of periods (d) Automatic monitoring systems it yields information about the dynam- with no effi cient rainfall. It is a global trend in biodiversity obser- ics of individual woody plants and not The long-term data on vegetation dy- vation projects to make use of advances the composition of the herbaceous and namics will further be made available for in technology to complement existing graminoid layers of the vegetation. The global analyses on changes in diversity, monitoring activities. Automated data eff ective interpretation of such drone data species, or life form composition. The recording and photography, robotic sys- also requires detailed ground-truth data. study has already attracted great inter- tems, genomic sampling, and sound sen- Whereas in the past we concentrated on est from researchers all over the world sors, are available and have recently be- detailed data related to the composition and has contributed, for example, to a come more robust. Such electronically of all vegetation layers, we will in future global analysis on the infl uence of mean recorded data can be integrated more eas- need to collect additional data on grass annual precipitation on the proportion ily into the existing data framework than sward density and the specifi c location of of annual and perennial species in the

394 C A regional fl ora (Torma et al., in subm.). Hakalume, I. (2018) Assessing the population ronmental monitoring and assessment, 184, Findings from our analyses have also density of Neoluederitzia sericocarpa using 655–78. aerial imagery in Seeheim, Namibia. Bachelor Klintenberg P, Seely M. (2004) Land degradation been included in the global PREDICTS Honours in Natural Resources Management monitoring in Namibia: a fi rst approximation. database (Projecting Responses of Eco- mini-thesis, Namibia University of Science Environmental Monitoring and Assessment, logical Diversity in Changing Terrestrial and Technology. 99, 5-21. Hall, B.P. (1960). The faunistic importance of the Mbata, K.J. (2018) Annotated checklist of cock- Systems (Hudson et al., 2017), and have scarp of Angola. Ibis 102, 420–442. roaches and termites of Zambia (Arthropoda: contributed to the project “Drivers of Hanke, W., Böhner, J., Dreber, N., Jürgens, Insecta; Blattodea). This volume. communities’ temporal stability” of the N., Schmiedel, U., Wesuls, D. & Dengler, J. Mendelsohn JM, vanderPost C, Ramberg L, (2014) The impact of livestock grazing on Murray-Hudson M, Wolski P & Mosepele K. Czech Academy of Science. plant diversity: an analysis across dryland 2010. Okavango Delta: Floods of Life. RAI- ecosystems and scales in southern Africa. SON, Windhoek, 1-144. Ecological Applications, 24, 1188-1203. Meyer, G.E. & Neto, J.C. (2008) Verifi cation of Hanke, W., Gröngröft, A., Jürgens, N. & color vegetation indices for automated crop Acknowledgements Schmiedel, U. (2011) Rehabilitation of arid imaging applications. Computers and Elec- rangelands: Intensifying water pulses from tronics in Agriculture, 63, 282–293. low-intensity winter rainfall. Journal of Arid Mucina, L. & Rutherford, M.C. eds. (2006) The The research was carried out in the Environments, 75, 185-193. Vegetation of South Africa, Lesotho and Swa- framework of SASSCAL and was spon- Hauptfl eisch, M., Vinte, M. & Blaum, N. (2017) ziland, South African National Biodiversity sored by the German Federal Ministry of A comparison of the community dynamics of Institute, Pretoria. Biodiversity bioturbating small mammals between live- Mucina, L., Jürgens, N., Le Roux, A., Rutherford, Education and Research (BMBF) under stock and wildlife farming areas in the Kala- M.C., Schmiedel, U., Esler, K.J., Powrie, L.W., promotion number 01LG1201M. hari, Namibia. Namibian Journal of Environ- Desmet, P.G. & Milton, S.J. (2006) Succulent ment, Vol 1 (2017): Karoo Biome. The vegetation of South Africa, Hillmann, T., Muche, G., Josenhans, K. & Jür- Lesotho and Swaziland (ed. by L. Mucina and gens, N. (2018) Online presentation of the M.C. Rutherford), pp. 221-229. South African SASSCAL ObservationNet. This Volume. National Biodiversity Institute Pretoria. 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