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Appendices
Appendix I: Images that illustrate mining and rehabilitation of coastal dunes along
the northeast coast of KwaZulu-Natal, South Africa.
Plate 1. Heavy machinery is used to clear vegetation from the coastal dunes prior to the
extraction minerals from the sand.
Plate 2. The mine works as an open-cast dredging system whereby dune sand is taken up by a
bucket wheel and separated from the heavy minerals (~4% of the sand) by means of a cyclonic
system on the mining plant. This heavy mineral concentrate is taken to the smelt er site for
further processing where the rutile, zircon and ilmenite are further separated and prepared.
138 |
Appendices
Plate 3. Once separated from the heavy minerals, the sand is stacked into shapes that mimic the
pre-mining topographic profile.
Plate 4. Topsoil collected from cleared areas ahead of the mine is brought and spread over the
newly stacked dunes. This is then sown with annuals and indigenous to stabilize the dune as
soon as possible with a cover crop. Shade -netting is erected to prevent wind erosion, as well as
shade and protect seedlings.
139 |
Appendices
Seral stage 1
Plate 5. The cover crop grows up within months and between these annuals and grasses, Acacia
karroo seedlings begin to germinate (insert picture).
Plate 6. Within three years an impenetrable Acacia karroo shrubland has formed (at three years
there are 20724±2143 trees/ha (van Dyk 1996)).
140 |
Appendices
Seral stage 2
Plate 7. Within 11 years the Acacia karroo still dominates but has thinned to 737±35 trees/ha
by the age of 14 (van Dyk 1996). Forest canopy species are beginning to e merge, although the
understory is not well-developed
Plate 8. After about 20 years of age the Acacia karroo trees begin to senesce and fall over or
die standing (inset), forming canopy gaps of varying sizes. Although A. karroo remain
dominant, the understory has become more developed and forest canopy species are more
common.
141 |
Appendices
Seral stage 3
Plate 9. After 30 years gaps of all sizes have formed as Acacia karroo continue to fall down.
The forest is multi-layered and forest canopy trees are in excess of 8m tall.
Plate 10. In these oldest stands (35 years) Acacia karroo has thinned to 141±11 trees/ha (van
Dyk 1998), larger gaps comprise grassy patches and clumps of forest tree species . Importantly,
these gaps are not recolonized by A. karroo (Grainger 2012).
142 |
Appendices
Appendix II: List of species from three taxa recorded in the study area
Table A-1. List of woody plant species identified in the regenerating and unmined forests, third
column indicates species associated with forest habitats ( ).
Species
Family
Acalypha glabrata
Acacia karroo
Acacia kraussiana
Acokanthera oppositifolia
Albizia adianthifolia
Allophylus africanus
Allophylus natalensis
Annona senegalensis
Antidesma venosum
Apodytes dimidiata
Artabotrys monteiroae
Barringtonia racemosa
Bauhinia tomentosa
Bersama lucens
Brachylaena discolor
Bridelia cathartica
Bridelia micrantha
Canthium inerme
Capparis sepiaria
Capparis tomentosa
Carissa bispinosa
Carissa macrocarpa
Casuarina equisetifolia
Cassine eucleiformis
Cassipourea gummiflua
Cassipourea malosana
Cassine tetragona
Cassinopsis tinifolia
Catunaregam spinosa
Celtis africana
Cestrum laevigatum
Chaetacme aristata
Chionanthus battiscombei
Chionanthus foveolatus
Chionanthus peglerae
Chrysanthemoides monilifera
Citrus lemon
Clausena anisata
Euphorbiaceae
Mimosaceae
Mimosaceae
Apocynaceae
Mimosaceae
Sapindaceae
Sapindaceae
Annonaceae
Euphorbiaceae
Icacinaceae
Annonaceae
Lecythidaceae
Caesalpiniaceae
Melianthaceae
Asteraceae
Euphorbiaceae
Euphorbiaceae
Rubiaceae
Capparaceae
Capparaceae
Apocynaceae
Apocynaceae
Casuarinaceae
Celastraceae
Rhizophoraceae
Rhizophoraceae
Celastraceae
Icacinaceae
Rubiaceae
Ulmaceae
Solanaceae
Ulmaceae
Oleaceae
Oleaceae
Oleaceae
Asteraceae
Rutaceae
Rutaceae
Forest-associated species

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143 |
Appendices
Clerodendrum glabrum
Clerodendrum myricoides
Cola natalensis
Commiphora neglecta
Cordia caffra
Croton sylvaticus
Cussonia sphaerocephala
Dalbergia armata
Deinbollia oblongifolia
Dichrostachys cinerea
Diospyros inhacaensis
Diospyros lycioides
Diospyros natalensis
Dodonaea angustifolia
Dovyalis longispina
Dovyalis rhamnoides
Dracaena aletriformis
Drypetes natalensis
Drypetes reticulata
Ekebergia capensis
Elaeodendron croceum
Englerophytum natalense
Ephippiocarpa orientalis
Erythrococca berberidea
Erythroxylum emarginatum
Erythrina lysistemon
Euclea natalensis
Euclea racemosa subsp. sinuata
Eugenia capensis
Eugenia natalitia
Ficus burtt-davyi
Ficus craterostoma
Ficus lutea
Ficus natalensis
Ficus polita
Ficus sur
Ficus sycomorus
Ficus trichopoda
Garcinia livingstonei
Gardenia thunbergia
Grewia caffra
Grewia occidentalis
Halleria lucida
Harpephyllum caffrum
Hibiscus tiliaceus
Verbenaceae
Verbenaceae
Sterculiaceae
Burseraceae
Boraginaceae
Euphorbiaceae
Araliaceae
Fabaceae
Sapindaceae
Mimosaceae
Ebenaceae
Ebenaceae
Ebenaceae
Sapindaceae
Flacourtiaceae
Flacourtiaceae
Dracaenaceae
Euphorbiaceae
Euphorbiaceae
Meliaceae
Celastraceae
Sapotaceae
Apocynaceae
Euphorbiaceae
Erythroxylaceae
Fabaceae
Ebenaceae
Ebenaceae
Myrtaceae
Myrtaceae
Moraceae
Moraceae
Moraceae
Moraceae
Moraceae
Moraceae
Moraceae
Moraceae
Clusiaceae
Rubiaceae
Tiliaceae
Tiliaceae
Scrophulariaceae
Anacardiaceae
Malvaceae
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144 |
Appendices
Hymenocardia ulmoides
Inhambanella henriquesii
Keetia gueinzii
Kiggelaria africana
Kraussia floribunda
Lagynias lasiantha
Lantana camara
Macaranga capensis
Maesa lanceolata
Maerua nervosa
Manilkara concolor
Manilkara discolor
Maytenus cordata
Maytenus heterophylla
Gymnosporia mossambicensis
Gymnosporia nemorosa
Maytenus procumbens
Gymnosporia senegalensis
Maytenus undata
Melia azedarach
Mimusops caffra
Mimusops obovata
Monanthotaxis caffra
Myrica serrata
Mystroxylon aethiopicum
Ochna arborea
Ochna natalitia
Olea capensis
Olea woodiana
Osyris compressa
Oxyanthus speciosus
Ozoroa obovata
Pancovia golungensis
Parinari capensis subsp. incohata
Passerina rigida
Pavetta lanceolata
Pavetta natalensis
Pavetta revoluta
Pavetta Sp01
Peddiea africana
Persea americana
Phoenix reclinata
Pinus elliotti
Pisonia aculeata
Protorhus longifolia
Euphorbiaceae
Sapotaceae
Rubiaceae
Flacourtiaceae
Rubiaceae
Rubiaceae
Verbenaceae
Euphorbiaceae
Myrsinaceae
Capparaceae
Sapotaceae
Sapotaceae
Celastraceae
Celastraceae
Celastraceae
Celastraceae
Celastraceae
Celastraceae
Celastraceae
Meliaceae
Sapotaceae
Sapotaceae
Annonaceae
Myricaceae
Celastraceae
Ochnaceae
Ochnaceae
Oleaceae
Oleaceae
Santalaceae
Rubiaceae
Anacardiaceae
Sapindaceae
Chrysobalanaceae
Thymelaeaceae
Rubiaceae
Rubiaceae
Rubiaceae
Rubiaceae
Thymelaeaceae
Lauraceae
Arecaceae
Pinaceae
Nyctaginaceae
Anacardiaceae
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145 |
Appendices
Psidium guajava
Psychotria capensis
Psydrax obovata
Rapanea melanophloeos
Rauvolfia caffra
Rhoicissus digitata
Rhoicissus revoilii
Rhoicissus rhomboidea
Rhoicissus tomentosa
Rhoicissus tridentata
Rhus natalensis
Rhus nebulosa
Ricinus communis
Rothmannia globosa
Salacia gerrardii
Sapium integerrimum
Schinus terebinthifolius
Schefflera umbellifera
Sclerocarya birrea
Scolopia zeyheri
Scutia myrtina
Senna pendula
Sideroxylon inerme
Solanum mauritianum
Strychnos gerrardii
Strychnos henningsii
Strychnos madagascariensis
Strychnos mitis
Strelitzia nicolai
Strychnos spinosa
Strychnos usambarensis
Syzygium cordatum
Syzygium cumini
Tarenna junodii
Tarenna littoralis
Tarenna pavettoides
Tecomaria capensis
Teclea gerrardii
Thespesia acutiloba
Trema orientalis
Tricalysia delagoensis
Trichilia dregeana
Trichilia emetica
Tricalysia lanceolata
Tricalysia sonderiana
Myrtaceae
Rubiaceae
Rubiaceae
Myrsinaceae
Apocynaceae
Vitaceae
Vitaceae
Vitaceae
Vitaceae
Vitaceae
Anacardiaceae
Anacardiaceae
Euphorbiaceae
Rubiaceae
Celastraceae
Euphorbiaceae
Anacardiaceae
Araliaceae
Anacardiaceae
Flacourtiaceae
Rhamnaceae
Caesalpiniaceae
Sapotaceae
Solanaceae
Loganiaceae
Loganiaceae
Loganiaceae
Loganiaceae
Strelitziaceae
Loganiaceae
Loganiaceae
Myrtaceae
Myrtaceae
Rubiaceae
Rubiaceae
Rubiaceae
Bignoniaceae
Rutaceae
Malvaceae
Ulmaceae
Rubiaceae
Meliaceae
Meliaceae
Rubiaceae
Rubiaceae
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146 |
Appendices
Turraea floribunda
Turraea obtusifolia
Uvaria caffra
Vangueria cyanescens
Vangueria infausta
Vangueria randii
Vepris lanceolata
Voacanga thouarsii
Xylotheca kraussiana
Zanthoxylum capense
Ziziphus mucronata
Meliaceae
Meliaceae
Annonaceae
Rubiaceae
Rubiaceae
Rubiaceae
Rutaceae
Apocynaceae
Flacourtiaceae
Rutaceae
Rhamnaceae

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147 |
Appendices
Table A-2. List of millipede species identified in the regenerating and unmined forests, third
column indicates species associated with forest habitats ( ).
Species
Family
Doratogonus sp.
Centrobolus fulgidus
Centrobolus richardii
Centrobolus rugulosus
Spirostreptidae
Spirobolidae
Spirobolidae
Spirobolidae
Gnomeskelus tuberosus
Orthroporoides sp.*
Orthroporoides pyrocephalus
Sphaerotherium giganteum
Sphaerotherium punctulatum
Sphaerotherium rotundatum
Sphaerotherium sp. B
Sphaerotherium sp. C
Sphaerotherium sp. D
Sphaerotherium sp. E
Sphaerotherium sp. F
Spinotarsus anguliferus
Spirostreptidae sp. Imm.
Spirostreptidae sp. Imm. 2
Ulodesmus micramma zuluensis
Dalodesmidae
Spirostreptidae
Spirostreptidae
Sphaerotheridae
Sphaerotheridae
Sphaerotheridae
Sphaerotheridae
Sphaerotheridae
Sphaerotheridae
Sphaerotheridae
Sphaerotheridae
Odontopygidae
Spirostreptidae
Spirostreptidae
Dalodesmidae
Forestassociated
species
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148 |
Appendices
Table A-3. List of dung beetle species identified in the regenerating and unmined forests, third
column indicates species associated with forest habitats ( ).
Species
Allogymnopleurus thalassinus
Anachalcos convexus
Caccobius nigritulus
Caccobius obtusus
Caccobius sp. 1
Caccobius sp. 2
Caccobius sp. 3
Caccobius sp. 4
Caccobius sp. 5 = Caccobius cavatus
Catharsius sp 1 (endemic)
Catharsius mossambicanus
Catharsius tricornutus
Cleptocaccobius viridicollis
Copris inhalatus ssp santaluciae
Copris puncticollis
Copris urus
Digitonthophagus gazella
Drepanocerus impressicollis (now Afrodrepanus impressicollis)
Drepanocerus kirbyi
Euoniticellus intermedius
Garreta azureus
Garreta unicolor
Gyronotus carinatus
Heliocopris hamadryas
Hyalonthophagus alcyonides
Kheper lamarcki
Liatongus militaris
Metacatharsius sp. 1 (=zuluanus)
Milichus sp. 1
Neosisyphus confrater
Neosisyphus mirabilis
Neosisyphus spinipes
Odontoloma sp.
Oniticellus formosus
Oniticellus planatus
Onthophagus aeruginosus
Onthophagus ambiguus (now Mimonthophagus ambiguus)
Onthophagus bicavifrons
Onthophagus depressus
Onthophagus fimetarius (coastal var.) possibly new
Onthophagus flavolimbatus
Onthophagus lacustris
Onthophagus nanus
Onthophagus obtusicornis
Onthophagus pugionatus
Onthophagus quadrinodosus
Onthophagus signatus
Onthophagus sp 1 (=horned pullus)
Onthophagus sp. 2 (v. small endemic)
Forestassociated
species



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149 |
Appendices
Onthophagus sp 3 (=sp. e George)
Onthophagus sp 4
Onthophagus sp nr bicavifrons
Onthophagus sp. nr sugillatus (coastal var.) possibly new
Onthophagus ursinus
Onthophagus vinctus
Onthophagus stellio or variegatus gp??
Onthophagus sp - mottled tail
Onthophagus sp A
Pachylomerus femoralis
Pedaria sp. IV
Pedaria sp. III
Proagoderus aciculatus
Proagoderus aureiceps
Proagoderus brucei (now P. chalcostolus)
Scarabaeus bornemisszai
Scarabaeus goryi
Sisyphus natalensis (cited as the syn. S. bornemisszanus)
Sisyphus seminulum
Sisyphus sordidus
Sisyphus sp nr gazanus
Sisyphus sp y
Stiptopodius sp. 1
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150 |
Appendices
Table A-4. List of bird species identified in the regenerating and unmined forests, third column
indicates species associated with forest habitats ( ).
Species
Common Name
Acrocephalus palustris
Alcedo cristata
Amblyospiza albifrons
Andropadus importunus
Anthus cinnamomeus
Apalis flavida
Apalis ruddi
Apalis thoracica
Apalpderma narina
Aplopelia larvata
Ardea melanocephala
Batis capensis
Batis fratrum
Bostrychia hagedash
Bradornis pallidus
Bycanistes bucinator
Calendulauda sabota
Camaroptera brachyura
Campephaga flava
Campethera abingoni
Caprimulgus europaeus
Centropus burchellii
Cercotrichas leucophrys
Cercotrichas quadrivirgata
Cercotrichas signata
Ceuthmochares aereus
Chalcomitra amethystina
Chalcomitra senegalensis
Chlorocichla falviventris
Chrysococcyx caprius
Chrysococcyx cupreus
Chrysococcyx klaas
Cinnyris bifasciata
Cisticola chinianus
Cisticola cinnamomeus
Cisticola fulvicapilla
Cisticola juncidis
Cisticola natelensis
Clamator jacobinus
Coccopygia melanotis
Eurasian Marsh Warbler
Malachite Kingfisher
Thick-billed Weaver
Sombre Greenbul
African Pipit
Yellow-breasted Apalis
Rudd's Apalis
Bar-throated Apalis
Narina Trogon
Lemon Dove
Black-headed Heron
Cape Batis
Woodwards' Batis
Hadeda Ibis
Pale Flycatcher
Trumpeter Hornbill
Sabota Lark
Green-backed Camaroptera
Black Cuckooshrike
Golden-tailed Woodpecker
European Nightjar
Burchell's Coucal
White-browed Scrub-Robin
Bearded Scrub-Robin
Brown Scrub-Robin
Green Malkoha
Amethyst Sunbird
Scarlet-chested Sunbird
Yellow-bellied Greenbul
Diederik Cuckoo
African Emerald Cuckoo
Klaas's Cuckoo
Purple-banded Sunbird
Rattling Cisticola
Pale-crowned Cisticola
Neddicky
Zitting Cisticola
Croaking Cisticola
Jacobin Cuckoo
Swee Waxbill
Forest-associated
species
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151 |
Appendices
Colius striatus
Columba delegorguei
Coracias caudata
Coracias garrulus
Coracina caesia
Corvus albus
Cossypha caffra
Cossypha dichroa
Cossypha natalensis
Coturnix coturnix
Cuculus canorus
Cuculus gularis
Cuculus solitarius
Cyanomitra olivacea
Cyanomitra veroxii
Dendropicos fuscescens
Dendropicos griseocephalus
Dicrurus adsimilis
Dicrurus ludwigii
Dryoscopus cubla
Estrilda astrild
Estrilda perreini
Euplectes axillaris
Euplectes orix
Eurystomus glaucurus
Guttera edouardi
Halcyon albiventris
Hedydipna collaris
Hippolais icterina
Indicator minor
Indicator variegatus
Ispidina picta
Lagonosticta rubricata
Lamprotornis corruscus
Laniarius ferrugineus
Lanius collaris
Lanius collurio
Lanius minor
Lonchura cucllata
Lonchura nigriceps
Lybius torquatus
Macronyx croceus
Malaconotus blanchoti
Mandingoa nitidula
Speckled Mousebird
Eastern Bronze-naped Pigeon
Lilac-breasted Roller
Eurasian Roller
Grey Cuckooshrike
Pied Crow
Cape Robin-Chat
Chorister Robin-Chat
Red-capped Robin-Chat
Common Quail
Common Cuckoo
African Cuckoo
Red-chested Cuckoo
Eastern Olive Sunbird
Grey Sunbird
Cardinal Woodpecker
Olive Woodpecker
Fork-tailed Drongo
Square-tailed Drongo
Black-backed Puffback
Common Waxbill
Grey Waxbill
Fan-tailed Widowbird
Southern Red Bishop
Broad-billed Roller
Crested Guineafowl
Brown-hooded Kingfisher
Collared Sunbird
Icterine Warbler
Lesser Honeyguide
Scaly-throated Honeyguide
African Pygmy-Kingfisher
African Firefinch
Black-bellied Starling
Southern Boubou
Common Fiscal
Red-backed Shrike
Lesser Grey Shrike
Bronze Mannikin
Red-backed Mannikin
Black-collared Barbet
Yellow-throated Longclaw
Grey-headed Bush-Shrike
Green Twinspot
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152 |
Appendices
Megaceryle maxima
Melaenornis pammelaina
Merops pusillus
Mirafra africana
Monticola rupestris
Motacilla aguimp
Motacilla capensis
Muscicapa adusta
Muscicapa caerulescens
Muscicapa striata
Musophaga porphyreolopha
Myioparus plumbeus
Nicator gularis
Oriolus larvatus
Oriolus oriolus
Passer domesticus
Phyllastrephus terrestris
Phylloscopus trochilus
Platysteira peltata
Plectropterus gambensis
Ploceus
Ploceus bicolor
Ploceus cucullatus
Ploceus intermedius
Ploceus ocularis
Ploceus subaureus
Pogoniulus bilineatus
Pogoniulus pusillus
Pogonocichla stellata
Prinia subflava
Pycnonotus tricolor
Rhinopomastus cyanomelas
Sarothrura elegans
Saxicola torquata
Serinus canicollis
Serinus mozambicus
Serinus sulphuratus
Sigelus silens
Smithornis capensis
Stactolaema leucotis
Streptopelia capicola
Streptopelia semitorquata
Sylvia borin
Sylvietta rufescens
Giant Kingfisher
Southern Black Flycatcher
Little Bee-eater
Rufous-naped Lark
Cape Rock-Thrush
African Pied Wagtail
Cape Wagtail
African Dusky Flycatcher
Ashy Flycatcher
Spotted Flycatcher
Purple-crested Turaco
Grey Tit-Flycatcher
Eastern Nicator
Black-headed Oriole
Eurasian Golden Oriole
House Sparrow
Terrestrial Brownbul
Willow Warbler
Black-throated Wattle-eye
Spur-winged Goose
Weavers
Dark-backed Weaver
Village Weaver
Lesser Masked-Weaver
Spectacled Weaver
Yellow Weaver
Yellow-rumped Tinkerbird
Red-fronted Tinkerbird
White-starred Robin
Tawny-flanked Prinia
Dark-capped Bulbul
Common Scimitarbill
Buff-Spotted Flufftail
African Stonechat
Cape Canary
Yellow-fronted Canary
Brimstone Canary
Fiscal Flycatcher
African Broadbill
White-eared Barbet
Cape Turtle Dove
Red-eyed Dove
Garden Warbler
Long-billed Crombec
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
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
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153 |
Appendices
Tauraco corythsix
Tauraco livingstonii
Tchagra australis
Tchagra senegala
Telophorus olivaceus
Telophorus quadricolor
Telophorus sulfureopectus
Terpsiphone viridis
Tockus alboterminatus
Trachyphonus vallantii
Treron calva
Trochocercus cyanomelas
Turdus libonyanus
Turtur chalcospilos
Turtur tympanistria
Uraeginthus angolensis
Urocolius indicus
Vidua macroura
Zoothera guttata
Zosterops virens
Knysna Turaco
Livingstone's Turaco
Brown-crowned Tchagra
Black-crowned Tchagra
Olive Bush-Shrike
Gorgeous Bush-Shrike
Orange-breasted Bush-Shrike
African Paradise-Flycatcher
Crowned Hornbill
Crested Barbet
African Green-Pigeon
Blue-mantled Crested Flycatcher
Kurrichane Thrush
Emerald-spotted Wood-Dove
Tambourine Dove
Blue Waxbill
Red-faced Mousebird
Pin-tailed Whydah
Spotted Ground-Thrush
Cape White-eye
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154 |
Appendices
1
Appendix III: Manuscript accepted for publication at Landscape and Ecological
2
Engineering (DOI: 10.1007/s11355-013-0211-1).
3
Journal: Landscape and Ecological Engineering
4
Manuscript type: Original paper
5
6
Title: Coastal dune topography as a determinant of abiotic conditions and biological
7
community restoration in northern Kwazulu-Natal, South Africa
8
9
Authors:
Ott, Theresia; Conservation Ecology Research Unit, Department of Zoology
10
and Entomology, University of Pretoria ; [email protected]
11
van Aarde, Rudi, J. ; Conservation Ecology Research Unit, Department of
12
Zoology and Entomology, University of Pretoria; [email protected] ;
13
tel. +2712 420 2535; fax +2786 653 3970
14
15
Keywords: aspect, dune morphology, elevation, gradient, microclimate, soil
16
Word count: 4,813 (including main text and references)
17
155 |
Appendices
18
Abstract
19
Topography is rarely considered as an independent goal of restoration. Yet, topography
20
determines micro-environmental conditions and hence living conditions for species.
21
Restoring topography may therefore be an important first step in ecological restoration. We
22
aimed at establishing the relative importance of topography where coastal dunes destroyed by
23
mining are rebuilt as part of a rehabilitation programme.
24
We assessed the response of 1) microclimatic and soil conditions, and 2) woody plant
25
and millipede species richness and density, to location-specific topographic profiles. We
26
enumerated the topographic profile using variables of dune morphology (aspect, elevation
27
and gradient) as well as relative position on a dune (crest, slope, valley).
28
Temperature, relative humidity and light intensity varied with aspect, elevation,
29
gradient and position. However, regeneration age was a better predictor of soil nutrient
30
availability than these topographic variables. Age also interacted with topographic variables
31
to explain tree canopy density and species richness, as well as millipede species richness. The
32
density of keeled millipedes (forest specialists) was best explained by topographic variables
33
alone. The transient nature of these new-growth coastal dune forests likely masks
34
topography-related effects on communities because age-related succession (increasing
35
structural complexity) drives the establishment and persistence of biological communities,
36
not habitat conditions modulated by topography. However, our study has shown that the
37
microhabitats associated with topographic variability influence specialist species more than
38
generalists.
39
40
156 |
Appendices
41
Introduction
42
Ecological restoration is widely recognised as a conservation tool and aims to re-instate
43
natural processes that sustain biological diversity (Dobson et al. 1997; MacMahon & Holl
44
2001; Rands 2012). Such diversity is determined by both regional and local forces, the latter
45
often as a function of topography due to cascadal effects on microclimatic conditions, water
46
retention, and nutrient availability (Larkin et al. 2006). These relationships are especially
47
well-documented in mountainous regions (Burnett et al. 1998; Nichols et al. 1998; Tateno &
48
Takeda 2003; da Silva et al. 2008), but less often for coastal sand dune ecosystems (e.g.
49
Martínez et al. 2001; Acosta et al. 2007). The restoration of topography may be a priority
50
(Weiss & Murphy 1990; Palik et al. 2000; Larkin et al. 2006), but difficult or costly to
51
achieve. However, an approximation of the original topography may be sufficient to maintain
52
desired ecological processes. This may well be the case in our study areas where succession
53
drives forest regeneration, but where the full complement of species has not yet been
54
regained (van Aarde et al. 1996b; Grainger 2012). This may be due to the micro-
55
environmental needs of specialist species not being met due to constraints imposed by
56
topography. Justification to restore terrain requires an assessment of the relevance of
57
topography for species and ecological processes. In this study, we assess the influence of
58
dune topography on abiotic and biotic conditions (Table ) in coastal dune forests regenerating
59
in response to an ecological restoration program.
60
The aspect, elevation, and gradient of slopes are collectively referred to as dune
61
morphology, while the relative position is described as the crest, slope, or valley. These
62
variables of dune topography can modulate habitat conditions in various ways (Larkin et al.
63
2006). For example, nutrients leaching from dune crests into valleys where plant-
64
communities are light-limited results in nutrient-limited communities on crests, but greater
65
nutrient availability in valleys (Tateno & Takeda 2003). Canopy structure changes with
157 |
Appendices
66
gradients in soil fertility and light (Nichols et al. 1998; Tateno & Takeda 2003), even with
67
limited altitudinal variation (da Silva et al. 2008). This may explain patterns in plant species
68
composition, abundance, and distribution (Chen et al. 1997; Oliviera-Filho et al. 1998). The
69
aspect and gradient of dune slopes may amplify these differences as they also influence light
70
availability (Oliviera-Filho et al. 1998; Bennie et al. 2008) and wind exposure (Chen et al.
71
1997; Acosta et al. 2007). Wind sculpts tree canopies (Kubota et al. 2004), hastens canopy
72
gap formation (Ritter et al. 2005), and contributes to seed dispersal (Furley & Newey 1979).
73
The windward slopes of coastal dunes have higher evaporation rates than leeward slopes and
74
are more exposed to salt spray that increases salt concentrations in the soil, in turn
75
influencing soil pH and the availability of nutrients (Furley & Newey 1979; Chen et al. 1997;
76
Acosta et al. 2007). We therefore hypothesized that dune morphology and position would 1)
77
modulate microclimatic conditions (temperature, relative humidity, and light intensity) and 2)
78
influence soil nutrient availability (C:N ratio) and soil pH (see Table ). Disturbed or
79
destroyed topographic profiles could therefore hinder the ecological restoration of plant and
80
animal communities of new-growth forests, or simply alter heterogeneity and rearrange the
81
distribution of resources. Thus the structure and composition of biotic communities at
82
locations with different dune morphologies should be assessed to determine the importance of
83
restoring the topographic profile.
84
Topography influences plant growth and species richness in old-growth forests
85
(Tateno & Takeda 2003; da Silva et al. 2008), which has cascadal effects on biota through the
86
responses of microclimatic conditions to topography (Larkin et al. 2006). Physiological trade-
87
offs associated with the small size and ectothermy of invertebrates, such as millipedes,
88
renders them sensitive to microclimatic conditions that dictate habitat preferences (Ashwini
89
& Sridhar 2008; Loranger-Merciris et al. 2008; David & Gillon 2009). We therefore assessed
90
the importance of the topographic profile in structuring millipede assemblages. We
158 |
Appendices
91
hypothesized that within a seral stage, dune morphology and position would 3) influence
92
plant community structure and composition, and 4) millipede community structure and
93
composition in regenerating stands of new-growth coastal dune forest (Table ). If millipedes
94
respond to topography, changes in the topographic profile should result in changes in
95
millipede diversity. If this is not the case, topography has a limited role to play, if any, in
96
explaining millipede community structure. Although this study is based upon coastal dune
97
forests, it may have implications for any disturbed dune system under restoration.
98
Methods
99
Study area
100
The study area was located north of Richards Bay town (between 28°46' and 28°34' south) on
101
the sub-tropical north coast of Kwazulu-Natal, South Africa (Fig. 1). The climate is humid
102
with a mean annual rainfall of 1458 ± 493.5 mm (mean ± SD, n = 34 years between 1976 and
103
2009), peaking in February. The mean annual temperature was 23.79 ± 3.40°C (n = 3 years
104
between 2006 and 2009. Winds of between 10 and 40 km.h-1 blew from the north-east for
105
about 20% of the time, as did those from south-south west and south-west combined (data
106
courtesy of Richards Bay Minerals).
107
The establishment of forests on the coastal dunes here occurred with the return of
108
warm interglacial conditions between 6,500 and 4,000 years ago, making them among the
109
highest vegetated dunes in the world (Weisser & Marques 1979; Lawes 1990). These forests
110
are therefore relatively young and harbour few endemic species (Lawes 1990; van Wyk &
111
Smith 2001). Coastal dune forests are sensitive to disturbance but previous work has shown
112
that they are relatively resilient and are thus able to recover (e.g. Wassenaar et al. 2005;
113
Grainger et al. 2011).
159 |
Appendices
114
Richards Bay Minerals (RBM) has leased this area since 1976 for the extraction of
115
heavy metals from the coastal sands. Ahead of the dredging pond, all vegetation was cleared
116
and the dunes were collapsed for mining. After mining, sand tailings were stacked to
117
resemble pre-mining topography and were covered with topsoil (van Aarde et al. 1996c). A
118
third of the mined area was set aside for the restoration of indigenous coastal dune forest and
119
this area comprised known-aged stands that at the time of the study ranged in age from 1 year
120
(in the northeast) to 33 years (in the southwest) (see Fig. 1). This age-range represented three
121
seral stages based on those defined by Grainger (2012): seral stage one = 1-10 years, two =
122
11-25 years, and three >25 years. Adjoined by a coastal strip of unmined vegetation about
123
200 m wide, the stands were themselves no wider than 2 km, set in a mosaic of active mining
124
areas, plantations, degraded woodland, and rural villages (Wassenaar et al. 2005).
125
Microclimatic data
126
Fifteen HOBO® 4-channel data loggers (Onset Computer Corporation, 470 MacArthur Blvd.,
127
Bourne, MA 02532, U.S.A.) were deployed in the 22-year old stand (see Fig. 1) on custom-
128
made platforms placed 10 cm above the ground (five on the crest, five on a slope and five in
129
the valley). We programmed these loggers to record ground-level temperature, relative
130
humidity, and light intensity (see Table 2 for definitions) every 10 minutes between 08:00, 28
131
January and 05:00, 4 February 2011, yielding 14,850 records.
132
Soil surveys
133
An auger was used to collect soil samples to 20 cm depth at the corners and centre of each of
134
the millipede survey transects (see below). These five samples were mixed into a single bag
135
and consequently 65 bags were analyzed at the Department of Plant Production and Soil
136
Science at the University of Pretoria using procedures described in van Aarde et al. (1998;
137
see supplementary information for detailed chemical profile). We used Nitrogen and Carbon
160 |
Appendices
138
concentrations to calculate the carbon-to-nitrogen ratio (C:N, Table 2) and included the pH
139
values of each sample in our analysis.
140
Woody plant surveys
141
All woody plants taller than 0.2 m in 106 randomly placed quadrats (16×16–m, at least 100 m
142
apart) in six stands of known regeneration age (10, 14, 18, 22, 26, and 33 years) were
143
sampled between July and November 2010. Each plant was identified against reference
144
material. We calculated six variables of woody plant community structure for each quadrat
145
(see Table 2).
146
Millipede surveys
147
Millipede species occurring on the ground up to 3 m on plants were counted between 13
148
January and 4 February 2011 in 65 randomly placed transects within a 10, 14, 18, 22, 26, and
149
33 year-old stand (see Fig. 2). Each transect was 32 × 6–m wide and comprised 48 2 × 2–m
150
cells. Surveys were conducted by three observers per transect, each responsible for a column
151
of 16 cells. All millipedes found in a cell during five minutes were identified based on
152
reference images and descriptions (Porter et al. 2007), counted, and removed to avoid
153
recounting. We calculated the number of millipede species and the density of cylindrical,
154
keeled, and pill millipedes (see Table 2) within each location-specific transect.
155
Topographic data
156
We used classified topographic data based on eight cardinal directions (aspect), seven
157
elevation categories, and five gradient categories that had been extracted from a topographic
158
map (see Fig.1.) based on a Light Detection and Ranging (LIDAR) mission conducted in
159
2010 (post-mining). We used GIS overlay procedures to relate all of the sampling points and
160
quadrat locations recorded in the field to location-specific variables of dune morphology
161
based on the topographic maps.
161 |
Appendices
162
Statistical analyses
163
We used stratified random sampling to extract one microclimate record (including the
164
temperature, relative humidity, and light intensity readings) per hour, per logger for each
165
sampling day (29 January – 3 February 2011), rendering 2,475 records to be included in
166
analyses. We log10-transformed the light intensity data to meet assumptions for analyses of
167
variance (ANOVA). To determine whether microclimatic conditions were modulated by
168
topography, we conducted repeated measures ANOVA with hour and day as repeated
169
measures factors, and categorized variables of dune morphology as between-groups factors.
170
We assessed the influence of dune morphological variables on soil C:N ratios and pH,
171
as well as woody plant and millipede community variables in each of the three seral stages.
172
We assessed these using generalized linear models with age as a covariate (Analyses of
173
Covariance (ANCOVA) for all seral stages for woody plants and seral stages 2 and 3 for soil
174
and millipedes. Millipede and soil data for seral stage 1 comprised too few cases and was
175
therefore not assessed separately. All statistical analyses were conducted using STATISTICA
176
10 (Statsoft Inc., Tulsa, Oklahoma).
177
Woody plant and millipede species abundance data were log10-transformed and
178
calculated the similarity between quadrats, with different dune morphological characteristics
179
using the Bray-Curtis index. Cluster analyses and non-metric multi-dimensional scaling
180
(NMDS) were used to detect community clusters based on the four characteristics of dune
181
morphology. Analyses of similarity (ANOSIM) allowed us to assess the significance of
182
community groupings based on dune morphology within each successional stage. To identify
183
the distinguishing species, we conducted similarity percentage (SIMPER) analyses
184
(SIMPER) for those community groupings that differed significantly based on dune
185
morphological characteristics. All multivariate techniques were conducted using PRIMER 6
186
software (Clarke 1993).
162 |
Appendices
187
Results
188
Dune topography and abiotic variables
189
Temperature was significantly modulated by aspect and gradient when sampling day and time
190
of day were taken into account (repeated measures ANOVA: F(575, 1035) = 1.33, p < 0.001 and
191
F(230, 1380) = 1.27, p = 0.007, respectively). Similarly, relative humidity was significantly
192
modulated by elevation (F(345, 1265) = 1.7632, p < 0.001), gradient (F(230, 1380) = 1.69, p < 0.001)
193
and position (F(230, 1380)=1.65, p < 0.001), while light intensity was influenced by aspect (F(575,
194
1035) =
195
and lighter than other slopes, although south-facing slopes were also relatively warm. Low-
196
lying areas were relatively humid compared to higher dunes. Slopes with mid-range steepness
197
were generally more humid, but cooler than comparatively gentle and steep slopes. Valleys
198
were generally more humid and darker than crests and slopes. For illustrative purposes, we
199
presented one day’s data for these significant cases (see Fig. 2).
200
1.93, p < 0.001) and position (F(230, 1380)=1.38, p < 0.001). Northern slopes were hotter
Variability in soil pH was best explained by age in seral stage 2, and a model
201
including aspect, elevation, and position in addition to age in seral stage 3 (ANCOVA and
202
AIC; Table 3). However, none of the models significantly explained variability in soil C:N
203
ratios (Table 3).
204
Dune topography and biotic variables
205
The 8,833 woody plants sampled in 106 quadrats comprised 7,122 canopy and 1,736
206
understory plants among 88 species. Variability in all woody plant variables was best
207
explained by models that included age as a covariate within pooled seral stages, as was the
163 |
Appendices
case
when plants
seral stage 2 was treated separately (ANCOVA and AIC;
Woody
b
10
Canopy tree species
(number/quadrat)
Canopy tree species
(number/quadrat)
a
8
6
4
2
0
N NE E SE S SW W NW
Aspect
Canopy tree species
(number/quadrat)
c
4
2
0
Crest
Slope
Position
Canopy tree density
(number/100 m2)
e
6
4
2
0
6-10 11-15 16-20
Gradient (degrees)
>20
10
8
6
4
2
0
41-60
61-80 81-100 101-120
Elevation (m.a.s.l.)
30
25
20
15
10
5
0
0-5
209
8
d
8
6
10
0-5
Canopy tree species
(number/quadrat)
208
6-10
11-15
Gradient (degrees)
210
Figure 5-3. Mean ± one standard deviation of the mean of woody plant response variables
211
presented as a function of those variables that best-explained their variability significantly
212
despite stand age (see Table 2).
164 |
Appendices
213
Table 5-3). The number of tree canopy species in seral stage 1 was best explained by a model
214
including aspect, elevation, gradient, and position, but not age. There were more species on
215
west- and northwest-facing slopes compared to south- and southwest-facing slopes (Fig. 3a),
216
while relatively flat slopes had fewer species than other gradients (Figure 5-3b), as did crests
217
relative to slopes (Fig. 3c). However, canopy tree species richness varied little with elevation
218
(Fig. 3d). Tree density in seral stage 3 increased significantly with gradient (ANCOVA and
219
AIC; Fig. 3e).
220
Only 11% of the variability in tree species abundances was explained by gradient in
221
seral stage 2, although the NMDS plot was unconvincing of this separation (ANOSIM, p <
222
0.05, Fig. ). Nevertheless, SIMPER analysis revealed consistent dominance by Acacia karroo
223
Hayne and Celtis africana Burm.f. (contributing more than 80% of the community) across all
224
gradients (Table 4). However, the number of species increased with gradient so that in
225
addition to these two species, Allophylus natalensis Sond. (Dune False Currant) characterized
226
slopes ranging from 0 to 15° and Brachylaena discolor DC. (Coast Silver-oak) those of 11 to
227
15°. Slopes of more than 15° were characterised by the addition of Grewia occidentalis L.
228
(Cross-berry), Chaetachme aristata Planch. (Giant Pock Ironwood) and Teclea gerrardii
229
I.Verd. (Zulu Cherry-orange), though all with less than a 5% contribution to tree communities
230
on these slopes (Table 4).
231
Elevation explained 32% of the variability in understory species abundances in seral stage 3
232
(ANOSIM, p < 0.05, Fig. ). However, this was the result of most cases representing mid-
233
elevations of 41–60 m.a.s.l, with very few cases for other elevation categories. Nevertheless,
234
these mid-elevations were dominated (61% contribution) by Rhoicissus revoilii Planch.
235
(Bushveld grape), followed by Scutia myrtina Burm.F (Cat-thorn) that contributed 28%, and
236
the invasive alien species, Chromolaena odorata L. (Triffid Weed), contributing 11% (Table
237
5). Elevations of 61–80 m.a.s.l. were dominated by S. myrtina alone (Table 5).
165 |
Appendices
238
Millipede assemblages
239
We recorded 28,987 millipedes (28,351 cylindrical, 513 keeled, and 123 pill millipedes) from
240
16 species in 65 quadrats. The number of millipede species in the transects of seral stage 2
241
covaried with dune position (Table 3), whereby valleys had the most species, though that of
242
slopes and crests did not differ from one another (Fig. 5). Models including age as a covariate
243
in addition to variables of dune morphology best explained the density of cylindrical
244
millipedes for pooled and separated seral stages. Pill millipede density was very low and also
245
driven by rehabilitating stand age in combination with dune morphological variables for
246
pooled as well as separate seral stages. The density of keeled millipedes for pooled seral
247
stages was best explained by a model including aspect, elevation, gradient, and position, but
248
not age (Table 3). These millipedes were most prolific in valleys (Fig. 5b), as well as east-
249
facing slopes (Fig. 5c) with gradients steeper than 10° (Fig. 5d). However, we found little
250
correlation between millipede communities and elevation (Fig. 5e), and when seral stages
251
were separated age was included in the best-fit model (Table 3). Based on our ANOSIM
252
analyses none of the variables of dune morphology significantly influenced species-specific
253
millipede abundances.
254
Discussion
255
In line with our hypotheses, dune morphology modulated microclimatic conditions in a
256
similar manner as reported for other studies (Tateno & Takeda 2003; Bennie et al. 2008). We
257
acknowledge though, that the conditions on each dune face are likely the product of
258
conditions ameliorated or exacerbated by surrounding dunes that have consequences for wind
259
channelling and shading, thus cumulatively influencing microclimatic conditions. Contrary to
260
our hypotheses, variability in soil nutrient concentrations was not explained by dune
261
morphology, but rather by regeneration age. The processing of sand as part of the mining
166 |
Appendices
262
operation probably reshuffled soil nutrients and minerals that accumulate through natural
263
processes. With only a few years of post-mining regeneration of biotic activity and
264
mechanical processes (e.g. leeching) it is not surprising that soil fertility (C:N ratios) and pH
265
levels are not yet conforming to expected spatially structured patterns induced by dune
266
topography. Given the weak associations between topographic and abiotic variables, it is also
267
not surprising that spatial variability in woody plant and millipede community structure could
268
not be explained by topographic variables.
269
Species richness and density, as well as species-specific abundances of canopy trees
270
and the understory varied with topography, as did millipede species richness, all in support of
271
our formulated hypotheses, though with the caveat of an overriding influence of regeneration
272
age. Keeled millipedes, a group of invertebrates associated with forests, also responded to
273
topography, although cylindrical and pill millipedes did not. This suggests that forest
274
specialists may be more sensitive to microhabitats induced by topography, but this requires
275
further investigation.
276
Increasing slope steepness resulted in more dense woody plant canopies in stands
277
older than 25 years, a finding similar to that of van Dyk (1996) for earlier stages of
278
regeneration in the study area. Laurance et al. (1999) also described a decrease in the number
279
of large trees with increased tree density on steep slopes. Although woody plant communities
280
of different gradients in stands of 11-25 years were generally dominated by similar sets of
281
forest tree species, species composition varied with the gradient of slopes. Incidentally, the
282
majority of these dominant species were identified by Grainger (2012) as species that could
283
colonize newly formed gaps in the woodland. This was likely due to their wide tolerance to
284
irradiance, temperatures, and moisture that change along dune slopes with elevation and
285
gradient (Ritter et al. 2005). Species abundances of canopy and understory communities
286
responded to different gradients in stands of 11-25 years, and elevation in stands of >25
167 |
Appendices
287
years, respectively. The number of canopy species, though not their abundances, was best
288
explained by aspect, elevation, gradient, and position in stands younger than 11 years,
289
suggesting that dune morphology may provide habitat conditions that support different
290
species in the early stages of succession when conditions are likely to be most harsh.
291
Millipede variables also responded to age and dune morphology. Explanatory models
292
for cylindrical and pill millipede density included age as a covariate. These relationships are
293
likely the result of age-related increases in woodland complexity (Kritzinger & van Aarde
294
1998), moisture-retention and nutrient accumulation associated with litter accumulation (van
295
Aarde et al. 1998) and the modulation of microclimate by topography as discussed above. As
296
in Greyling et al. (2001), two closely related cylindrical millipedes (Centrobolidae)
297
dominated these new-growth forests. This may have obscured patterns in species-specific
298
abundances related to topography. However, the number of millipede species covaried with
299
position on the dune face in stands of 11-25 years, whereby valleys supported more millipede
300
species than slopes and crests. When considering the microclimatic data, this likely relates to
301
the moderate temperature and light intensities but relatively humid conditions that existed in
302
the valleys in comparison with ambient conditions such as wind and high temperatures.
303
Keeled millipedes responded to topographic variables independent of age and this likely
304
relates to the provision of microhabitats for this relatively small, forest-associated species and
305
justifies further study.
306
Despite the idiosyncratic responses by woody plants and millipedes, position on the
307
dune, as well as aspect, elevation and gradient of the dune face contributed to age-related
308
changes in community structure. Our study also suggests that due to its modulation of
309
microclimatic conditions, dune topography provides habitats conducive to forest-associated
310
species that have narrow climatic habitat tolerances. This suggests that even though these
311
new-growth forests are in transition, topography may influence the structure and composition
168 |
Appendices
312
of biological communities of new-growth forests, especially when acting in concert with
313
other site-level factors. Such factors are likely to include those previously identified as
314
determinants of community structure and composition, such as landscape composition
315
(Grainger et al. 2011), and age (Wassenaar et al. 2005; Grainger & van Aarde 2012a).
316
The role of dune morphology seems more obvious in well-established ecosystems (Chen et
317
al. 1997; Oliviera-Filho et al. 1998; Tateno & Takeda 2003; Larkin et al. 2006), than the new-
318
growth forests that we studied, where age explained changes in assemblages better than
319
topography. Dune topography shaped as part of the rehabilitation procedure provides for the
320
topography that influences local conditions and therefore possibly for ecosystem patterns and
321
processes in a set manner according to prevailing climatic conditions. Topographically, these
322
dunes may differ from those shaped by natural forces (wind, water) which will probably
323
affect patterns and processes. However, these differences may be negligible and therefore not
324
be reflected in biological patterns, especially during the early stages of succession-driven
325
forest regeneration where most community variables vary with regeneration age.
326
For instance, age-related increases in habitat complexity provide an increasing variety
327
of conditions that accommodate more animal species and associated ecological processes
328
(Kritzinger & van Aarde 1998; Wassenaar et al. 2005). For example, increased plant
329
diversity, tree senescence and the associated development of a litter layer, increased soil
330
water retention, and nutrient accumulation would presumably benefit millipede communities
331
(e.g. Scheu & Schaefer 1998; Greyling et al. 2001; Berg & Hemerik 2004). In conclusion,
332
topography matters, more so for specialists than generalists. Response to topographic
333
variability is clearly species-specific and not necessarily reflected at the community level.
334
335
169 |
Appendices
336
Acknowledgements
337
The authors declare that they have no conflict of interest. The study forms part of a larger
338
program conducted by the Conservation Ecology Research Unit (CERU), University of
339
Pretoria and financed by the Department of Trade and Industry and Richards Bay Minerals.
340
The authors also benefited from National Research Foundation grants. We thank members of
341
CERU that assisted with fieldwork and provided helpful comment on earlier versions of this
342
document. The authors declare that the research conducted as part of this study complied with
343
the requirements of South African legislation.
344
170 |
Appendices
345
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456
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174 |
Appendices
463
Tables
464
Table 1 Key questions and hypotheses of this study
Key
General
Hypotheses
Examples from
question
assumptions
1. Does dune
Dune topography
Irradiation, temperature and humidity may
(Tateno &
topography
modulates
increase or decrease, depending exposure to
Takeda 2003;
influence
microclimatic
wind and sun that is facilitated or eased by dune
Bennie et al.
abiotic
conditions
aspect, elevation, and position
2008)
conditions?
Dune topography
Soil carbon-to-nitrogen ratio and soil pH will be
(Chen et al.
influences soil
greater in valleys and at low elevations
1997; Tateno &
the literature
nutrient
Takeda 2003)
availability
2. Does dune
Dune topography
 Woody plant richness will depend on aspect,
(van Dyk 1996;
topography
influences woody
elevation and position depending on their
Oliviera-Filho et
influence
plant community
exposure to wind
al. 1998; da
biotic
structure and
conditions?
distribution
 Woody plant canopy structure will depend on
gradient and position
 Species-specific woody plant abundances will
Silva et al.
2008; Laurance
et al. 2010)
differ based on dune morphology and position
Dune topography
 Millipede richness, as well as taxon-specific
(Weiss &
influences
density may be influenced by aspect,
Murphy 1990;
millipede
elevation, and position depending on their
Moir et al.
community
exposure to wind and sunlight
2009)
structure and
distribution
 Species-specific millipede abundances will
differ based on dune morphology and position
465
175 |
Appendices
466
Table 2 Definitions of response variables
Microclimate
Variable
Definition and units
Temperature
Ambient temperature measured in degrees Celsius (°C)
Relative humidity
The partial pressure of water vapor measured as a percentage (%) of
the saturated vapor pressure
Light intensity
Incident sunlight, measured as luminous power per area (illuminance)
Soil
in lumens (lux)
Soil pH
Soil acidity
Soil C:N
Carbon and nitrogen percentage content in soil samples presented as a
ratio of carbon-to-nitrogen
Canopy tree species
Total number of species forming the canopy (height class 2-5,
referred to as trees) per quadrat
Mean tree height (TH) class ( 2 [ >2–4 m], 3 [ >4–6 m], 4 [>6–8 m],
and 5[ >8 m]) of each quadrat
Woody plants
Response variables
TH
CBH
Per-quadrat mean circumference at breast height (CBH),
measurement carried out on all trees (height class 2-5) at ~1.4 m
above ground
Canopy tree density
Number of trees per100 m2, calculated for each quadrat
Understory species
Total number of species making up the understory (height class 1 [02m], referred to as understory plants) per quadrat
Understory density
Number of understory plants per100 m2 calculated for each quadrat
Millipede species
Total number of millipede species per quadrat
Cylindrical density
Number of Centrobolus spp., Doratagonus sp., Spinotarsus
Millipedes
anguiliferus, and Spirostreptidae spp. per 100 m2 calculated for each
quadrat
Keeled density
Number of Gnomeskelus tuberosus individuals per 100 m2 calculated
for each quadrat
Pill density
Number of Sphaerotheridae spp. individuals per 100 m2 calculated
for each quadrat
467
176 |
Appendices
468
Table 3 Dune morphological variables included in the most parsimonious models (based on Akaike
469
Information Criteria (AIC) scores) explaining variance in abiotic and biotic variables for each of
470
three seral stages and pooled stages, as well as the significance of the model (p < 0.05). Those
471
response variables that were explained by dune morphological variables in the absence of age are
472
highlighted in boldface text.
Explanatory variables
Dune morphology
ANCOVA results
1
df
AIC
P
Age
Position
Gradient
stage
Aspect
Response variables
Elevation
Seral
Insufficient cases
2
X
1
54.35
0.0005
X
12
13.73
< 0.0001
X
1
157.54
< 0.0001
4
284.46
0.119
Soil pH
3
X
X
X
Soil
Pooled
1
Insufficient cases
2
X
Soil C:N
3
X
1
186.59
0.745
Pooled
X
1
542.26
0.778
X
X
9
23.03
< 0.0001
X
X
5
23.77
< 0.001
X
12
46.27
< 0.001
X
5
236.79
0.024
X
10
158.23
< 0.0001
X
1
280.81
< 0.001
X
X
10
229.17
< 0.001
X
16
787.49
< 0.001
13
125.49
0.002
X
5
195.20
< 0.001
X
3
169.77
0.015
X
7
528.67
< 0.001
1
X
2
Mean canopy height
3
X
Pooled
Woody plants
1
X
X
X
X
X
X
2
Mean canopy tree CBH
3
X
Pooled
X
X
X
1
X
X
X
Number of species in
2
canopy
3
Pooled
X
X
X
X
X
177 |
Appendices
1
Mean canopy tree
2
density
3
X
X
X
X
1
-10.80
0.009
X
15
-120.87
< 0.001
2
-120.89
0.0004
X
Pooled
X
X
X
X
14
-155.73
< 0.001
1
X
X
X
X
14
97.78
0.009
X
5
105.12
< 0.001
X
5
57.26
0.0006
X
12
289.13
0.0008
X
1
74.66
0.679
X
15
-171.69
< 0.001
3
X
1
-113.38
0.0005
Pooled
X
1
-305.24
0.003
2
126.00
0.016
X
Number of species in
2
X
understory
3
X
Pooled
X
X
X
1
2
X
X
X
Mean understory density
1
Insufficient cases
2
X
Number of species
3
X
X
X
Pooled
1
X
14
83.35
< 0.001
X
X
3
271.23
< 0.001
X
6
92.18
< 0.0001
X
X
13
-18.05
< 0.001
X
X
20
183.63
<0.001
X
X
15
-114.18
< 0.0001
X
X
12
-96.33
0.0004
9
-235.50
< 0.001
X
14
-221.88
0.004
X
12
-110.06
0.0001
X
18
-400.40
< 0.001
Insufficient cases
Cylindrical millipede
2
density
3
X
X
Pooled
X
X
Millipedes
X
X
X
1
Insufficient cases
2
X
X
3
X
X
Pooled
X
X
X
Keeled millipede density
X
X
1
Insufficient cases
2
X
3
X
Pooled
X
X
X
Pill millipede density
X
X
X
X
473
178 |
Appendices
474
Table 4 Characteristic tree species (taller than 2 m) forming the canopies on slopes of different
475
gradients in seral stage two based on similarity percentage analysis (SIMPER).
Species
Family
Average
Average
Similarity Percentage
Cumulative
abundance similarity
SD
contribution percentage
0-5 degree slope
Average similarity: 54.91
Acacia karroo Hayne
Mimosaceae
3.26
39.44
6.11
71.83
71.83
Celtis africana Burm.f.
Celtidaceae
0.92
7.70
1.12
14.02
85.85
Allophylus natalensis
Sapindaceae
0.76
4.90
0.88
8.93
94.78
Acacia karroo
Mimosaceae
3.39
35.83
2.44
73.18
73.18
Allophylus natalensis
Sapindaceae
0.70
4.41
0.98
9.01
82.19
Celtis Africana Burm.f.
Celtidaceae
0.99
3.32
0.78
6.78
88.97
Cestrum laevigatum
Solanaceae
0.52
1.19
0.41
2.42
91.39
Acacia karroo Hayne
Mimosaceae
3.44
40.69
4.33
77.62
77.62
Celtis Africana Burm.f.
Celtidaceae
0.70
3.71
0.72
7.07
84.70
Brachylaena discolour
Asteraceae
0.35
1.67
0.45
3.19
87.89
Sapindaceae
0.47
1.54
0.37
2.94
90.82
Sond.
6-10 degree slope
Average similarity: 48.96
Sond.
Schltdl.
11-15 degree slope
Average similarity: 52.42
(DC.)
Allophylus natalensis
Sond.
16-20 degree slope
179 |
Appendices
Average similarity: 50.52
Acacia karroo Hayne
Mimosaceae
3.49
26.86
4.48
53.17
53.17
Celtis Africana Burm.f.
Celtidaceae
2.08
14.93
5.77
29.55
82.72
Grewia occidentalis L.
Tiliaceae
0.87
2.47
0.56
4.89
87.61
Chaetachme aristata
Ulmaceae
0.55
1.03
0.37
2.04
89.66
Rutaceae
0.30
0.87
0.39
1.72
91.38
Planch.
Teclea gerrardii
I.Verd.
>20 degree slope
Less than two samples in a group
476
477
180 |
Appendices
478
Table 5 Characteristic species occurring in the understory of each elevation category within seral
479
stage three based on similarity percentage analysis (SIMPER).
Species
Family
Average
Average
Similarity
Percentage Cumulative
abundance similarity
SD
contribution percentage
Vitaceae
1.49
27.25
1.10
61.23
61.23
Rhamnaceae
0.95
12.50
0.69
28.09
89.32
Asteraceae
0.57
4.75
0.46
10.68
100.00
Rhamnaceae
0.87
30.00
0.76
100.00
100.00
21-40 m.a.s.l.
Less than 2 samples in group
41-60 m.a.s.l.
Average similarity: 44.51
Rhoicissus revoilii
Planch.
Scutia myrtina
Burm.F.
Chromolaena odorata
L.
61-80 m.a.s.l.
Average similarity: 30.00
Scutia myrtina
Burm.F.
480
181 |
Appendices
Figures
Fig. 1 Digital elevation model of the study area also showing the delineation of rehabilitating stands according to age, and the sites where data
loggers were deployed (a). The locations of woody plant quadrats and millipede transect surveys were conducted are shown in relation to stand
age (b). Inset maps provide geographical context (c & d).
182 |
Appendices
95
90
85
80
75
70
65
60
0-5
6-10
11-15 degrees
90
85
80
75
70
65
41-60
61-80
81-100
101-120 m.a.s.l.
Temperature (C°)
34
32
N
E
SE
S
30
Temperature (C°)
36
30
28
26
85
80
75
70
60
Crest
Slope
Valley
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
Hour
Hour
Hour
32
90
65
60
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
38
Relative humidity (%)
100
95
Relative humidity (%)
100
95
Relative humidity (%)
100
0-5
6-10
11-15 degrees
28
26
24
24
22
22
20
20
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
Hour
Log10 light intensity (lux)
7
6
5
4
Hour
9
N
E
SE
S
SW
W
8
Log10 light intensity (lux)
8
3
2
1
7
Crest
Slope
Valley
6
5
4
3
2
1
0
0
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
Hour
Hour
Fig. 2 Mean ± one standard deviation of the mean of three microclimatic variables (relative humidity, temperature, and light intensity, from top to bottom,
respectively) that showed significant responses to variables of dune morphology according to the repeated measures ANOVA, as recorded between 01h00 and
24h00 on the 29th of January 2011.
183 |
Appendices
Woody plants
b
Canopy tree species
(number/quadrat)
10
8
6
4
2
0
N NE E SE S SW W NW
Aspect
Canopy tree species
(number/quadrat)
c
4
2
0
Crest
Slope
Position
Canopy tree density
(number/100 m2)
e
6
4
2
0
6-10 11-15 16-20
Gradient (degrees)
>20
10
8
6
4
2
0
41-60
61-80 81-100 101-120
Elevation (m.a.s.l.)
30
25
20
15
10
5
0
0-5
1
8
d
8
6
10
0-5
Canopy tree species
(number/quadrat)
Canopy tree species
(number/quadrat)
a
6-10
11-15
Gradient (degrees)
2
Fig. 3 Mean ± one standard deviation of the mean of woody plant response variables
3
presented as a function of those variables that best -explained their variability significantly
4
despite stand age (see Table 2).
184
Appendices
Fig. 4 Non-metric multi-dimensional scaling (NMDS) plots of woody plant abundances in the canopy
(top) and understory (bottom) where analysis of similarity revealed significant ( p < 0.05) community
separation attributable to dune morphological characteristics (elevation, gradient, position) according
to seral stages two (11-25) and three (>25 years), respectively.
5
185
Appendices
b
10
8
6
4
2
30
Keeled millipedes
(number/100 m2 )
Millipede species
(number/transect )
Millipedes
a 12
Crest
Slope
5
20
15
10
5
Slope
Valley
Position
Keeled millipedes
(number/100 m2 )
Keeled millipedes
(number/100 m2)
25
30
25
20
15
10
5
0
N
NE
E
SE
S
SW W NW
Aspect
Keeled millipedes
(number/100 m2)
10
Crest
d
30
0
6
15
Valley
Position
e
20
0
0
c
25
0-5
6-10
11-15 16-20
Gradient (degrees)
30
25
20
15
10
5
0
Elevation (m.a.s.l.)
7
Fig. 5 Mean ± one standard deviation of the mean of millipede response variables presented
8
as a function of those variables that best -explained their variability significantly despite
9
stand age (see Table 2).
186
>20
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