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Abundance and foraging niches of forest birds in part of the Ruamahanga Ecological Area, Tararua State Forest Park : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy at Massey University

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(1)Copyright is owned by the Author of the thesis. Permission is given for a copy to be downloaded by an individual for the purpose of research and private study only. The thesis may not be reproduced elsewhere without the permission of the Author..

(2) ABUNDANCE AND FORAGING NICHES OF FOREST BIRDS IN PART OF THE RUAMAHANGA ECOLOGICAL AREA , TARARUA STATE FOREST PARK. A thes is pre s en t ed in par t i al ful f i lment o f the requiremen ts for t h e degree of Doc t or of Phi loso phy at Massey Uni ve rs i ty. M i chae l M o f f a t June 1989.

(3) ii. ABSTRACT. To t es t the appl i ca b i l i t y i n New Zealand o f ecologi�al t heo r i es de r i ved from t he s t udy of no r t hern tempera te and t ro p i cal avi faunas , . t he commun i ty i n. par t. of. the. Forest Park vas s t ud i ed f r om. Ruamahanga Oc t o ber. b i rd. Eco l ogical Area , Tararua S t a t e 1 982. un t i l. F e b r uary. 1 98 5 .. A. mod i f i e d f i ve - m i nu t e b i rd coun t t o de t ermi ne the rela t i v e a bundances of each b i rd. spe c i es wi th a nea r / far ra t i o proved useful i n assessing t he. d is t r i bu t i on o f t he c ommon b i rd spec i es r a r e r spec i es . probably bred. but. wi t h i n. t he s t udy area .. signi f i can t ly. the. t he. spec i es d is t r i bu t i o n B i rd spe c i es. B i rd. near / fa r .. speci es. cor rela t e d wi th f o l i age h ei gh t d i vers i t y , P r i n c i pal compone n t analys i s was. used as a graph i cal t o o l t o descr i be the. s t ruc t ure and. for. Eleven fo res t b i rd spec i es were. bu t n o t wi th p lan t spec i es d i versi ty.. de t a i l .. inadequa t e. Twen t y - n i n e b i rd spec i es we re seen , t wen ty-one of wh i ch. seen w i t h su f f i c i en t f requency t o apply d i v e rs i t y vas. vas. i n t e r-rela t i onsh i�s. of. b i rd. wi th plant spec i es and plan t s t r u c t u r e i n gr ea t e r compos i t i on. vas. r e la t ed. t he p lant s pec i es composi t i o n .. to. bo t h. the. f o res t. The dis t r i bu t i ons o f t en. commo n b i rd spec i es were posi t i ve ly cor rela t ed wi t h h i gh canopy f o r es t , f i ve s p ec i es w i t h red beech-domina ted. f o r es t. pod o c a r p / b roadleaf-domina t ed f ores t .. Many. mos t a b undan t a t the end of. the. breed i ng. and of. f i ve. the. season. s p ec i es. w i th. b i rd spe c i es were in. F e b ruary-Ma rch .. This vas no t apparen t f rom cons i d e ra t i o n o f t he f i ve-m i n u t e b i r d coun ts alone because. of. seasonal. ,.. h:.ncr�c:: -�"-·· o --. f i ve - m i n u t e b i rd coun ts we r e useful i nd i ca t o rs of and o u t. o f the s t udy area .. The. in conspicuousness.. b i rd. moveme n t. into. Only vhi t eheads shoved cons i s t e n t seasonal. changes i n al t i t u d i na l d is t r i bu t i on , h ighe r i n summer t han By d e t e rm i n i ng. mod ified. in. win t e r .. t he r e la t i ve i mpor tance o f f o l i age he i gh t , t re e speci es.

(4) Hi. and substra�e bird species foraging site sho�ed. the. niches. there. site bet�een. is. habitats. a. Foraging. examined.. greatest difference bet�een bird species,. tree species and then foraging height. shoved that. �ere. Comparison with. followed by. other. studies. large degree of plasticity in foraging niche. -. in. Nev. Zealand. birds.. Foraging. congeners in Australia and Nev Zealand were similar. preferred different species of trees for foraging.. niches. of. Each bfrd species In �inter decreased. foraging niche overlaps �ere observed in conjunction �ith mixed species flocking.. Studies. of. New Zealand birds indicate that foraging niches. are sufficiently plastic for forest conservation management be considered. on a forest by forest basis.. strategies. The plasticity of foraging. niches may also account for the small proportion of introduced birds in the study area. forest bird. Competition is probably important in. community.. . Both. niche. comparable �ith studies on much richer birds �ere. largely. confined. �ere previously used by. structuring. the. breadths and niche overlaps �ere bird. assemblages.. Introduced. to fo�est margins and to resources �hich. extinct. native. birds,. suggesting. that. remaining native birds are successfully excluding introduced birds.. the.

(5) iv. Acknowledgemen t s. I would l i ke t o t hank my supe r v i sors E d M i n o t and B r i an th e i r cons t ruc t i ve. c r i t i c i sms. S p r i nge t t. and adv ice on the dra f t of th i s thes i s .. Eds ' s t a t i s t ical expe r t i s e was a gre a t. h elp. and. he. also. program wh i ch I u s e d f o r my p r i nc i pal componen t analyses . provided the. i ns p i r a t i on. cou n t t echn ique .. for. wrote. the. Dav i d Daws on. f o r the mod i f ica t i on o f his f i ve-minute b i rd. He d e r i ve d the fo rmula f o r calcula t i on o f the dens i t y. i n d i ces , and was p a r t i cu l a r ly helpful d u r i ng t he i ni t ial stage s o f. the. s tudy .. John Innes , John Lea t hwi ck and the i r col leagues o f the Fore s t. Res earch. Ins t i tu t e , Ro t o rua sugges t ed the use o f T�IN SPAN for analys i s of f o res t types and sys t em .. suppl i ed. a. f o rum. for. d i scuss i on. ou t s i d e. the un i v e rs i t y. The r e s e ar ch was funded by Fore s t Servi ce con t rac t 1 7 0 .. Dav i d Drummond and h i s eo-wo rke rs John A rch e r , B rendan Spr i ng and S t rachan collec t e d. the. d e t ai led. b o t an ical. E r ic. d a t a used i n thi s thes i s .. The i r compan i onsh i p i n the bush was a great boon .. The hel pful sugge s t i ons o f Malcolm Crawley and Harry the. intent. and. conclus i ons. of. t he. thes i s .. Re che r. c lar i f i e d. The i r. gramma t i cal. Zoology. De par tme n t ,. c o r re c t i ons we r e also apprec i a t e d .. F i naily , the s t a f f and s tu d en t s o f the B o t any and M as s ey Un ivers i ty , e nv i r onmen t .. have. provided. a. p leasan t and s t imul a t i ng work i ng.

(6) V. TABLE OF CONTENTS. P age. Abs t ract. ii. Acknovledgemen t s. iv. L i s t of append i ce s. vi. Li s t o f f i gu r e s Li s t o f t a b l e s CHAPTER 1 : I NTRODUCTI ON. vii ix 1. 1 . 1 Aims. 2. 1 . 2 Analy s i s. 5. 1 . 3 The s tudy area CHAPTER 2 : B I RD ABUNDANCE AND DISTRIBUTI ON. 13 35. 2 . 1 I n t ro du c t i o n. 35. 2 . 2 Me thods. 39. 2 . 3 Resu l t s. 41. 2 . 4 D i s cus s i o n. 72. CHAPTER 3 : FORAGING NICHES. 82. 3 . 1 I n t roduc t i on. 82. 3 . 2 Me thods. 85. 3 . 3 Resu l t s. 88. 3 . 4 D i s cus s i on. 107. CHAPTER 4 : SYNTH ES I S. 1 17. REFERENCES. 1 22. APPENDICES. 148.

(7) vi. LI ST OF APPENDICES 1 T r e e spec i es surround i ng each s t a t i on by t i e r. 148. 2 Tree spec i es po i n t he i gh t i n t ercep ts at each s t a t i o n. 152. 3 S t ru c tural parame t ers of the vege t a t i on a t each s t a t i on 1 53 4 BASIC program for cal cula t i o n o f d e ns i ty ind i ces. 154. 5 To tal numbe rs o f b i rds o bserved at each s ta t i on ( 80 c oun t s ) 6 Mean b i rd dens i ty at each s t a t i on ( b i rds per he c t a r e ). 155 156. 7 Pearson c o r rela t i on c oe f f i c i en ts o f b i rd spec i es d e ns i t i es w i th var i ab les o f the vege t a t ion. 157. 8 Mean mon thly f i ve-m i nu t e b i rd coun ts. 1 60. 9 P e rcen t o f each class o f behavi our obse rved. 161. 10 P e r cen t foraging use o f subs t ra t es. 162. 1 1 P e r c e n t forag i ng use o f t ree spec i es. 163. 1 2 Per cen t fo raging use o f h e i gh t c lasses. 1 64. 1 3 Seasonal forag i ng use o f subs t ra t es ( pe rcen t ). 1 65. 1 4 Seasonal fo rag i ng use o f t r e e spe c i es ( percen t ). 167. 15 S e asonal forag i ng use o f he i gh t classes ( percen t ). 169. 1 6 Numbe r o f b i rds coun t ed each mon th o n the contour t rans e c ts 1 7 Numbe r o f b i rds observed nea r / far a t each s t a t i on. 171 1 75.

(8) vii. LIST OF FIGURES. 1.1. Map o f the s tudy a rea. 15. 1.2. Fo res t types and mean canopy he i gh t of each s ta t i on. 20. 1.3. P r i n c i pal c omponen t analy s i s of tree s p e c i e s d i s t r i bu t i on ( t i e rs d a t a ). 1.4. 21. P r i n c i pal componen t analys i s of t r ee s pe c i es d i s t r i bu t i on ( po i n t he igh t i n t erce p t d a t a ). 1.5. 22. P r i n c i pa l componen t analys i s of tre e s p e c i e s d i s t r i bu t i on ( t i e rs d a t a , s t a t i ons 43-48 excluded ). 1.6. 26. P r i n c i pa l componen t analys i s of tree s pec i es d i s t r i bu t i on ( po i n t he ight i n t e r ce p t d a t a s t a ti ons 27. 43-48 excluded ) 1.7. P r i nc i pal compone n t analys i s of fo res t s t ruc ture ( s t a t i ons 1 -42 o n ly ). 28. 1 .8. To t al rainfall a t Pu t ara. 34. 1.9. Mon t h ly max i ma and m i n ima tempe ratures a t s i t e. 2.1. E f f e c t s of wind no i s e on mean f i ve-mi nu te b i rd coun ts. 44. 2.2. E f f e c t s of wa t e r n o i s e on mean f i v e -m i nu t e b i rd coun t s. 44. 2.3. E f f e c t s o f wind and wa ter noise on mean f i ve-minu t e. C. b i rd coun t s 2.4. 53. B i rd s p e c i es d i s t r i bu t ions rela t i onsh i ps t o plan t spe c i es d i s t r i bu t i ons. 2.6. 45. P r i n c i pa l component analys i s o f bi rd s pec i e s d i s t r i bu t i on. 2.5. 34. 54. B i rd s p e c i es d i s t r i bu t ions rela t i onsh i ps to fores t s t ru c ture. 55.

(9) viii. 2.7. Mean monthly five-minute bird counts. 2.8. Principal component analysis of mean monthly five-minute bird counts. 2.9. 56. 59. Annual cycles of mean five-minute bird counts, effective radii'of detection and density indices. 62. 3.1. Dendrograms of foraging substrate overlaps. 95. 3.2. Dendrograms of foraging height overlaps. 97. 3.3. Dendrograms of foraging tree species overlaps. 98. 3.4. Dendrograms of multidimensional foraging niches. 104.

(10) ix. LI ST OF TABLES 1.1. The p e r c e n t age o ccu r r ence of common woody spec i e s i n t he vege t a t i onal s t ra ta o f t he s tudy area. 17. 1.2. Two-way i n d i ca t o r s p e c i e s analy s i s of plan t t i e r s. 18. 1.3. Two-way i n d i ca t o r s p e c i e s analy s i s of po i n t he i gh t i n t e r cep t s. 19. 1.4. D i ve rs i ty i nd i ces a t each s t a t i on. 25. 1 .5. Mean t empe ra tures wi t h i n the s tudy area. 32. 1.6. Mean r a i n fall w i t h i n the s tudy area. 33. 2.1. Quan t i f i ca t i on o f env i ronmen t a l n o i s e. 43. 2.2. To t a l numbers o f b i rd s obse rved i n f i ve-minu t e b i r d coun t s f o r all s p e c i e s observed i n the s tudy area. 2.3. Mean f i ve-minu t e b i rd coun t s , b i rd dens i ty indi ces and e f fe c t i v e rad i i sampled by s t a t i o n group. 2.4. 46. 48. Numbers of b i rd s observed at ea ch group of s t at i o n s i n 1 9 8 3 and 1 984. 71. 3.1. Number o f n i che observa t ions o f each b i rd spec i e s. 89. 3.2. G values calculated f rom a compa r i son o f f i rs t fo r ag i ng obs erva t i o n with subs eque n t forag i ng observ a t ions. 94. 3.3. P re f e ren t i al us e of t ree s p e c i e s by fo raging bi rds. 101. 3.4. Seasonal f o ragi ng n i che bread t h s and evenness. 105. 3 .5. Mean s easonal f orag i ng over laps. 1 06. 3.6. Comp a r i son of New Zealand b i rd s pe c ies foraging s i t e u t i l i s a t ions be tween s tud i e s. 113.

(11) CHAPTER 1. INTRODUCTION. One of the maj o r aims o f ecology is to unders t and the. conv i n c i ng t es ts o f e co l ogi cal theo r i es , des c r i p t i ve also. b i rd s has p r ov i de d. use ful. much. e c o l ogi cal theo r i es. of. ( Re che r. ( Ala talo the. d a ta. 1985a ) .. et. al .. us ed In. Nev. da ta. 198 6 ) .. to. from. T h e s t udy o f. formu l a t e Zealand. f ield. and. the. Nev. a group o f i s olated is lands v i t h r e l a t i vely f ev na t ive land. b i rds , vher e a large par t of the avifauna has pas t 1000. tes t. s tudy o f. communi ty eco l ogy i n fo res t birds has been neglec t ed ( G i l l 1 980 ) . Zealand is. of. Al though expe r i men ta l resu lts p r ov i de the mos t. communi ty compos i t i on .. observa t i ons are. d e t e rmi nan t s. years. ( Ho ldaway. 1989).. be come. ext i n c t. t he. Wi th the a r r ival o f E u r o p eans the. ra t e of ex t i nct i ons inc r eased rap i d ly in conj unc t i on wi t h t h e o f i n d i genous. in. clea r ing. f o res t s for farm i ng and t he i n t rod u c t i o n of many mammals. and exo t i c b i rd s pec i es ( Ho ldaway 1 9 8 9 ) .. T h i s s tudy vas s e t up t o exam ine the b i rd communi ty fores t i n. the. l igh t. of. of. this h i s t o r i ca l pers pec t i ve .. ecologi cal theor i es , d e r ived f rom t h e s tudy o f n o r thern. an. i nd igenous. The u t i l i ty o f t empe r a t e. and. t ro p i cal av i faunas , could be i nves t i g a t e d on vha t may be des cr i bed as a large na tural exper i me n t ..

(12) 2. 1 . 1 Aims. Many ecolog i s t s t h i nk t hat i mportan t fac t o r. compet i t i on. is ,. or. has. Sup po r t for the impo r t ance o f compe t i t i on i n. c omes. f rom. exp e r i men tal. ( M i no t. 198 1 ,. observa t i onal ( Al a t al o 1 9 8 1 b, 1 982 , B e l l al .. 1 9 86 ) .. of. Ala talo 1 98 5 ). i n t e r s pe c i f i c. 1 9 8 2 , Br awn e t al .. b i rd. and. commun i t i es 1 98 5 ) '. al .. et. 1 983 ) .. compe t i t i o n. Ther e. compa ra t i ve. in. is. some. li t tle. areas. Ro tenber ry 1 98 1 , Moun t a i n s p r ing and S co t t 1 98 5 ) or e t al .. mos t. work. O t hers con s i d e r the evi dence for compe t i t i on. to be weak ( S i mbe r l o f f 1 9 83, S t rong e v i dence. t he. i n commun i ty organ i za t i on ( Roughgarden 1 9 83 , Schoener. 1983 ) .. ( Alatalo e t. been ,. s easons. or. ( � i ens. no and. ( Rosenberg. 1 9 87 ) .. In obse rva t i onal s tud i e s ev i dence for compe t i t i on. has. been. s ugges t ed. by : 1 . Search i ng f o r n i che s h i f ts concomi t a n t wi th changes i n gui ld c ompos i t i o n ( Al e r s t am e t al . 1 9 7 4 , Hogs t ad 1 9 78 , Alatalo 1 9 8 1b , Alatalo et al . 1 98 5 , Rabo l 1 98 7 ) . 2 . Compleme n t a r i ty o f fo r ag i ng niche axes ( Cody 1 9 7 4a , Schoener 1 9 7 4 , P i anka 1 9 7 8 ) . 3 . Seasonal change s i n n i che use ( Ul f s t rand 1 9 7 7 , Ala talo 1 9 8 0 , 1 9 8 2 �agner 1 98 1 , B e l l 1 9 85 , Lau ren t 1 986 ) . 4 . Ni che expans i on on i s l ands as compared to the mai nland (MacAr thur and � i l s on 1 9 6 7 , D i amond 1 9 70, Ala talo e t al . 1985 ) .. A maj or a i m o f the p�es e n t s tudy vas t o compe t i t i on i n. s t ru c tu r i ng. a. New. d e t ermine. t he. i mpo r t ance. of. Zealand fores t b i rd commun i ty , and.

(13) 3. each o f t he above po i n ts vere cons i de r ed .. Many b i rds a r e t e r r i t o r i al. d u r i ng the b ree d i ng seas o n .. are unde r t aken. bi rds ,. fores t. of. The maj o r i ty o f commun i ty s t ud i es , es p e c i ally t hose. vhen breed i ng , and the males are usually con s p i cuous , a i d i ng popula t i on quan t i f i c a t i on and ni che s t udy .. Hovever , i mp o r t an t fac t o rs d e t e rm i n i ng ou t s i d e. the occurre n c e and abundance of bi rds i n t empe rate reg i on s a c t the. breed i ng. s eason. ( Lack. 1 9 5 4 , 1 9 66 ,. F r e t vell. generally breed vhen f ood is mos t abundan t , this t ime. of. year. As. 1972 ) .. compe t i t i on. for. b i rds. f ood. may be reduced o r absen t ( Ros enberg e t a l .. Therefore i nves t i ga t i o ns of commun i t y s t ruc t ure should cover t h e. at. 1982 ) . vho l e. year .. I t has been sugges t ed. tha t. vege t a t i o n. s t ruc ture. coup l ed. vi th. food. resource ava i lab i l i ty and abundance, provide pa r t i cular comb i na t i ons o f forag i ng oppo r tun i t i es. for. bi rds. tha t. in. t urn de t er m i n e vh i ch b i rd. spec i e s can fo rage success fully and s u rv i ve there 1 986b ) .. The. fo raging. opportun i t i es. (Holmes. avai lable. to. fo res t. influenced b y t re e s p e c i es ( Holmes a nd Robinson 1 98 1 , foliage h e i g h t. ( Pearson. 1 9 7 1,. H olmes e t al .. A i rola. Carras cal e t a l . 1982 , Holmes. and. and. 1985 ,. Rob i nson. requi re mo r e i n f o rma t i o n .. 1988 ) . in. 1 9 88 ) ,. 1 9 7 9 , Beedy 1 98 1 , F r i th. Holmes. 1 9 8 7 ) , and forag i ng t echn i qu e. impor t ance of these f a c t o rs. utilisat ion .. Bar re t t. Re che r. b i rd s a re. V i rkkala. 1 984 ) , the s i t e or subs t r a t e ( Landres and MacMahon 1980 , Ala talo 1 9 8 2 ,. and. and. Moreno Recher. ( Rob inson. and. 1 98 1 , 1986a , Ho lmes. Gene ral i z a t i ons abo u t t he rela t i ve. s t ruc t u r ing. fores t. b i rd. commun i t i es. I stud i ed he i gh t , t ree spec i es and subs t r a t e. The t re e species prefe r en c e o f b i rd spec i e s v e re measu red. t o i den t i fy v h i c h tree spe c i es ve re i mpo r t an t for each b i rd s p e c i e s ..

(14) 4. B i ogeograph i ca l t he o ry pred i c t s larger n i ch e s. t han. congeners It. 1 9 67 , D i amond 1 9 7 0 ) .. that on. s pe c i es. the. on. i s lands. w i ll. have. mainland ( MacAr t hu r and � i lson. is assumed that where there are fewer. spec i es. t h e re a r e few e r compe t i t o rs , and compe t i t i ve release resul t s i n broader n i ches .. This. t h e o ry. was t e s t ed by comparing ni ches o f spe c i es common. t o b o t h Aus t ra l i a ( ma inland ) and New Zealand. ( i s land ) .. i n New. several. Zealan d. the. recen t. ex t i n c t i on. of. A dd i t i onally , b i rd s p e c i e s and. i n t roduc t i on o f many o t hers has mean t tha t. the. b i rd s w i t h i n. could be q u i te l arge.. the. f o res t. b i rd. c ommun i ty. p ropo r t i on. of. r es u l t o f t h e s e changes the b i rd commun i ty may be in a s ta t e For these. reasons. t he. in tegrat i on. of. e xo t i c. of. As a flux .. t he int roduced b i r d s wi t h the. na t i ve b i rd s was examine d .. MacA r t hu r and MacAr thur ( 1 9 6 1 ) used dive rs i ty measures t o s h ow t ha t the s t ruc tu ral complex i ty o f the envi ronment was rela ted t o the b i rd s p e c i e s. in. t h a t env i ronmen t .. numbe r. of. Nume rous res earchers have ve r i f i ed. t h i s rela t i on s h i p ( MacAr thur 1 9 6 4 , Re che r 1 969 , Karr and Ro t h 1 9 7 1, Rov 1 9 7 5 , Beedy 1 9 8 1 ) , b e tween b i rd. but. s p ec i es. o thers. have. d iv e rs i t y. and. 1 9 7 4 , � i l ls on 1 9 7 4 , Caro t h e rs e t . 1 9 7 6 , E rd e l en. 1 98 4 ,. Ralph. al .. 1 985 ) .. d e t a i l e d mul t i va r i a t e s t a t i s t i cs have. not. found. s t rong. cor r ela t i ons. f o l i age he i gh t d i versi ty ( Tomo f f 1 9 7 4 , Pearson 1 9 7 5 , 1 9 7 7 ,. Ro th. S t ud i es of b i rd commun i t i es us ing t ended. to. concen t ra t e. on. the. s t ru c t ural f e a t u res o f t he i r h ab i t a t s ( James 19 7 1 , And e r s on and Shugar t 1 9 7 4 , C o l l ins 1 98 6 ) . of. bird. et. al.. 1982 ,. J ames. and �amer 1982 , Mehlop and Lynch. In t h e s e s t ud i es the mos t s i gn i f i can t s pe c i es. d i s t r i b ut i ons. were. s t ru c t u ral. associa ted. w i th. d e t e rminan t s c anopy. Var i ab les whi ch meas�red t ree s pe c i es compos i t i ons were confined few. s ummary. measures. such. as. pe rcen t. coni fers. and. t ree. size . to. a. s pec i es.

(15) 5. r i chness;. but whe r e these. var i ab l es. were. i ncluded. they. we re. also. i m po r tan t in d is tingu i s h i ng b i rd spe c i es group ings .. Re cher ( 1 98 5 b ) s ta te d tha t. the. produce a. wh i ch w i l l expla i n pa t terns and pred i c t the. general. theory. ul timate. goal. cons equences of changes to the envi ronmen t . the phys i cal. s truc tur e. and. of. e c o logi s ts. It i s appare n t. is. tha t. in. 1974a ) .. showed tha t plant spe c ies compos i t i on and pla nt spe c i es. s truc ture tend to vary concu r ren tly fac tor. bo th. the s pec i es compos i ti on of the vegeta t i on. are impor tan t parame te rs i n b i rd commun i ty r e l a t i o nsh i ps ( Cody G i lmore ( 1 985 ). to. d e term i n i ng. b i rd. but. s pe c i es. s truc ture. is. d i s t r i b u t i on ,. the I. i mpor tan t. tes ted. the. app l i cab i l i ty o f th i s hypo thes i s w i th i n my s tudy a rea .. M i xed s pec i es flock i ng , par t i c u la rly s e as ons, is. -. 1 97 7 ) s ugges ts tha t. f l o cks mus t. be. p r esen ted a. model. i s food. w i n te r. a common phenomenon ( Morse 1 9 7 0 ) .. ( Pyke e t al .. f l o cking .. in. maxi m is i ng for. the. the i r. the. the. n on- bree d i ng. O p t imal f o r ag i ng theory. i nd i v i d uals. Darw i n i an. p r esumed. or. in. f i tness .. advan tages. of. mi xed Mors e m ixed. ( 1978 ) spe c i es. I f ove r lap i n fo rag ing i nc reas es then mixed s pe c i es flo ck i ng med i a ted .. o ther s p e c i es Convers e ly , i f. and. Fac tors i n c r eas ed. o v e r l ap. predator med i a ted .. s uch. as copy i ng the forag i ng ac t ivi ty o f. flus h i ng. decreas es. of. then. T he relevance o f these. p r ey. will. be. Analys is. i mpor tan t .. m i xed s pe c i es f lock i ng may be mode ls. to. f o r a g i ng. complemen tar i ty in the s tudy area d u r i ng w i n te r was ass es s e d .. 1.2. spe c i es. n iche.

(16) 6. A. variety of analytical techniques were used in this thesis.. description of. the. techniques. selecting each technique,. evenness,. Oiyersity,. used,. together. where. s. Shannon-Veaver. diversity. The Shannon-Veaver equation is:. 1949).. _!. the. number. of. categories. individuals in the ith �ategory. the. indices. of Simpson. ( 1966). Pielou. breadth.. and. p. the. i. This index varies. to. noted. containing a fixed number of specie� (s),. measure that. proportion. less. or Hill. ( 1949). The Shannon-Veaver equation was used niche. the. �=1. =. is. size than. the reasons for. niche breadth and niche overlap. (Shannon and Veaver H. short. follows.. Diversity indices were calculated using formula. with. A. ( 1973) both. among. with. sample. (Beedy. 198 1).. diversity. all. diversity is maximum when all (Hmax). is equal to the natural logarithm of the total number of species . her. to. define. and. communities. the species are equally abundant and that the maximum diversity. observation led. of. evenness. (J). as. the. diversity index of the community to the maximum possible. ratio. This of the. diversity. of. that community:. J. =. H/Hmax. H/Ln(s). The index of overlap used to measure coincidence of. =. (Schoener. 1 970). 1. -. o. s 2. I. where. j.. p ij. pi j. is. -. ph j. distribution. was:. 1. the proportion of species i. in resource.

(17) 7. in. s t at e j and phj i s the propor t i on o f spe c i e s h s tate .. ( m i n imum ). 0. is. Over lap. the. same. res ource. two spec i es , i and h , share no. when. resou rce s t a t es , and 1 ( max imum ) when the p r opo r t i onal d i s t r i bu t i ons of two spec i es among the resource s t a tes are i d en t i ca l .. The mos t common c r i t i c i sm o f these s i mple measures in n i che analys es i s that they d o not t ake i n t o ac coun t resource ava i lab i l i ty. ( Colwell. Futuyma 1 9 7 1 ,. Hur l be r t 1 9 7 8 , P e t r a i t i s 1 9 7 9 , F e ins inger et al .. These au t ho r s. sugges t. ava i l ab i l i t y .. They. t he. use. of. measures. we igh t ed. by. that :. the. 1981 ) . resource. assume ei ther that t o t al resource avai lab i l i ty can. be meas u r ed or that resource availa b i l i ty is p ropo r t i onal use by. en t i re. commun i ty .. Colwell. to. resource. and Fu tuyma ( 1 9 7 1 ) p o i n t ou t. " Unl e s s res ource s ta t es have e cologi cal ly equivalent d egrees among. d i s t i n c t ne s s. and. them ,. compa r i s ons. par t i cularly wi t h i n communi t ies, a r e pe r i lous . " problems a s s o c i a t e d. wi th. obtaining. commun i t i e s. be tween. ad equa t e. They also d i s cuss measures. of and the. of i n d i v i d ual. spec i es n i ches .. In my s t udy the feed i ng n i ches o f t h e commun i ty were. assumed. to. be. subs t ra t es f o r ac t i ve forag i ng . each s ub s t ra t e. avai lable. i n d i v i dual. r e la t ed. to. the i r. M e a s ureme n t o f. was n o t p o s s i b l e .. spe c i e s use. the. wi t h i n of. t o t al. the. d i fferent amoun t. of. The rela t i o n s h ip o f t o t al. b i rd commun i ty use t o the actual subs t ra t es avai lable i s unknown and t o assume that. they. are. available. commun i ty u s e i s d angerous .. in. proportion. the. total. bird. Because of these fact ors I used t h e s i mp l e. unwe i gh t ed measu res o f n i che bread th and overlap .. Mul t i va r i a t e analyses. to.

(18) 8. All compound. ind i ce s , that. d i s advan t age. such. they. as. d i ve r s i ty. comb i ne. the. and. e f fects. evenness ,. have. Mul t i va r i a t e. analyses al low u s t o d es c r i be the rel a t i onshi ps be tween a l arge. and. t ha t. v a ria bles. of. i nd i v i dually may b e o f b i o logi cal i n t e res t ( Pielou 1 9 6 9 ) .. of v a r i ables .. the. number. Compl ex i n t e rac t i ons be tween b i rd s pe c i es , p l an t spe c i es. vege t a t i onal. s t ruc ture. can. be. d i s t i ngui shed .. p r ed i c t i ons can be o f great value. in. r e s ource. b e f o r e the. tests ,. app l i ca t i on. of. such. The. c o n s e quen t Howev er ,. manageme n t .. i t i s essen t i al t o h ave s ome. unders tand i ng o f t he i r t he o ry , me thodo logy , and l i mi t a t i ons .. In p r i n c i pal componen t analy s i s. (PCA ). d e r i ved by. e igen. th e c o r re l a t ion ma t r i x o f t he o r i g i nal. v a r i able s .. Each componen t represen t s. analy s i s. variance present. in. the. of. o r i ginal. a c coun t for d e c r eas i ng propo r t i ons -. un c o r rel a t ed w i t h. al .. 1977 ,. Such. port i on. data of. t he. of. me thod. in. var iance. ecological. a. gen e r a l i zed. wh i l e. r ema i n i ng. s tud i es. PCA. ( James. componen t s. d a t a,. by. al .. "succes s " i f a large propo r t i on o f the. ( P i e l ou 1 9 84 ) .. the. f i rs t. two. or. The o r i g i na l v a r i a b l e s can. be proj e c t ed on t o t h i s two o r t hree d i me n s i onal f rame , t he. a re. Suc ces s i v e c o mponen ts. set .. vari a t i on in the o r i ginal data se t is explained by. pa t t ern o f. the. 1 98 2 , James and Warner 1 98 2 , Ande r s o n e t. an o rd i na t i on i s. three p r i n c i pal. compon e n t s. Vh i t mo r e 197 5 , Ro t en b e r ry and Viens 1 98 0 , M au r e r e t. 1 98 1 , Co l l i ns e t al .. 1983 ) .. a. princ i pa l. p r ev i ous componen t s ( Rummel 1 9 7 0 , P i e lou 1 9 7 7 ) .. i s o f ten used as an o rd i na t i on 1 9 7 1 , Smi th. t he. to. reveal. the. plo t t i ng the e igen values of each var i able .. Gauch ( 1 9 8 2 ) has shown that t h i s type. of. plo t. also. reduces. " no i se ". as s o c i a t ed wi th s t ochas t i c va r i a t i ons i n the da ta s e t .. Johnson ( 198 1 ) d es c r i bed t hree speci f i c problems asso c i a t ed. w i th. PCA ..

(19) 9. Fi rs t , the. analys i s may s eem be t t er than i t a c tually i s b ecause o f the. presence of a large num be r o f redundan t var i ab l es. always easy. to. relate. the. how the. an imal. p e r c e i ves. produced s i m i lar resul t s emphas i s i ng the. need. i ts f rom. for. is. necessar i ly Karr. envi ronmen t . PCA. care ful. of. bo th. related. was. s i m i lar. real. i n t e r p re t a t i on. to. tha t. for. to. and Mar t i n ( 1 9 8 1 ) and. random. data ,. of. resul t s .. They. concluded t ha t when the amoun t of var i a t ion explained by the f i rs t p r inc i pal componen t s. not. derived fac t o rs back to t h e o r i gi nal d a t a. T h i r d , t h e p r i n c i pal componen ts a r e n o t. set .. S e co nd, i t. a. two. random numbe r s e t. b i ologi cal i n t er p r e t a t i ons were ques t i onab l e .. Mul t i va r i a t e techn i ques as sume that the da ta are normal ly. d i s t r i bu t ed .. The e f f e c t. o f non-normal i ty and non-homogeneous var i ance a re decreased. wi th l a rge. s amples. ( G reen. nece s s a ry ( Dunn 1 9 8 1 ) . but should. be. 1979 ) ,. bu t. t rans f o rma t i ons. are. o f t en. These t rans f o rma t i ons may have l i t t le advan t age. car r i ed. out i f the s t a t i s t i ca l assump t i on s are cl early. violated ( J ohnson 1 9 8 1 ) .. Non-li near response by s pec i es. to. var i ab les. i s a par t i cular p r o b l em i n PCA because l i near combina t i o ns of var i ab les are. produced .. A. non- l i near. data. swarm. when. p r oj e c t ed. dimens i ons may g i v e a m i s l ead i ng p i c ture o f the da ta . e f f e c t o c curs. when. a. series. of. samples. envi r onmen t al grad i en t , such as a moun t a i n respond independen t ly pa tern produced by. 1984 ) .. in. PCA. a. Gauss i an. exhibits an arch. has. ( no rmal or. The mos t. been. s lope ,. into. t aken. wher e. curves ). horseshoe. the. common along an s pec i es. fashion . shape. two. The. (Pielou. H i ll ( 1 9 7 9 a ) des c r i bed t h i s arch as a ma thema t i ca l a r t i fa c t and. devis ed a. t echn i que. overcome i t . of succe s s i ve. called de t rended co r re s p ondence analy s i s ( DCA ) t o. O th e r ·researchers regard the a r ch a s a n i nh e r e n t prope r ty r e p laceme n t. d ata. wh i ch. mus t. be. cons i de red. in. any.

(20) 10. d i s cuss i on o r. analys i s. of. such. d a t a ( Noy-Me i r and Aus t i n 1 9 70 , Swan. 1 9 7 0 , P i e lou 1 9 7 7 , 1 984 , Va r t enberg e t a l . ( 1 9 8 7 ) r ecommend. repor t ing. the. 1 98 7 ) .. V a r t enberg. et. al .. arch unsealed i n two d imens i ons , even. t hough i t is a one d i mensional form.. Des p i t e flag ran t v i o l a t i ons t e chni ques have. been. of. s t a t i s t i ca l. mul t i var i a t e. use ful i n d ef i n i ng communi t y s t ruc tur e .. ( 1 9 8 1 ) concluded t ha t there we r e two E i ther. apparen t i ncons i s t ency .. p o s s i ble. and. explana t i ons. Johnson for. this. b i o lo g i s t s were rep o r t i ng the r e su l t s. o f soph i s t i ca t ed analyses only when they b i o log i cal i n tu i t i on. as sump t i ons. o t her. we re. resul t s ,. in. or. a ccord. the. wi t h. tests. thei r. may b e more. s t a t i s t i cally r o bus t than is r ecognized .. In this thes i s two d i f f e ren t types o f PCA have been used , b o th o f wh i ch presen t the i n t e r- r e lat i onsh i ps be tween the i nd i v i duals of data. ma t r i ces. in. a. s ingle. f i gure .. In. p roduced i s based on the f i rs t two p r i nc i pa l analys i s of. the d a t a s e t .. are. compone n t s. a r e pos i t i vely. d i v i ded. f rom. The. p r i n c i pal. by the s quare roo t of the l a t e n t r oo t s , s quare. root. of. the. On such a graph po i n t s o r l i nes whi ch are c lose t oge t h e r correla t ed ,. those. at. oppos i t e. s i des. correl a t e d and those at r i ght angles a re n o t correla t ed . a variable l i ne i nd i ca t e s the var i able t h a t. d e r i ved. The varia b l e s a r e plo t ted on the s ame g raph. whereas t h e l a t e n t v e c t o rs are mul t i pl i e d by the latent r o o t s .. var i ables. the f i rs t t he s t ruc ture. as the i n d i v i duals by scal i ng b o t h by t h e l a tent roo t s . component s co r e s. and. propo r t i o n. of. the. a re nega t i ve ly The l en g t h o f. var i a t i on. of. is descr i be d by the f i rs t two p r i nc i pa l compone n t s .. longer t h e l i ne the grea t e r the propo r t i on o f explained ( Has s a rd unpubl . ) .. the. var i a t i on. tha t. that The is.

(21) 11. The s econd t y p e o f PCA i s a pa r t i t i on i ng me thod appl i ed o r d i n a t i on. ave rag i n g. ( RA ) .. RA. I n t h i s t echnique the. analys is .. ord inat ed s i mul t aneous ly . to maxi m i z e. the. is. also. var i ab l es. a nd. correla t i on. analys i s. the. co r re s pond ence i n d i v i duals. be tween i nd i v i duals and var i a b l e s .. ( T�INSPAN ) .. ordina t i ons i s used t o. as. rec i pr o c a l. are. Scores are as s igned t o each i n such a way as. ( 1 97 9 b ) d eveloped a p a r t i t i on i ng p r o cedu r e spec ies. known. to. spl i t. A the. cal led. s er i es data. of. into. two. one. way. Hill. i n d i ca t o r. d i men s i onal. several. class e s .. RA. The. resul tan t c las s i f i ca t i on i s consid e red t o be more na tural t han s tand a rd PCA becaus e. " i n d i f f e ren t " spec i e s do no t a f f e c t the resul t s .. the cos t o f t h e s e r e f i n emen ts i s t hat t h e number o f fo rms. i n c reases. exponen t i ally. increas i ngly subj e c t i ve analys is a t t emp t s. to. and. ( P i elou. choo s i ng. 1984 ) .. o rd i na t e. Howeve r ,. pos s i b le. be tween. mod i f i ed. t h em. Add i t i onally ,. becomes the. b e caus e. t h e d a t a i n t o a one d imens i onal space ,. problems as s o c i a t ed wi t h e r roneous c a l cu la t i ons o f the a r ch e f f e c t arise .. A l t h ough. fores t- type maps, the des i re obscure. the. is. T�INSPAN. " real ". to. a. s i tua t i on .. d e t ermi ned. can. Changes l eve ls. the. analys t ' s. whi ch. that. preconce i v e d is. the. s e l e c t i on spec i e s. final. n o t i ons .. obj ect ive a l t e rna t i ve .. T�INSPAN. vege t a t i onal groups. a propo r t i onal bas i s .. on. p r oduc i ng. clas s i f i ca t i on the. in. at. for. and. marke d ly al t e r the f inal ou t pu t .. subj e c t i v e d e c i s i ons can b e chosen so agrees w i t h. t e chn ique. p roduce a d i v i s i ve. pseudos peci es cu t levels and the group ings are. use ful. commonly. each plan t s pe c i es a t each s t a t i on i s us ed. may. may of s i te These. c l a s s i f ica t i on. PCA o f fe r s a mo re used. to. c las s i fy. The rela t i v e d e nsi ty o f. r a t her. t han. the. abs o l u t e. dens i ty .. The use o f PCA and T�INSPAN i n conj un c t i on s hould decrease. the. chance.

(22) 12. o f m i s i n t erp r e t i ng. commun i ty. s t r u c t ure .. To sa t i s fy the a s s um p t i on o f. n o rmal i ty d a t a were t rans f o rmed be fore PCA b y add i ng o n e t o p o i n t and then taking t h e n a t u ral loga r i thm . the. raw. dat a .. The. p s eudos pec i es. cu t. add i t i onal. cut. level. at. 50% .. Th i s. were. percen tage allowed. calculated data. to. to. w i th. one. to. be. s t a t i on s. d i f f e r en t i a t ed by plan t s p e c i e s dens i ty i n addi t i on compos i t i on .. data. TVINSPAN was p e r f o rmed on. levels. c o r res pond wi th the d e f au l t cu t levels f o r. e a ch. plant. s pec i e s. FHD and PSD were als o calcula t ed a t each s t a t i on .. Clus t e r analys i s. S t ud i es o f nume rous .. the. fo rag i ng. e c o l ogy. of. f o res t. b i rd. commun i t i es. are. Several au thors have d i v i ded the i nd i v i dual s p e c i es of the i r. b i rd commun i t i es i n t o gu i lds ( V illson 1 9 7 4 , Her re ra 1 9 7 8 , H o lmes e t al . 1 9 7 9 , Eckhard t. 1 97 9 ,. o f t h e commun i ty i n which i nd i v iduals use in. a. s i m i lar. manne r. A gui ld i s a subs e t. Land res and MacMahon 1980 ) .. ( Ro o t. 1967 ) .. a. s i mi lar class o f. G roup i ng. s pe c i es. f a c i l i t a t es r e cogn i t i on o f commun i ty o rgan i za t i on mos t probable. compe t i t o rs. i d en t i f i ed by. several. ( Landres. techniques .. and. and. MacMahon. Some. into. guilds. i den t i f i es. 1 980 ) .. au thors. r esources. the. Gu i ld s are. a s s i gn. gu i lds. subj ec t i v e ly o n the bas i s o f known subs t ra t e preferences ( V i l l s on 1 9 7 4 , Herrera 1 9 7 8 ,. E ckha rd t. 1 9 7 9 );. o t he r s. resource s t a t es used by. each. ( Holmes e t. Land re s. 1 98 6 b ) .. al .. 1 9 7 9,. spe c i e s and. use to. clus t e r. fo rmal i ze. analys i s o f the gu i ld. s t ru c t ure. MacMahon 1980; Holmes and Recher. The lat t e r approach has been used i n t h i s. thes i s. be cause. it. p r o v i d e s an o bj ec t ive es t i mat i on of poss i ble compe t i t i on .. May ( 1 9 7 5 ) po i n t ed o u t t he d anger o f e s t i ma t i ng t h e overlap i n n i che by.

(23) 13. t he use o f aggrega t ed measuremen t s o f i nd i v i dual resour ces .. C lus t e r i ng. t echni ques based o n euc l i d ean d i s t ances cal cula t ed f rom aggrega t e d d a t a s e t s overes t i ma t e t h e s i m i l ar i ty coef f i c i en t s . s i ngle axi s. In my. both. the. a n d t h e mul t i-di mens ional n i c h e b read ths and over laps w e r e. calcula ted , aggrega t e d measures were no t used . w i t h the. s tudy. use. of. euc l i d e an. d i s tances. on. A maj or problem. occurs. s parse data ma t r i ces .. The. eucl idean d i s tance b e tween two s parse quad ra t s , or rare s p e c i e s , may be qui t e s mall d es p i t e the f a c t that none of ove r came t h i s. p rob l em. by. calcula t i ng. s ta t ions ( Schoe ne r 1 9 7 0 ) , and. used. the. variables. over lap .. I. t h e over lap be tween s pe c i e s o r. the. p ro p o r t ional. overlaps. as. a. s imi lari ty ma t r i x for clus t e r analys i s .. Var i ous types of c lus t e r 1 984 ) .. The. groups. analys is. d e f i ned. clus t e r i ng algo r i t hm used .. in. are. ava i l able. clus t e r. ( Review. analy s i s. In th is t h e s i s the. by. P i e lou. are d e f i ned by t h e. unweigh t ed. pa i r. g roup. mean clus t e r i ng t ec hn i que was used .. 1 . 3 The s tudy area. The s tudy area i s loca t ed on the no r t h eas t ern s lopes Range ( F ig .. 1.1).. of. the. Tararua. The area was chos en b ecause i t con t a ins a v ar i e ty. o f fore s t types and fo res t s s t ruc tures whi c h hav e no t been mod i f i ed loggi ng .. The. i nves t i gated . 1 , 500m and. are. r e s ponse. of. The p eaks of t he covered. the. avi f auna. Tararua. r ange. wi th a l p i ne s c rub .. l i es wi thin Tararua -S t a t e Fore s t Park .. to. th is vary. d i vers i ty f rom. 1 , 200m. by was to. The maj ori ty of the r ange. The s lopes of the moun tains a re. covered wi th m i xed podocarp-broadleaf f o re s t w i t h pa t ches o f beech ..

(24) 14. �i t h i n t he s tudy area s i x t rans e c t s were comp r i s e d e igh t. b i rd. coun t i ng. 1.1) .. 200 me t res ( F ig .. es tab l i s hed .. Each. t rans e c t. s ta t i ons a t i n t e r vals o f a p p r o x i ma t e ly. The s i x t rans ec t s we re :. Transe c t 1 a t 360 me t res i n the Manga tainoka S t ream val l ey . Trans e c t 2 a t 580 me t res i n the Manga tai noka S t ream val ley . Trans e c t 3 f rom t he Manga tai noka f o rks a t 360 me t res t o the r i dge be tween the Manga t a i noka and Ruapae cat chmen t s a t 720 m e t re s . Trans e c t 4 a t 720 me t res along the r i dge be t ween t he Manga t a i no ka and Ruapae ca t chmen t s . Transe c t 5 a t 580 me t res i n the Ruapae S t ream val ley . Transec t 6 f rom 7 2 0 m e t r es t o the t op of Herepai a t 1100 me t res .. The t rans e c t s were s e t up s o t hat changes i n d i s t r i bu t i on o f. b i rd s. at. d i f ferent a l t i tudes and i n the maj or fores t types could be s t ud i ed .. To. enable t he. maxi mum. r e p l i ca t i on of coun t s ta t i ons exi s t i ng t ra cks Ye re. u t i l i z ed in es tab l i shmen t o f t rans e c t s . compos i t i on around. each. s t udy ( Drummond i n. prep ) .. bo tani cal s t udy. to. The vege t a t i on. s t r u c t ure. and. s ta t i on was i n t ens ively mapped in a compan i on I. analysed. the. data. c o l l e c t ed. in. t he. i d en t i fy aspec t s of t he vege ta t i on t ha t a f fec t t he. b i rds .. The vege t a t i on was a rb i t rar i ly d i v i ded i n t o four t i ers : Canopy - Trees wi t h more t han 50% o f t he c rown unshaded . Subcanopy - Trees > 4 me t res i n he i gh t bu t under t h e canopy . Shrub - T rees 0 . 5 - 4 metres i n he igh t unde r t he canopy . Ground. Trees < 0 . 5 m e t res. in. heigh t under t he canopy .. In each t i e r 120 t r�es wi t h i n 40 me t res o f each b i rd coun ting s ta t i on were i d en t i f i ed ( Append ix 1). At s ome o f the h i gh e r a l t i t ud e s ta t i ons.

(25) 15. FIGURE 1.1 Map of the Study Area. +-. )( ... " . ". X. t.

(26) 16. t he sub canopy and s hrub l ay e r s we re absent o r reduced 1 2 0 t re e s. were. Po i n t. encoun t e r e d .. and. fewer. heigh t i n t e r c e p t ( PHI ) d a t a were. a l s o c o l lec t ed a t 24 po i n t s wi t hin 40 me t res of each s ta t ion 2) .. At. each. po i n t. a. range. f i nder. ( Append ix. was used t o r ecord the ver t i cal. f o l i age d i s t r i but i on and t h e t ree species o f each i n t e rcept. purposes of. t han. For. the. analys i ng b i r d / plant in t e rac t i ons t r e e f e rn s w e re grouped ,. t he maj o r i ty. were. Cya t he a. s mithi i. wi th. D i cks o n i a squarrosa , and D i cks o nia fi brosa . Me t ro s i d e ros fulgens. and. M e t ros i deros. Cya thea. some. medular i s ,. Two c l i m b i ng r a t a spe c i es ,. di f fusa ,. w ere. These t wo groups and 1 7 t re e s pecies comprised mo re. also. t han. grouped .. 9 5%. of. the. woody vege ta tion i n the s t udy area (Table 1 . 1 ) .. On the bas is o f TIHNSPAN vege t a t i onal types. t he. s tudy. 1.2,. ( Fig .. area. was. c lassif i ed. in to. f i ve. Tables 1 . 2 , 1 . 3 ) , t h e var i a tion w i t h i n. t h e s e groups was demons t ra t e d b y PCA ( F igs .. 1 . 3 , 1 . 4 , d a t a in Appen d i x. 1 , a n d Appendix - 2 ) .. The upper four s t a t i ons we r e markedly di f f e ren t f rom t he s tudy area ,. these. s t a t i o ns. D racophyl lum. foe t i d i s sima ) . canopy h e i gh t. fil i fo lium ,. wid th. some. ( Olear i a. ex t rem ely high ( Append i x 3 ) . through. 48 ,. in. laye r,. and. the. canopy. the They. c olensoi ) ( Coprosma. s t i nkwood. w e r e each les s t han one me t re .. t he r e was no subcanopy o r s h rub. s t a t i ons 45. wi th. leat herwood. O the r woody s p e cies were almost absen t and t he and. of. were clas s i fied as sub a l p ine s crub .. were charac t e r i zed by an abundance o f and. res t. average. Cons equen t ly d ens i ty. was. Stat i ons 43 and 44 w ere mo re d i ve rse t han addition to leatherwood and Dracophyl lum. s everal of t he common f o re s t s pecies were also p r es e n t .. The canopy.

(27) 17. TABLE 1 . 1 The p e r cen t ag e occurrence of common woody s pe c i es i n t h e vege t a t i onal s t ra ta of t h e s tudy a rea. Canopy Subcanopy Shrub. Tre e spe c i es. G round. P.H.I .. Dac ry dium cueress i num. RIMU. 6.1. 0.7. 1.7. 0.3. 3.5. Podocareus fe r rug ineus. M IRO. 4.5. 3.8. 5.7. 6 .0. 6.4. Podocarpus hal l i i. HALL. 2.3. 3.8. 7.1. 1.1. 2.2. Phyllocladus a l p i nus. PHYL. 3.2. 1.1. 2.5. 0.8. 2.4. No tho fagus fus ca. RBEE. 15 . 1. 5.1. 1.6. 3.7. 13 . 1. Me t ro s i deros s pp .. RATA. 0.0. 0.0. 0.6. 2.9. 1.4. �ei nmann i a racemosa. KAMA. 41 . 8. 25 . 4. 3.8. 3.7. 40 . 8. Mel i cy tus rami f l o rus. MAHO. 0.8. 2.6. 0.3. 1.4. 0.8. Myrs ine sal i c i na. T ORO. 6.5. 39 . 8. 6.7. 14 . 8. 9. 9. G r i s e l i n i a l i t t ora l i s. BRDL. 1.7. 0. 3. 0.4. 12 . 6. 1. 1. Elaeo carpus de nt a tus. HI NA. 0.9. 0.5. 1.0. 2.3. 0.5. Carpode tus serratus. PUTA. 1.3. 1.8. 1.7. 1.6. 0.6. Pseudowin t e ra ax i l lar i s. AXIL. 0. 1. 3.8. 6.4. 1.8. 1.4. Pseudowin t era colora ta. COLO. 0.3. 1.5. 5.6. 3.3. 1. 1. Coprosma f oe t i d i s s ima. C FO E. 0. 5. 0. 1. 5.1. 6.1. 0.8. Coprosma polymo rpha. CPOL. 0.2. 0.2. 24 . 3. 12 . 8. 2.3. Olear ia colens o i. O LEC. 6.1. o.o. 0.3. 3.6. 2.8. Dracophyl lum f i li fol i um. DFIL. 2.5. o.o. 0.3. 0.6. 1. 2. Cyathea and Di cks o nia s p p . TFER. 1.9. 7.0. 13 . 2. 0.3. 3.4. 95 . 8. 97 . 5. 88 . 3. 79 . 7. 95 . 7. T o t al percen t ages.

(28) 18. TABLE 1 . 2 Two - way ind i ca t o r spe c i es analy s i s o f pl an t t i ers. S t a t i on. Sp e c i e s. 1 1 1 1 1 114 1133 3 33132 3 3 3 2 2 2 2 2 2223 442444444 348 12567 6 780159034456 7 3 2 980120169 2 34578 1 2 9 345678 0000 HAHO 0000 HINA 0000 PUTA ��������--�=-----�--�---r-RATA 000 1 000 1 AXIL 000 1 TFER RBEE -;;'"'l'"!""F,...."'77..-.t.,..-;:;--.----�---:::��--;->or--r-r""""''r-t-- 0010 00 1 1 RIMU 00 1 1 MIRO 00 1 1 TORO 00 1 1 COLO �----����--010 HALL 010 PHYL ----- ---KAMA 011 011 BRDL 011 CPOL CFOE 1 1 OLEC ------ -DFIL --- � -1 -. --. --. --. 0000000000000000000000 0000000000000000000001111 00000000000000000000000 1 1 1 1 1 1 1 1 1 1 11 1 1 1 1 1 1 1 1 1 000000000001 1 1 1 1 1 1 1 1 1 1100000000000000001 1 1 1 1 Values d eno t e c a t eg or i es o f �bundance d e f i ned by pseudospeci es cu t leve l s . The analy s i s was p e r formed on t he raw d a t a t o clas s i fy s t a t i ons by p l an t s pe c i es compos i t i on and r e la t i ve dens i ty concu r rent ly . The pseud o s p e c i es cu t levels w e re calcula t ed to corres pond wi t h t he d e faul t c u t levels f o r percen t age da t a wi th one add i t i onal c u t l e v e l at 50% . Values t h ere f o re d eno t e the sum of each plan t species p re s en t in a l l t i e rs a t each s ta t i on w i th approx i ma t e equ iva lence t o : absen t. 1 4. =. 0 - 1% 10-19%. 2 5. 2 -4% 20-49%. 3 6. 5-9% 50- 100%. hor i zon t a l Ver t i cal l i nes s e pa r a t e c lasses of s t a t i on a t l e vel 3 ; l ines separa t e c la s s e s o f s p ec i es a t l eve l 4 . Plan t s pe c i e s codes are in table 1 . 1 ..

(29) 19. TABLE 1 . 3 Two-way indi cator spe c i es analys i s o f po i n t he ight i n tercepts. Stat i on. Spec i es. 1 1 13 3 3 1 13 3 34 2 2 2 3 1 2 2 22 3 3 2 2234411444444 1 1 2 6 15 7 73468834 3 4 6 1 5 7 59 047 900190232885611229345678 0000 RATA 0000 PUTA -----------------2 0000 AXIL 0000 - - - 1 1- ----- --- 11-- TFER HAHO ......,...,,...,.--,....,..-.-1-:-:--.--+----rl- 000 1 0001 HINA 001 RBEE 0100 KAHA 0100 TORO 0100 BRDL 0101 RIHU 010 1 H IRO 0 1 10 HALL 0110 COLO 0110 CPOL PHYL ---------0111 0111 CFOE OLEC ---- ----554 1 DFIL 443 1 -------. ---. 00000000000000000000000000000000000000000000 1 1 1 1 00000000000000000000001l 1111111111111111 1111 00000000000111111111110000000000000000000011 Values d enote catego r i es of abundance de f ined by pseu dospeci es c u t levels . The analys i s was pe r fo rmed on t h e raw d a t a t o c lass i fy s t a t i ons by plant spec i es compo s i ti on and rela t i ve d ens i ty The pseu d o s p e c i e s c u t levels were calculated to concurren t ly . correspond wi t h the de faul t c u t levels for p ercen t age d ata wi t h one Values there fore d eno t e the number o f additional cu t level a t 50% . in tercep t s o f each plan t s pec i es present a t each s t a t i on w i th approxi ma t e e q u i valence t o : -. =. absent. 1 4. =. 0 - 1% 10-19%. 2 5. 2-4%. 20-49%. 3 6. 5-9%. 50- 100%. horizon t al Vert i cal l i nes separate clas s es o f sta t ion at level 3 ; l i nes s e p arate classes o f s p ec i e s at level 4 . Plant s pe c i es cod es are i n tab l e 1 . 1 ..

(30) KEY. KEY. nREAM. -----. BIAO COUHTIHO STATION. SCALE. M. A. Subalplrte scrub. B E R s BE. Intermediate AlE High altitude forest. Q o. .,. Diverse Intermediate forest etc. Intermediate B/E Mean Canopy Heigh t 5m.. 0. 0. . , 0. Low altitude forest. <. 5-10 m.. (1) (/). ..... '< "'C <D (/) Q) :::1 a. s:. 10-15m.. >. 1. . 5m. CD Q) :::1. (). !l) :::1 0 "'C '<. :I:. !!?.. ::!!. G) c :0 m -1.. i\;). (Q ::r. (/) 0. I� ;j' en -. Q) ::::: 0 :::1. N 0.

(31) 21. -t. AXIL TFER -1; PUTA "\ MAH \ O \"\ HINA \ \. \\ l ow al t i tude fore s t \\\ RBEE ��.RATA "t. 3 4. p c 1. 2 1. 8 18 7 6. I/n � �. KAMA. ·. BRD. TORO... /. // RIMU d i vers e � 1613 i n t ermed i a te al t i tude 114 f /fore s t 373634 35 # \� 4 0191015 12. �*. '?. MIRO. 17. '3. CPOL 39 20� ��-2132-+ COLO 38923 h igh 31 26 a l t i t ud e 28272524 fo res t + 3042 22 ........ _,.. __ __. .... HALL �. CFOE. �. PHYL. 43 29. scrub/hi gh al t i tude fores t subalp i n e. 44. 48 4 64 7 45. PC 2 FIGURE 1.3 P r i n c i pal component analys i s o f t ree s p e c i es d i s t r i bu t i on ( t i e r s da ta ) The f i r s t two p r i nc i pal componen t s expla i ned 64.1% o f the variation w ithin the data set (PCl 34.7%, PC2; 29.4%). T ree spe c i e s abbrev i a t i ons as in table 1.1, s t a t i ons are numbe red . Four of the 19 var ia bles we re s kewed . =.

(32) 22. \ TFER 3 TA '. � �; ::. al u f o re s t. p c. 1. \� �� �,. MAHO. A. EE AXIL 16 13 \1 6 HINA -�r,34 � 11143 '. 35 39. \J-5. subal p i n e s crub 48474546 DFIL. 17. 3340 37 19. � �. 2 1. �. d i verse �BRDL10 3021 O LEC 43 scrub i n t e rmed i a t �al t i tude 20232427 h igh al t i tude fore s t fore · 12 93228 44 29 ....-TORO /38 MIRO RIMU 2 high 26 C FOE al t i t u d e fores t COLO 41 42. i. ��. 1. CPO 31 25 HALL. j PHYL. PC2 . F IGURE 1.4 Pr i n c i pa l c om ponen t analys i s o f t ree species d i s t r i bu t i o n ( po i n t he i ght i n t ercep t da t a ) The f i rs t t w o pr i n c i pal componen t s expla i ned 47.9% o f t h e 22.7%). varia t i on w i t h i n t h e d a t a se t ( PC 1 35.2%, PC2 Tree s pe c i e s a bbrevi a t ions as i n t able 1 . 1, s t a t i ons are numbere d . 14 o f the 19 var i ables were skewed . =. =.

(33) 23. t he s e. hei ght a t. Al though t h e. t wo. s t a t ions. to. a. two. was. abs ent. some. lesser. extent. s t a t i ons. subcanopy. s t a t i ons , and. be tween. was. and. t h ree. me t re s .. shrubs were p re s en t . 41 ,. 42. and. These. 29,. were. int erm ed i a t e b e tween subalp i ne sc rub and h i gh a l t i tude f o re s t .. All of t he o th e r s ta t ions in the s tudy area were c las s i f i ed as. fores t .. Kamahi ( � e i nmannia racemosa ) was common in t h e canopy and t h e s ubcanopy throughou t t h e. Coprosma po lymorpha and broad lea f ( G r i s e l i n i a. fores t .. li t toral i s ) we r e common i n the shrub and ground t i ers .. The s ta t i on s o f t rans e c t one , 1 6 , 1 7 and 18 were c harac t e r i z ed by l arge numbers of. red. beech. ( No t hofagus. (Melicy t us r am i florus ) , hi nau ( Elaeocarpus. fusca). in. canopy .. t he. Mahoe. ma rble leaf ( Carpo d e t us s erra tus ) , t re e f e rns ,. den tat us ) ,. c l i m b i ng. and. rata. P s eudowi n t e ra. ax illar i s ) w e r e common i n t he o t her t i ers .. S tat ions 1 1, 1 3 , 1 4 , 15 , 33 , 34, 35 , 36, 3 7 fores t .. The. s pec i es. found. on. t ransect. and one. 40. wer e. were. c ommon. s t a t i ons, wi t h t h e exce p t ion of red beech wh i ch was no t s t at ions i n. the. Ruapae valley .. rimu ( Da c ry d ium cupres s i num ) and common. in. the. canopy .. ( Pseudowi n t e r a ax i llar i s ). in. diverse a t t he s e. f o und. at. the. In add i t i on t o t h e u b i q u i tous kamah i , mi ro. ( Podocarpus. Toro. ( My r s ine. we re. common. s ali cina) in. the. f e r r ug i neus ) and. subcan o py. pepper and. were t r ee shrub. layers .. The s t a t i on s o f t ranse c t fou r , 9, 1 2 , 20 , 2 1 , 2 2 , 23 , group as s o c i a t ed wi tn h i gh al titud e fores t . ra t a , t re e f erns and P .. and. 38. form. a. Mahoe, h i nau , marb le l e a f ,. axillar i s we re rare at these s t a t i ons .. Hall's.

(34) 24. t o t ara ( Podoc a rpus c.. hal l i i ) , Phyl loc ladus a lpinus , Coprosrna p o lymo rpha ,. foe t i d i ss i ma , r i mu , m i r o and t o ro �ere. s t a t i ons along. the. r i dge. red. common .. some. of. the. beech was c ommon i n t he canopy , bu t at. mos t s t a t i ons kamahi was the domi nan t spec i es . 39 , 4 1. At. S t a t i ons. 10,. 19,. 29,. and 4 2 �ere clas s i f i ed i n t o d i f fe r e n t groups b y analys i s o f the. PHI and all t i e rs d at a and. �e r e. clas s i f i ed. as. i n t e rmedi a t e. between. fore s t t ypes .. The graphs of the f i rs t t�o p r i nc i pal componen t s i llus t rate the gradual change i n fores t compos i t i on � i th al t i tude and the fores t. s t a t i ons. and. the. the subalp i ne s t a t i ons .. subal p i n e / s crub s t a t i ons i n the data s� t obscured i n ter-rela t i onsh i ps s t a t ions ( F igs .. and. fur t her. 1.5, 1 . 6) .. analyses. d i chot omy. The pre s en c e of the the. excluded. forest the. da t a .. spec i es. upper. s ix. The PCA analys es o f t he PHI da t a d e s c r i bed. less of the t o tal var i a t i on in the o r i g i nal da t a s e t t han the t i ers. be t�een. analyses. of. Many o f t h e var i ables i n the PHI d a t a we re s kewed i n. v i olat i on o f the s t a t i s t i c a l as sump t i ons .. FHD was cal cula t ed f r om PHI da t a by he igh t s into. 35. o ne. me t r e. clas s i f i ca t i on. cl as s e s .. be t�een FHD and i n t ercep t h e i gh t ( r. =. There 0 . 91 , d . f .. was. of. the. i n t e r cept. a h igh cor rel a t i on 46 ,. p. <. 0 . 001 ) .. Th i s was par t i cularly ev i d e n t at the subal pine s t a t i o n s (Table 1 . 4 ) ..

(35) 25. TABLE 1 . 4. Dive r s i ty i nd i ces at each station. S t a t i on. P' o l i a q e H e i qh t Dive rsity H. P l a n t S p e c i ea D i v e r s i ty. :1. H. B i rd S pe c i e s Di v e r s i ty .. J. H. :1. 0 . 70 8. 1. 2 . 890. 0 . 8 20. 1 . 846. 0 . 429. 1 . 699. 2. 2 . 716. 0 . 770. 2 . 312. 0 . 537. 1. 849. 0 . 771. 3. 2 . 801. 0 . 794. 2 . 275. 0 . 529. 1 . 790. 0 . 746. 4. 2 . 960. 0. 839. 2 . 292. 0 . 53 3. l . 830. 0 . 76. 5. 2 . 901. 0.823. 2 . 44 3. 0 . 568. 1 . 78 2. 0 . 743. 6. 2 . 912. 0 . 8 26. 2 . 26 0. 0 . 525. 1 . 685. 0 . 70 3. 7. 2 . 999. 0 . 8 50. 2 . 56 2. 0 . 59 5. 1 . 795. 0. 749. 8. 3 .008. 0 . 8 53. 2 . ·4 3 7. 0 . 566. 1 .831. 0 . 764. 9. 2 . 729. 0 . 774. 2 . 24 0. 0 . 520. 10. 2 . 904. 0.823. 2. 283. 0 . 530. 3. 1 . 355. 0 . 565. 65 7. 0 . 691. l. l.. 11. 2 . 550. 0 . 72 3. 2 . 397. 0 . 5 57. 849. 0 . 771. 12. 2 . 827. 0 .802. 2 .386. 0 . 554. 1 . 58 7. 0 . 66 2. 13. 2 . 760. 0 . 78 3. 2. 401. 0 . 558. 1 . 605. 0.. 14. 2 . 881. 0. 817. 2. 433. 0 . 565. l . 69 4. 0 . 706. 669. 15. 2 . 876. 0 . 815. 2 . 312. 0 . 537. 1 . 775. 0. 740. 16. 2 . 74 4. 0 . 77 8. 2 . 512. 0 . 584. 1. 798. 0 . 750. 17. 3 . 200. 0. 907. 2. 356. 0 . 547. 18. 3. 229. 0.916. 2 . 52 2. 0 . 586. 19. 3 . 134. 0.889. 2. 425. 20. 2 . 932. 0 . 832. 21. 2 . 409. 0.683. 22. 2 . 047. 0 .581. 2 .141. 0 . 497. 1 . 483. 0. 618. 23. 2 . 438. 0.691. 2 . 237. 0 . 520. 1 . 29 9. 0 . 54 2. 2 _4. 1 . 823. 0. 517. 2 . 343. 0 . 544. 490. 0 . 621. 25. 2 . 151. 0.610. 0 . 526. 26. 2 . 428. 2 . 282. 0 . 530. 1 . 49 6. 0 . 624. 27. 2. 541. .o . 6 8 8. 2. 263. 0 . 721. 2 . 271. 0 . 528. 1 . 13 4. 0 . 4 73. 28. 1 . 766. "0 . 5 0 1. 2. 402. 0 . 558. 1 . 479. 0 . 617. 29. 1 . 907. 0 . 541. 2. 314. 0 . 538. 1 . 90 7. 0 . 79 5. 30. 2. 623. 0.744. 1 .853. 0 . 430. 1 . 270. 0 . 529. 31. 2 . 197. 0 . 623. 2 . 13 4. 0 . 4 96. 1 . 54 3. 0 . 644. 32. 2 . 897. 0.822. 2.. 0 . 485. 845. 0 . 769. 33. 2 . 487. 0. 705. 2 . 326. 0 . 540. 34. 2 . 401. 0. 6 81. 2 . 395. 0 . 729. o ·. 6 9 1. 1 .. 710. 0 . 71 3. 1. 835. 0 . 76 5. 0 . 56 3. 1 . 646. 0. 686. 2. 347. 0 . 545. 1 . 744. 0. 727. 2. 334. 0 . 542. 1 . 86 3. 0 . 777. OB 9. l.. 1 .. l.. 146. 0 . 478. 1 . 158. 0. 4 83. 0 . 5 57. 1 . 133. 0 . 472. 2 . 357. 0 . 54 8. 1 . 20 6. 0 . 503. 2 . 361. 0 . 549. 1 . 120. 0 . 467. 2 . 272. 0 . 528. 1 . 19 5. 0 . 498 0 . 410. 35. 2. 436. 36. 2 . 572. 37. 2 . 534. 0 . 719. 3 8. 2 . 270. 0 . 64 4. 1. 930. 0 . 448. 0 . 983. 39. 2 . 672. 0 . 758. 2 . 19 3. 0 . 509. 1 . 213. 0. 506. 40. 2 . 497. 0 . 708. 2 . 21 5. 0 . 515. 1 . 19 7. 0 . 499. 41. 2. 468. 0 . 70 0. 2 . 10 1. 0 . 488. 1. 920. 0 . 801. 42. 2 . 299. 0 . 652. 2 . 370. 0 . 5 51. 1 . 94 9. 0 . 813. 43. 1 . 499. 0. 4 2 5. 2 . 431. 0 . 565. 1 . 435. 0 . 598. 44. 1 . 309. 0. 371. 2. 476. 0 . 5 75. 1 . 207. 0 . 503. 45. 0 . 410. 0 . 116. 1. 311. 0 . 305. 1 . 077. 0. 449. 46. 0 . 58 3. 0 . 165. 1 . 02 2. 0 . 238. 1 . 16 9. 0. 487. 47. 0 . 8 79. 0 . 249. 1. 401. 0 . 326. 48. 0. 624. 0 .177. 2 . 027. 0 . 4 71. H = diversity. 1 . 029 1 . 401. J = evenness. 0 . 4 29 0 . 584.

(36) 26. \1 ER. AXIL. r:. PUTA. HO. /. lov a l t i tude fore s t. 18. \. 8 1 6. 14 11. p c 1. d i ve r s e 40 i n t e rmed i a t e. 4 2. RBEE. 1. 33. � CFOE CPOL HALL. PHYL. PC2 FIGURE 1 . 5 P r i n c i pal compone n t analys i s o f t r e e s pe c i es d i s t r i bu t ion ( t i ers d a t a , s t a t i on s 43-48 excluded ) The f i rs t t vo p r i n c i pal componen t s explai ned 56 . 1% o f the var i a t i on w i t h i n the d a t a s e t ( PC l 40 . 7% , PC2 15 . 4 % ) . T ree s pecies abbrev i a t i ons as i n t able 1 . 1 , s t a t i ons are numbered . Tvo of the 17 v a r i a b l e s vere skeved . =. =.

(37) 27. p c. 17 35. 1. 2 13 0 10 . 2 7 2 02 423 38932 29 22 COLO PHYL. PC2 FIGURE 1 . 6 Prin c i pa l componen t analys i s of t ree s pe c i es d i s t r i bu t i o n ( po i n t he i gh t i n tercept d a t a , s ta t i on s 43-48 exclud ed) The f i r s t t wo p r i nc i pal compone n t s expl a i ned 46 . 4% of t h e vari a t ion w i t h i n the d a t a s e t (PCl 3 1 . 5% , PC2 14 . 9%) . Tree s p e c i e s abbrevi a t ions as in t a b l e 1 . 1 , s ta t i ons a re numbered . 1 1 of t he 1 7 var i ab les w ere skewed. =. =.

(38) 28. 29. small fores t PD3. 25. 28. 24 31. 27 p c. 1. 41. 42. s parse. I 2036. subcanopy. 2 6 1. 14. 3. 127 I 1 7 18 4. 30. 9. �. 40. /. \. .. 5. 37. ./ YID2. 21 32 dense subcanopy. 10. 11. PD3. \. YID3 DBH3 + DBH1. XCAN YID1 large s i zed fore s t PC2 F IGURE 1 . 7 P r i n c i pal c ompon e n t analys i s o f fores t s t ruc ture ( s ta t i ons 1-42 only ) The f i rs t two p r i n c i pal componen ts explai ned 64 . 3% o f the var i a t i on wi t h i n the d a t a s e t ( PCl 48 . 1% , PC2 1 6 . 3%) . S t ru ctural parame t e r abbrev i a t i ons as i n appen d i x 3 , s ta t ions are numbe red . No vari able was skewed . =. =.

(39) 29. FHD of. the. s ta t i on s. i n t he Hanga t a i noka R i v e r valley ( s t a t i ons 1 - 20 ). ve r e s i g ni f i can tly larger ( t 4 0 s t a t i on s .. 7 . 67 . p. =. 0 . 00 1 ) than t he o th er f o r e s t. <. PSD vas c a l cula t ed f rom the fore s t t i e r s d a t a (Table 1 . 4 ) , a. to tal o f 7 4 plan t s p e c i e s vas reco rded .. The. f our. subalp i ne. s ta t i ons. ha d love r P SD but n o pa t t e r n vas e v i d e n t in the r e s t of t he s t udy a rea . FHD and. PSD. were. 0 . 6 4 ) , and when. n o t s i gn i f i can t ly corre l a t ed ( t 4 6. the subalp i ne s t a t i on s wer e removed f rom the analy sis ( t 4 0. the. The i n t e r-rela t i onsh i ps be t ween fores t s t ruc ture and the s tudy. area. in. d i splayed. ar e. 1.7. or. m i s s i ng. t ree. size.. The. shrub. The f i rs t t wo. s t a t ions. mai nly. this. on. the. These. compone n t .. laye r s .. The. and. mean. s e cond. t runk. d i ame t e r. The s e. par ame t e rs. of. bo t h. p r i n c ipal componen t s epa r a t ed. s t a t i ons on the bas i s o f subcanopy dens i t y and mean t runk the subcanopy .. s ix. c o r r e l a t e d wi t h mean canopy h e i gh t , mean f o l i age w i d t h. o f all t hree vege t a t i onal s t ra t a , canopy and. upper. d ens i t i es o f b o th t he canopy and t he s h rub. layers were h ighly po s i t i v e ly correl a t ed wi t h we re nega t i ve ly. of. 6L. . 4% o f t he v a r i ance i n t he d a t a s e t .. expl a i ned. The f i rs t p r i n c ipal c ompone nt d i f f eren t i a t ed bas is o f. s t a t i on s. the. at. s t a t i ons t hese s ta t i ons we r e exclud ed f rom t he analys i s . pr i ncipal componen t s. 0 . 034 ) .. ( da t a i n Append i x 3 ) .. f i gure. Be cause s ome o f the t i e r s were absen t. =. d i ame t e r. of. we re i nv e r s e ly co r r e l a t e d w i th e a ch. o t her .. The s t a t i ons o f t rans e c t s o ne and t wo and t he t ran sec t. three. s t a t i o ns , wi th ':orrel a t ed w i t h. were the. c o r r ela t ed excep t i on. p r i n c i p al. of. wi t h. large. s t a t i on. compone n t. one .. ass oci a t e d. Al l. t rees . n i ne , The. s ta t i ons. were other. of. of. these. nega t i ve l y s ta t i ons we r e. r rel a t ed wi t h smal l e r t re e s , the excep t ion i n t h i s group vas. s t a t i on.

(40) 30. 37 .. The. d ens i ty. and. size. of. the. subcanopy var i ed markedly w i t h i n. t ra nse c t s .. s t udy. Pre c i p i t a t ion and t empe ra t ure were measured at four s i t e s i n t h e are a : A. A t s t a t i o n 1 7 near t he Manga t a inoka forks a t 3 60m .. B. A t s t a t i on 1 1 in the Manga t a inoka valley a t 580m .. c. A t s ta t i o n 2 4 on t he r i dge a t 730m .. D. A t s t a t i o n 3 7 in the Ruapae valley a t 580m .. Tempera t ure was si t e .. u s i ng. a. max i ma / min i ma. An analys i s of vari ance of the r e corded. tha t s i t e 1.5) .. recorded. A. was. s i gn i f i can t ly. gauge. o f t he s t udy an. t empe ra t ures. i nd i ca t ed. warmer t han the o th e r s ta t ions ( Table. P r e c i p i t a t ion was recorded us i ng. Ini t i al ly one. t he rmome t e r a t each. 1 50mm. capac i ty. rain. gauges .. was p laced a t each s t a t i on but i n t he second year. add i t i onal. were. placed. at. p re c i p i t a t i on. wi t h i n. t he. f o res t was. d i f f i cul t , wha t was a c t ual l y measured was t hroughfall .. The. amoun t. Accurat e measuremen t. wa t e r. wh i ch. of. reached. t re e s . The presence quan t i f i ca t i on. of. t o tal. e ach. of. two. gauges. gauge. three. was. gauges. wi t h i n -s i t e. affected at. i n t erpre t a t i on o f d i f f e r ences b e tween s i t e s .. the. of. sur round i ng the. accura t e. more. and. site.. enabled. site. each. var i a t i on. by. each. Us i ng t hese t e chn iques i t. was found t h a t s t a t i ons B and D rece i ved s igni f i can t ly more throughfall t han s t a t ions A and C ( Tabl e gauges w i t h i n. the. 1 .6) .. On. s evera l. o ccas i on s. t he. s t udy a r e a o v e r f l o w e d b e tween v i s i t s h e n ce. rain. t he. data. f rom New Zealand M e t eo r o log i cal S t a t i o n a t Putara t h r e e ki l ome t res f rom the s t udy area were col l e c t ed . Pu t a ra and. the. mon t hly. The t o t a l mon thly r a i n fall meas u re d. maxima/ m i n i m a. d i s p layed i n f i gu res 1 . 8 and 1 . 9 .. t empera t ures. Tempe r a t ure. cycled. at. s i te. annually ,. C. at are wi th.

(41) 31. m ax i ma in. summe r. pred i c t able �ay .. and. m i n i ma. in. �inter .. Rai n fall d i d n o t vary i n a.

(42) 32. TABLE 1 . 5 Mean t empe r a t ures wi thin the s t udy area. SITE c. S.E.D.. A. B. MEAN MAXIMUM ( C. 15. 4. 14 . 6. 14 . 4. 14 . 5. 0 . 13. MEAN MINIMUM ( C. 4.8. 3.7. 3.6. 3.9. 0 . 09. S.E.D.. =. D. The s t andard e r r o r of the d i f ference i n. t emper a t ure. be tween. s i t e s on a weekly bas i s c a l cul a t e d by Analys i s of Var i ance .. Applying Tukeys Tes t. •. A > B. Level o f. C. D. s ign i f i can c e. t empera tures .. 0 . 00 1. for. bo t h. max i mum. and. m i n i mum.

(43) 33. TABLE 1 . 6 Mean r a i n fall w i t h i n the s t udy a rea. SITE S.E.D.. A. B. c. D. MEAN RAINFALL ( cm ) A. 68 . 9. 75 . 0. 69 . 4. 69 . 9. 2 . 37 ·. MEAN RAINFALL ( cm ) B. 69 . 2. 79 . 3. 57 . 4. 85 . 4. 2 . 71. The. S.E.D.. s t andard. e rr o r. of. the d i f fe rence i n r a i n fall be tween. s i t es on a weekly bas i s ca lcula t ed by Analy s i s of Var i an ce .. A. Vi s i t s 6 t o 3 9 when t he r e was one ra i n gauge a t each s i t e .. B. V i s i t s 40 t o 7 6 when t here were t hree r a i n gauges a t each s i t e .. Applying Tukeys Tes t. I n t e rval A. no s ign i f i can t d i f ferences be t ween s i tes .. I n t e rval B. S i t es D. B. >. A > C. S i t e D > s i t e s A and C a t the 0 . 00 1 level o f s ign i f i cance . a t t h e 0 . 00 1 lev e l n f s i gn i f i cance .. Site B > si te. c. Si te B > s i t e. A a t the 0 . 05 level o f s i gni f i can ce .. S i te A. c. >. si te. a t the 0 . 05 level of s ign i f i cance ..

(44) 34. 700 600 500. Total Rainfall. (mm). 400 300 200 1 00. Nov. Jan. Mar. May. Sep. Jul. 1 983. Nov. Jan. Mar. May. Jul. Sep. Nov. Jan. 1 984. Month of study. FIG U R E 1 .8 Total rai nfall at Putara 25. -. Maxim um. --. Minimum. 20. 15 Temperature 10 (celsius). 5 I. I'. 0. -5. I. '-. \. I '/. r. \ ' /. I. I. ". \. I -..... 1. �'�����. Nov. Jan. Mar. May. 1 983. Jul. Sep. Nov. Jan. Mar. Month of study. May. Jul. Sep. Nov. 1 984. FIG U R E 1 . 9 Monthly maxi ma and m i n i ma temperatu res at site C. Jan.

(45) 35. CHAPTER 2. BIRD ABUNDANCE AND DI STRIBUTION. 2 . 1 I n t r o du c t i on. To es tabl i s h t h e rela t i ve i mp o r tance of d e t e rm i nan ts abundance and. d i s t r i bu t i on. the rela t i ve or absolu t e The. selec t ed .. a. abundance. of. t hose. b i rd. mus t. be. s ubj e c t. of. d e ba t e. census t echn i q ues b y s i mul t aneous collec t i on o f d a t a us ing -. al .. Emlen. 19 7 7 ,. Des an t e. 1 98 1 ,. 1 98 1 , And e r s o n and Ohmar t 198 1 , O ' Meara 1 98 1 , Redmond. 1 98 1 , T i lghman and Rus ch. Hamel 1 984 ,. s p e c i es. There have been several compar a t i v e s t ud i es o f. two o r more me thods ( F ran z r e b 1 9 7 6 , 1 9 8 1 ,. e t al .. spec i es. val i d i ty o f d e ns i ty es t i ma t e s and the u l t i m a t e accuracy. (Ralph and Sco t t 1 9 8 1 ) .. Edwards e t. b i rd. census t echn i que whi ch e s t i ma t es e i ther. of the d i f f e ren t t ypes of l and b i rd su rvey are the. the var i ous. of. Shields. and. 1 98 1 ,. Re cher. Svensson. 198 1 ,. Arnold. 1 98 3 ,. 1984 , Verner and R i t t er 1 985 , 1 988 ) .. The gen e ral conclus i on t o be d rawn f rom these papers i s t h a t. t he. mos t. accura t e me thod of es t i m a t i ng d e ns i ty i s band i ng and s tudy o f all b i rds in an. area .. dens i ty .. All. of. the. o t her. t echni ques underes t i ma t e popul a t i on. I n d e c r eas i ng accuracy t h e o th er me t hods we r e. c i r c u la r - p l o t ,. and. l i ne. t ranse c t. argu ed that all o f these t echn i q ues accura t e e s t ima t es. of. ( van. Ri per. have. absolu t e abundance .. 1 98 1 ) .. prob lems. and. spo t. map p i ng ,. Dawson ( 1 98 1 c ). n one. prov i d e. H e conclu ded t hat t he mos t. eff i c i en t type o f su rvey g i ven the po s s i ble sources o f e r r o r was a l in e t r ans e c t t e chn i q ue wi th a nea r / far ra t i o ( Jarvinen and V a i s anen. 1975 ) ..

(46) 36. Ver ner ( 1 9 8 1 ) s t a t es t ha t : s ci ence " , and. po i n t s. to. " b i rd coun t i ng i s a d i s t r e s s i ng ly i mprec i s e t he. h i gh. be tween. var iance. in d i ca t i on of the large number o f bias i ng fac t o rs .. coun t s. as. He concluded. an. t ha t ,. wh i l s t i mp roved s ampl i ng d e s i gn could reduce t he amoun t o f b i a s , i t had prov ed i mpos s i bl e. to. coun t. accura t ely. all. s pe c i e s comp r i s i ng av i an. comm un i t i e s thus f ar s ample d .. In New Zealand fores t s far mor e b i rds are pr ecludes accu r a t e. e s t i ma t es. of. heard. d i s t ance. t han. ( Daws on. s ee n and. and. Bul l. this 1975 ) .. Add i t i onally , the ruggednes s o f the t e r r a i n i n many New Zealand f o re s t s makes t he use o f t rans e c t c ensuses d i f f i cul t b ecause t he o bserver concen t r a t e on. p rogre s s i ng t h rough the f o r e s t .. The s e d i f f i cu l t i es led. Daws on and Bull ( 1 9 7 5 ) t o d e v e l o p a cos t e f f i c i en t me t hod New Zealand seen o r. f o re s ts .. heard. in. a. Transec t s through. for. use. s t a t ionary. par t i cular. coun t. hab i t a t s. over can. a be. t e chn i que was developed to provi de an i ndex of. areas .. f i ve-m i nu t e. p e r i od .. und e r t aken w i th coun t. abundance. wh i ch. could. spec i es. t i mes o f the year o r for i n t e r - s p ec i es compa r isons .. is becaus e no es t i ma t i o n o f d i f f e rences. The. d i f f erences in the d ens i ty o f common b i rd s p e c i e s b e t ween. I t canno t be used in c ompar ing t he dens i ty of the s ame. a t d i f feren t. in. The me thod involves the record i ng o f every b i rd. s t a t i ons a t suf f i c i en t i n t e rvals t o avo i d overlap o f c ensus areas .. de t e c t maj o r. mus t. in. d e t e c t ion. cons p i cuousness. d i s t ances. could. ac coun t. is for. i n clude d , mos t. of. Thi s hence the. va r i ab i l i ty be tween s p e c i e s o r s easons .. Several researchers i n New Zealand have used f i ve-min u t e b i rd coun t s t o compare b i rd commun i t i es i n d i f fe ren t 1 9 7 7 , Dawson e t a l .. habi t a t s. ( Vi l k i ns o n. and. Gues t. 1 9 78 , Onley 1 980 , G i l l 1 980 , Har r i s on and Saund ers.

(47) 37. 1 98 1 , Vi lson. et. al .. 1 98 8 ) .. G i l l ( 1 9 8 0 ) has shown th a t c oun ts f o r 2. species vari ed i n conj unc t i on map ping .. Howeve r ,. t he r e. charac t e r i s t i cs o f rev i ewed t he. wi th. was. conce rn. d i f ferent. factors. that. d e ns i ty. assessed. abo u t. hab i t a t s .. by. var ia t i o n. V i l ey. and. d i s t ances , t i m e s o f. at. a f f e c t s ound t rans m i s s ion ;. d i f fe re n t. day ,. and. l oca t i ons ,. wea t h e r. Saunde r s. a t t enua t i o n .. The d i f ferences be tween hab i t a t s. var iab l e .. ( 1982 ). t h ey concluded habi t a t s. needed. heigh t s above ground ,. cond i t i on s .. Harri son and. i n the sound. R i chards. that quan t i f i ca t i on of s ound a t t enua t i on i n d i f fe r ent repeated measu r emen t s. t e r r i t or i al. In. New. Zeal and. ( 1 9 8 1 ) a t t em p t ed t o quan t i fy var i a t i on in sound. Amp l i f i c a t ion ,. i.e.. an. we re. i n c on s i s t ent. and. i n c rease i n volume w i t h i ncreased. d i s t ance , o c c u r red at vari ous d i s t ance s , f r equen c i es and. They. a reas .. concluded t h a t the r e s o lu t i on of fac t o rs a f fe c t i ng sound a t t en ua t i on i n fo res ts wou ld b e a n e xt reme ly comp l ex task.. To compare FHD and PSD with rela t i onsh i p of. b i rd. BSD ,. communi ty. and. to. s t ru c t ure. compos i t i on , e s t i ma t es o f the dens i ty of s t a t i on are. r e qu i r e d .. inclus i on of comb ined wi t h. a. to. e ach. PCA. to. f o re s t b i rd. d es c r i be. the. s t ruc t ure. and. spe c i es. at. each. I cal c u la t ed an i n d ex of cons p i cuousnes s by the. d i s t ance the. use. t o tal. del i m i t e r . count. The. y i e lded. c o n s pi cuousness. r e la t ive an. index of abundance .. The. census was then e q u i valent to the t ranse c t coun t me thod of J arv inen and Vai sanen ( 1 9 7 5 ) mod i f i ed for p o i n t coun t s .. Be cause. a. n ea r / far. ra t i o. quan t i f i es conspi cuousness i t can be used a s a summa t i on o f b i as . al lows val i d. compar i sons. of. d i fferen t t imes o f t he year . coun t s is. small. large. d i f fe r en t. Th i s. spec i e s i n var i ed hab i t a t s a t. Howeve r , i f the number. of. e r r o r s can resul t due t o chance .. n ear. or. far. Th i s type o f. bias i s p r i ma r i ly caused b y small numbers o f c oun ts b u t can a l so. occur.

(48) 38. because a s p ec i es is i ncons p i cuous o r rare .. The mod i f i ca t i o n o f the s tandard f i ve-mi n u t e b i r d coun t t o c l o s e to t h e resear che r is eas ily appl i ed .. i n t e r i o r area mod i f i ca t i on is. f i ve -minu t e b i rd. of. maj or. count. s i gn i f i cance. f rom. a. h ab i t a t s. and. it. an. Howeve r , the. t ran s fo r ms. the. coarse i ndex of abundance wi t h s evere. l i mi ta t i on s to a census t echni que . b o t h be t ween. b ecause. i n cl u d e. As a result many more. spec i e s ,. c an. be. made .. The. d e t ermina t i on of t ho s e fac t o rs wh i ch are mos t impor tant i n. c ompar i sons , s u bsequent s t r u c t u r i ng. the b i rd commu n i t y i s fac i l i t a t ed .. In t h i s chap t e r e igh t main po i n t s are con s i d e red : 1 . The gene ral e f fe c t o f w i nd and wa t e r n o i s e on the numbers .o f b i rds observed . 2 . The u s e o f n e a r / far ra t i os t o calcu l a t e an e f f ec t i ve rad i us o f d e t e c t i o n f o r each b i rd spe c i es a t each group o f s ta t i o n s . Exam i na t i on o f t h e mean rank o f these e f fect ive rad i i i n d i ca t e s wh i ch envi r onmen tal var i able has t h e l arges t e f f e c t on b i rd c o un t s . 3 . The use o f n e a r / f a r ra t i os i n conj unc t i on wi th t o t al num b e r o f b i rds coun t ed t o calcul a t e dens i ty i n d i ces . The d ens i ty i nd i ce s were compar e d w i t h t o t al b i rd coun t s a n d wi th dens i ty e s t i m a t e s based on n e a r o b s erva t i ons only . 4 . The i n t e r - r e la t i o ns h i ps of b i rd spec i es d i s t r i bu t i ons w i t h t re e species 5.. d i s t r i bu t i ons and f o res t s t ru c t u r e .. The t o tal num b e r s o f each b i rd s p e c i e s o b s erved i n each mon t h o f the s tudy .. 6 . The rela t i ons h i p . o f changes in numb e r s o f bi rds observed t o changes in cons p i cuous n e s s and e s t i m a t es of changes in dens i ty on a mon t h ly.

(49) 39. bas i s . 7 . S i mi lar i ty o f b i rd s pe c i es d i s t r i bu t i ons w i thin the s t u d y a rea be tween years . 8 . Seasona l movemen t o f b i rds wi t h i n the s t udy area .. 2 . 2 M e thods. Fo r ty-e i gh t b i r d coun t ing s ta t i ons on s i x 1.1).. (Fig.. F rom. Sep t ember. 1 98 2. t ransec ts. un t i l. were. February. f i ve-m i nu t e b i rd coun t s ( Dawson a nd B u l l 1 9 7 5 ) we re station.. e s t ab l i s hed. 1985. mod i f i ed. execu t ed. at. each. The mod i f i ca t i on cons i s t ed o f reco r d i ng each b i rd o b s e rved as. near or. far .. obse r ve r ;. Near. observa t i ons. were w i t h i n 20m hor i zo n t al ly o f the. all o t her observa t i ons were f a r .. was e l i m i n a t e d. by. maki ng. three. coun t s. mo r n i ng , m i d d l e o f day and a f t ernoon . hours o f d awn o r dusk .. B i as due to per. No coun t s. used to d e r i ve i nd i ces of r e la t ive abundance . model. of. coun t s ( Append i x 4 ) .. were. of. d ay. a t ea ch s ta t i on ; made. w i thin. Jarvi nen. The nea r / f a r r a t i o was The index was b ased upon. and Vai s anen ( 1 9 7 5 ) mod i f i ed for po i n t. T o calcula t e. the. i nd ex. of. abundan ce. at. each. s t a t i on the s t a t i ons were g rouped .. Group 1. S t a t i ons 1 -8 , 1 7 , 1 8. T rans e c t one and rela t e d s t a t i ons. Group 2. S t a t i ons 9 - 1 6 , 1 9 , 20. T rans e c t two and rela t e d s t a t i ons. Group 3. S t a t i ons 2 1 - 3 2 , 4 1 -42. Fo res t s t a t i ons of the r i dge. Group 4. S t a t i ons 33-40. T rans e c t three. Group 5. S t a t i ons 43-48. Subal p i ne and s crub s t a t i on s. =. 2. B i as due t o d i f f e ren t i a l wea ther cond i t i on s was. reduced by avo i d i ng adverse wea ther cond i t i ons .. the l i near. month. t i me.

(50) 40. Th i s m i n i mi zed s t ochas t i c e f f e c t s on. the. d e t e c t i on were. of. e s t i ma t ed. d en s i ty per s t a t i on vas obs e r ved a t s t at i ons .. tha t. each. compu t ed. s t at i on. and. f rom the. with. e s t imates. these the. groups .. t o t al. Rad i i. ra t i o .. of. The relat i ve. numbe r s. of. bi rds. e f f e c t i ve rad i u s at t ha t group of. The ac curacy o f the me thod. dens i t i es ob tained obs e r ved .. for. near / far. vas. checked. bas ed. by. compa r i ng. the. on the numbe r o f near bi rds. Vhen d e ns i ty vas calcul a t ed on near observa t i ons only i t vas. assumed t h a t all b i rds However , t h i s. wi t h i n. calcula t i on. 20m. would. of be. the an. obse rver. underes t i ma te. wer e. r ecorded .. o f popula t i on. d ens i ty because s ome b i rds woul d be m i ss ed .. Da ta recorded i n each coun t : 1 . The coun t s t a t i on . 2 . New Zealand S t andard T i m e a t the s t a r t o f the coun t . 3 . The w i nd no i s e on a subj e c t i ve s cale 0. calm. 1. some leaf moveme n t no no i s e heard. 2. d i s tan t rus t le. 3. i mmed i a t e no i se , t w i gs and small branches mov i ng. 4. i mmed i a t e no i se w i th gus t s , b ranches movi ng. 5. con t i nuous h i gh w i nd. 6. gale , leaves be i ng s t r i pped o f f t rees. 4 . C loud cover i n o c t as . "' a t e r no i s e o n. a. subj e c t i ve s cale. 1. no wa t e r n o i se. 2. low level wa t er n o i s e. 3. med i um level '"a t e r no i s e. 4. h i gh l eve l wa t e r n o i s e.

Figure

FIGURE 1.1 of the Study Area
TABLE 1 . 1
TABLE 1. 2
TABLE 1 .  3
+7

References

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