SOE Report 2015-2018

Aquatic Ecosystems in Gisborne

MACROINVERTEBRATE COMMUNITIES

August 2018

2

SOE REPORT 2015-2018

AQUATIC ECOSYSTEMS IN GISBORNE

MACROINVERTEBRATE COMMUNITIES

AUGUST 2018

Harriet Roil (Gisborne District Council)

Russell Death (Massey University)

This report has been peer reviewed by:

Sandy Gorringe (Gisborne District Council)

3

Executive Summary

Gisborne District Council’s biomonitoring programme collects macroinvertebrate data

annually from 81 sites around the region to assess stream ecological health. The programme is

a state of environment (SOE) monitoring programme that helps understand Gisborne’s

freshwater ecosystems and contributes to councils freshwater reporting for the Resource

Management Act 1991 (RMA), Tairāwhiti Resource Management Plan, and the National Policy

Statement for Freshwater Management (NPS-FM). The report presents the first assessment of

the ecological state of Gisborne’s streams from 2015-2018.

Across the East Coast from 2015-2018, using the Macroinvertebrate Community Index (MCI),

12% of sites had excellent water quality and 17% had poor water quality and are below the

national bottom line (NPS-FM). At 37% of the sites the Macroinvertebrate Community Index

(MCI) indicated good water quality. This includes two of the reference sites (Te Arai River at

Intake GRES86 and Waihirere stream GRES67) that are located in soft sedimentary geology. At

32% of the sites the MCI was classified as fair.

All the streams with excellent health were found in indigenous forest or exotic forest and were

higher up in catchments. The sites in the poor category were located in a mixture of pasture,

urban and cropping land use, and were found in the lowland and intensified areas of the

region. The site with the highest MCI score was a reference site Mata Upper (MCI=141), and

the site with the lowest MCI score in the region was Kurunui stream (MCI=55).

Land use had an influence on the health of a stream, with sites that had higher levels of

deposited sediment and conductivity having a lower MCI compare to sites with low deposited

sediment levels that were found in indigenous of mature exotic forest. Indigenous forest, exotic

forest, pasture, urban and cropland are the dominant land uses found in the region. Geology

also had an influence on the biological health of a stream, with a significant difference

between hard and soft geology types.

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Table of Contents

Executive Summary ................................................................................................................................... 3

General introduction ................................................................................................................................. 5

Legislative context .......................................................................................................................... 5

Introduction ................................................................................................................................................. 6

Objectives ........................................................................................................................................ 6

Background ..................................................................................................................................... 6

Overview of Aquatic Monitoring Programme .................................................................................... 23

Stream monitoring ........................................................................................................................ 23

Methods ..................................................................................................................................................... 23

Monitoring sites .............................................................................................................................. 23

Invertebrate Sampling and Processing .................................................................................... 24

Habitat and Periphyton sampling ............................................................................................. 24

Biological Indices .......................................................................................................................... 25

Statistical analysis .......................................................................................................................... 26

Results ......................................................................................................................................................... 26

Summary of physical conditions ................................................................................................ 26

Macroinvertebrate metrics ......................................................................................................... 26

The link between land use, geology and water quality ....................................................... 35

Invertebrate communities ........................................................................................................... 39

Discussion ................................................................................................................................................... 41

Recommendations .................................................................................................................................. 44

Acknowledgements ................................................................................................................................ 45

References................................................................................................................................................. 45

5

General introduction

Under the Resource Management Act (RMA) 1991, Gisborne District Council is required to

promote the sustainable management of the region’s natural and physical resources. The

Gisborne region’s land use is made up of 56% agriculture, 24% exotic forestry, 13% indigenous

forest (Including regenerating) and 2% horticulture, and supports a population of 43,653

people. Proportionally, Gisborne has the highest area of the most erodible overlay 3A land in

the country. Land use activities associated with exotic forestry, urbanisation, farming and

horticulture can have adverse effects on freshwater systems. These adverse effects are likely

to increase with intensification of land use practices.

Gisborne District Council is faced with a challenge of economic growth in horticulture, large

areas of forestry harvest and intensification of farming practices while minimising

environmental degradation and loss of freshwater ecosystem values. Aquatic ecosystem

monitoring is used to assess waterways in the Gisborne region to understand and inform the

ecological condition of streams in areas throughout the East Coast.

Legislative context

The Resource Management Act (RMA) 1991 Section 35(2)(a) imposes a duty on Regional

councils to monitor the state of the environment (SOE) in their region and section 35(2)(b)

requires the effectiveness and efficiencies of policies, rules, or other methods in their policy

statements or plans . The National Policy Statement for Freshwater (NPS-FM) 2014 (amended

2017) requires councils to set objectives and limits for the state of freshwater bodies in their

regions, and directs them to manage water quality in an integrated and sustainable way. The

NPS-FM states ecosystem health as a compulsory value and sets a national bottom line.

The NPS-FM policy CB3 indicates that if the Macroinvertebrate Community Index score (MCI)

is below 80 or has a declining trend the MCI needs to be improved to above 80 and to halt

the declining trend. This gives certainty as to whether desired outcomes are being met. When

waterways are in a poor state, they will need to have a restoration plan and be improved to

at least above the national bottom line.

6

Introduction

Objectives

In 2015, a monitoring programme was started by the Gisborne District Council to monitor

stream ecological health across the region. SOE monitoring and reporting is designed to

provide an early warning of environmental influences, and to understand where

environmental management practices have been effective. The information allows council

and communities to understand the condition of the environment and potential pressures.

SOE monitoring should inform policy and plans and highlight the need for change or further

action where there have been findings from monitoring.

The aims of the ‘State of Environment’ (SOE) Biomonitoring programme in Gisborne are to:

Provide information on the current state of ecological communities

(macroinvertebrate and periphyton) in the rivers in the Gisborne region.

Assist in detection of spatial and temporal changes in freshwater quality and quantity

Provide scientific information required to assist with the preparation of Gisborne’s

policies and plans, and determine the effectiveness of regional plans and policies.

Provide information to assist targeted investigations where remediation or mitigation of

poor water quality is required

Background

The Gisborne region is approximately 8355 km2 and includes over 12,000 km of river length. The

larger catchments found in the Gisborne region are the Waipaoa, Waimata, Uawa, Waiapu,

Hangaroa and Motu, with smaller catchments located along the coast, and further inland

including the Koranga.

The region is composed mainly of soft sedimentary geology (Figure 1), located around the

Poverty Bay Flats, up to Tokomaru Bay and inland towards Matawai. The East Cape also has

soft sedimentary geology and as you get closer to the district boundary, along the base of the

Raukumara ranges the geology changes to hard sedimentary. A few pockets of volcanic

acidic and alluvium geology also exist within the region.

Gisborne’s dominant land uses include exotic forestry, extensive farming and horticulture.

Large amounts of land used for extensive farming were planted in exotic forest following

Cyclone Bola in 1988 and these areas are now being clear fell harvested throughout the region.

With only 5 dairy farms in the region, the environmental pressures from large areas of intensive

dairying found in other regions of the country are less of an issue in Gisborne.

The soft sedimentary geology making up most of the region (Figure 1), coupled with land use

and climate are the strongest influences on local freshwater systems. Due to the range in

climate, and other natural conditions across the region it is important to understand the

ecological differences between catchments across the region. This may help explain potential

pressures or areas where pressures interact with land use.

There are 81 sites, including 6 reference sites currently monitored in the SOE biomonitoring

network in Gisborne (Figure 1). The sites are located across geologies, climate, stream orders,

land use and source of flow (Table 1).

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It is important to consider all of these environmental variables to include the ecological range

that might be present across the region. The sites sampled from Austral summer 2015-2018 are

shown in Table 1, there were 212 samples taken in total over the three year period.

Table 1. Number of sites in the Gisborne biomonitoring region in River Environment Classification (REC)

categories; Source of Flow, Geology, Climate, Stream Order

Landuse Number of

sites

Source of

Flow

Number of

sites

Geology Number of

sites

Cropland 1 H (High

Elevation)

27 Al (Alluvium) 1

Exotic Forest 14 L (Low

Elevation)

52 HS (Hard

Sedimentary)

14

Indigenous forest 9 M

(Mountain)

2 SS (Soft

Sedimentary)

59

Pasture 56 VA (Volcanic

Acidic)

7

Urban 1

Grand Total 81 Grand Total 81 Grand Total 81

Climate Number of

sites

Stream

Order

Number of

sites

CW (Cold Wet) 18 1 2

CX (Cold

Extremely Wet)

7 2 23

WD (Warm Dry) 8 3 15

WW (Warm Wet) 38 4 19

WX (Warm

Extremely Wet)

10 5 15

6 5

7 2

Grand Total 81 Grand Total 81

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Figure 1: Map of biomonitoring sites in the Gisborne region with Geologies (Aluvium (AL), Hard

Sedimentary (HS), Miscellaneous (M), Soft Sedimentary (SS) and Volcanic Acidic (VA) from the REC

classification system. 6 reference sites are highlighted in green.

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Table 2: The 81 sites monitored from 2015-2018, (reference sites are surrounded in red)

GRES1 Kopuapounamu stream Trib GRES2 Waipaoa Trib at Lavenham-

Humphrey rd

GRES3 Parihohonou stream at SH2

Overbridge

GRES6 Pangopango stream at Waiau

GRES7 Makarika stream at Keelan rd

GRES8 Mangatu Trib

10

GRES9 Huitatariki stream GRES10 Waipiro stream at Te Puia

GRES11 Kouetumata stream at Ihungia Rd

GRES13 Makomuka stream at SH35

GRES14 Anaura stream at Anaura Bay Rd

GRES15 Waipaoa River at Armstrong rd

11

GRES16 Pakarae river at Whakaauranga

Bridge

GRES 17 Waikohu River at Oliver rd

GRES 17 Kaitawa stream

GRES19 Waikohu Trib at Whakarau Rd

12

GRES20 Waihuka River at No3 Bridge

GRES21 Waikohu River at No3 Bridge

GRES22 Urumiti Stream at Holdsworth Br SH2 GRES23 Waihuka Stream at No2 Bridge

GRES24 Mangaoai Stream at Mangaoai Rd

GRES25 Pakarae Trib at Whangara Rd

13

GRES26 Te Arai trib

GRES 27 Pakarae Trib at Stevens Rd

GRES28 Wharekopae River above falls

GRES29 Waikirikiri Stream at Quarry

GRES30 Maraetaha Stream at No2 Bridge

GRES 31 Haupapa Stream at Tahora

settlement Rd

14

GRES32 Mangaotara Stream at Tiniroto rd

GRES33 Upper Motu Trib at Marumoko Rd

GRES43 Marumoko Stream at Marumoko Rd

GRES36 Koranga Trib at Rakauroa Rd

GRES37 Lottin point Rd Stream

GRES 38 Karakatuwhero Trib

15

GRES39 Whangaparoa Stream at Waikura Rd

GRES40 Mangaoporo River at Mangaoporo

Rd

GRES41 Waitekaha Stream at Tuparoa Rd

GRES42 Mangaehu Stream at Marshall Rd

GRES44 Waipaoa Trib at Pipiwhakao Rd

GRES45 Te Arai Trib at Waugh Rd

16

GRES46 Te Arai River at Waingake

GRES47 Mangakino Stream at

Mangatokerau rd

GRES48 Koranga River at Koranga Valley rd

GRES49 Papokeka Stream at Pehiri

GRES50 Whakarau trib at Whakarau Rd

GRES 51 Motu River at Kotare Station

17

GRES52 Motu Conservation Area

GRES53 Wharekahika Upstream of Bridge

GRES54 Mangatutu Stream at Wi Pahuru

Bridge

GRES55 Oweka River at SH35 Bridge

GRES 56 Karakatuwhero River at SH35 bridge GRES57 Awatere River at SH35 Bridge

18

GRES58 Waiapu River at Rotokautuku GRES59 Poroporo River at Rangitukia Bridge

GRES60 Mangaoporo river at Tutumatai

Bridge

GRES61 Mata River at Pouturu Bridge

GRES62 Mata River at Aorangi Bridge GRES63 Ihungia River at Ihungia Rd

19

GRES64 Hikuwai River at Willowflat Bridge GRES65 Hikuwai River at No4 Bridge

GRES66 Mangaheia River at Paroa Rd Bridge

GRES 67 Waihirere Stream at Domain

GRES69 Wainui Stream at Heath Johnston

Park

GRES70 Waimata River at Goodwins Rd

Bridge

20

GRES71 Waimata River at Monowai Bridge

GRES72 Taruheru River at Tucker Rd

GRES 74 Waipaoa River at Kanakanaia Bridge GRES75 Waipaoa River at Matawhero

Bridge

GRES 76 Motu River above Falls

GRES77 Te Arai River at Pykes Weir

21

GRES78 Whakaahu River at Brunton Rd

GRES79 Waikohu river at Mahaki

GRES80 Wharekopae River at Rangimoe

Bridge

GRES81 Mangatu River at Omapare

GRES82 Waingaromia River at Terrace Station

GRES83 Pakarae River at Pakarae Rd bridge

22

GRES84 Matawai Stream at Tawai

GRES 85 Makahakaha Stream

GRES 86 Te Arai River at Intake Weir GRES89 Upper Mata River

GRES90 Mangaokura Stream

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Overview of Aquatic Monitoring Programme

Stream monitoring

Macroinvertebrates have been collected annually at 81 sites from around the Gisborne region

since the Austral summer of 2015. Macroinvertebrates include larval stages of insects, molluscs,

crustaceans and worms and are used nationally and internationally to measure water quality

and the ecological condition of streams. Stream invertebrates are a vital component to food

webs in waterways and provide ecological functions including consuming plant and woody

material instream, are predated on and provide food to fish, birds and other insects. They are

sensitive to pollution and show a range of responses to chemical, physical and hydrological

conditions over long periods of time (Stark 1985, Stark and Maxted 2007, Rosenberg and Resh

1993).

Macroinvertebrates are much less mobile than fish, are relatively long lived and can occur in

high abundances. The relatively straight forward identification of macroinvertebrates and their

known ecological tolerances means that they can be used as an environmental indicator of

the ecological condition of a stream (Rosenberg and Resh 1993).

Compared to chemical water testing, (where water samples are taken at one point in time for

things such as pH, temperature, dissolved oxygen, conductivity and nutrients) stream

invertebrates live in the waterway and have to tolerate the conditions present. A one off test

could miss a particular contaminant, however the effects on stream invertebrates can be seen

for days or weeks following an event. As the ecological condition of a waterway starts to

decrease, there is a loss of sensitive species such as mayflies, stoneflies and caddisflies

(Ephemeroptera, Plecoptera, Trichoptera (EPT)) and an increase in more pollution tolerant

species such as snails, chironomids and worms. A loss of EPT taxa results in less biodiversity

within the stream, and a reduction in food for animals higher in the food chain such as fish,

birds and terrestrial insects (Hall et.al 2001). Measuring invertebrates help explain the effects

from point source discharges, diffuse discharges, urbanisation, agricultural and silviculture

activities. Macroinvertebrate monitoring is used in all regions in New Zealand by regional

councils for SOE monitoring.

Methods

Monitoring sites

Sites were chosen using a random selection protocol that included land use, source of flow,

geology, stream order and climate from the River Environment Classification (REC) system

(Snelder and Biggs 2002). Sites were selected near a road intersection and added to the

current monthly SOE water chemistry site network of 33 freshwater sites. This resulted in a

network of 81 annually sampled biomonitoring sites throughout the region (48 new sites and 33

existing monthly SOE sites). There are four geology types present in the Gisborne region, and

sites were monitored in all geology types. 1 Aluvium, 14 Hard Sedimentary, 59 Soft Sedimentary

and 7 Volcanic Acidic sites were monitored.

The REC spatial layer is based on a digital elevation model that shows the location of

waterways, built along valleys and uses a NZReach number code to define river sections. The

NZReach number was used for each site and linked to the Freshwater Environments of New

Zealand (FENZ) database to provide data on environmental factors such as elevation,

distance to sea, rocks rich in calcium etc. The Landcover was set for each site using Larned

24

et.al (2017) and the classifications used were pasture, exotic forestry, urban, indigenous forest

and cropland.

Invertebrate Sampling and Processing

All sites are monitored annually between the months of December and April during low flow

conditions. There is a stand down period of ten days following large floods where the

streambed has been mobilised (3 times the median flow). The sites monitored include both

wadeable hard bottomed streams with stony beds and wadeable soft bottomed streams

dominated by silt and sand. Streams drying or flooding prevented sample collection

occasionally (212 samples were taken over the three year period).

Macroinvertebrate C1 protocol (Stark et.al 2001) slightly modified is used for collecting

macroinvertebrate samples in hard bottomed streams. Invertebrates were sampled from all

habitats within the stream over a 100 m reach using a kick net and dislodging the streambed

material upstream of the net and collecting all dislodged material in the net. This differs from

the C1 protocol as all habitats were sampled not just riffles. The C2 protocol (Stark et al 2001)

is used for soft bottomed streams, where woody debris, macrophytes and other invertebrate

habitat was sampled in proportion to its percentage of occurrence over the 100m reach.

Samples are collected in 0.5 mm mesh net (305 mm 204 mm net opening), sieved and

preserved with 70% IPA in the field. Only one pooled sample at each site is collected, which is

about 1m2 of habitat sampled. Proportions of each habitat type sampled for

macroinvertebrates were recorded e.g wood, stones, edges etc.

Samples were processed using protocol P2 (Stark et al. 2001) by Stark Environmental Ltd, using

the fixed 200 count and scan for rare taxa method (Duggan et al 2002). The number of

different types of mayflies, Stoneflies and Caddisflies (EPT) are given as a percentage of

abundance (%EPT). A macroinvertebrate community index (MCI or sbMCI) was calculated for

each site. EPT refers to the sensitive groups Ephemeroptera (mayflies), Plecoptera (stoneflies)

and Trichoptera (caddisflies). A quality assurance protocol involved 10% of samples being

randomly selected and sent for processing by another taxonomist every three years.

Habitat and Periphyton sampling

Qualitative assessments of habitat were conducted at each site using the Rapid Habitat

Assessment Protocol (Clapcott 2015) for the 100m reach sampled. Habitat quality scores are

based on deposited sediment, invertebrate habitat abundance, invertebrate habitat diversity,

fish cover diversity, fish cover abundance, hydraulic heterogeneity, bank erosion, bank

vegetation, riparian width and riparian shade (Appendix A). These are added together

resulting in a score out of 100 for each site.

In-situ water quality measurements using a YSI ProDSS multiparameter water quality metre (pH,

Dissolved Oxygen %, Dissolved Oxygen mg/l, conductivity, salinity, turbidity, and temperature)

were taken during sampling at each site.

Periphyton assessments are conducted using a modification of the RAM-2 protocol (Biggs and

Kilroy 2000), 20 visual assessments are conducted at each site using a viewer and measuring

percent cover on the stream bed using the SHMAK enrichment categories, the number of

transects is dependent on stream width (<5m wide = 4 transects, 5-10m = 3 transects, 10-20m

= 2 transects, >20m = 1 transect).

Embeddedness was subjectively assessed as loose, good, moderate or tightly packed. Flow

conditions were observed as ambient, elevated or below ambient.

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Biological Indices

The Macroinvertebrate Community Index (MCI) was developed by Stark (1985) for assessing

organic enrichment of stony hard bottomed streams (Table 3), in 2007 Stark and Maxted

developed a soft bottomed MCI (MCI-sb) for streams that are naturally soft bottomed. The

MCI relies on prior allocation of scores (between 1 and 10) to taxa based on their tolerance of

organic enrichment. Taxa that are characteristic of unenriched conditions score highly (10)

compared to taxa tolerant to pollution with low scores (1). MCI scores shown in Table 3 show

the interpretation of MCI values.

Table 3: Interpretation of QMCI and MCI values (Stark and Maxted 2007)

Mean metric scores were calculated over the three years’ worth of data and compare against

water quality classes in Stark and Maxted (2007). Stark and Maxted (2007) note that metrics

should be interpreted with ‘fuzzy’ boundaries with a margin of ±5 for MCI thresholds. It is also

noted that the MCI metric were designed to measure nutrient enrichment so some

environmental variables such as sediment may not be adequately assessed (Stark and Maxted

2007, Boothroyd and Stark 2000).

The Quantitative Macroinvertebrate Index (QMCI) is similar to the MCI but also takes into

account the number of individuals of each species collected. The QMCI uses densities and is

not sensitive to finding taxa only represented by one or two animals. Species can reach very

high densities indicating environmental stress.

The percentage of pollution sensitive taxa Ephemeroptera (mayflies), Plecoptera (stoneflies)

and Trichoptera (caddisflies) (%EPT) taxa is calculated as a proportion of these sensitive taxa

being present. A score of 100% would indicate that all of the animals collected belonged to

the pollution sensitive taxa, and would be a very healthy stream. As the %EPT decreases, there

are less of these sensitive groups present indicating the waterway would be polluted and not

suitable habitat for the pollution sensitive taxa. %EPT taxa is calculated by dividing the number

of EPT taxa by the total number of taxa identified in the sample. %EPT abundance is calculated

by dividing the number of EPT individuals by the total macroinvertebrate count for the sample.

Both %EPT taxa and % EPT abundance exclude caddisfly taxa Oxytheria and Paroxyethira as

they are relatively insensitive to pollution.

QMCI MCI Score Quality

Class

Description

♦>6.00 ♦ >119 Excellent Clean

water

♦ 5-5.99 ♦ 100-119 Good

Possible

mild

pollution

♦ 4-4.99 ♦ 80-99 Fair

Probable

mild

pollution

♦ <4.00 ♦ <80 Poor

Probable

severe

pollution

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Statistical analysis

Analysis of Variance was used in R (Version 3.5) to test whether land use or geology affected

MCI and the other metrics. And whether this differed between years. NMDS Ordination analysis

was performed in Primer version 7.0.

Results

Summary of physical conditions

Sites range from first order streams, such as the Motu conservation site (GRES52) and Upper

Mata (GRES89) with cobble and boulder dominated substrate, to seventh order rivers such as

the Waipaoa at Kanakanaia (GRES74) and the Waiapu at Rotokautuku (GRES58). Sites also

include lowland streams such as the Taruheru River at Tucker Rd (GRES72) and Whakaahu

stream (GRES78) which are dominated by silt, sand and clay substrate. Many of the streams

monitored are located in soft sedimentary geology (61 sites), this includes the Te Arai River at

Intake (GRES86) and Waihirere stream (GRES67) which are also reference sites.

The Waipaoa, Waimata, Uawa, Waiapu, and Motu which are the major catchments in the

region are represented by multiple sites on their main stem and tributaries. The 81 sites that are

monitored include sites in stream orders 1 through to 7 (Table 4).

Macroinvertebrate metrics

Biological metrics are presented in Table 4 along with the corresponding REC Land Use and

Geology classification for each site, Figure 6 shows MCI scores for sites by location. Mean MCI

scores ranged from 48 (Taruheru River at Tucker Rd GRES72) to 141 (Mata Upper GRES89),

highlighting a range of ecological health throughout catchments. The sites that had the lowest

two MCI scores are known to be occasionally influenced by tidal backflow. The MCI was not

designed for estuarine influence so it is worth noting that this may explain the low scores. The

next lowest score was Kaitawa stream at wharf rd. (GRES18) with a score of 52.

The MCI values indicated that 12% of sites had excellent water quality and 17% had poor

water quality and with an MCI of less than 80 (Figure 3). Thirty seven percent of the 81 sites had

MCI indicating good water quality. This included two of the reference sites Te Arai River at

Intake (GRES86) and Waihirere stream (GRES67) that are located in soft sedimentary geology,

32% of the sites were classified as fair. Figure 6 shows the sites in the poor MCI classification are

all located in lowland areas of the Poverty Bay flats or at the bottom of catchments closer to

the coast. Sites in the excellent categories are located higher up in the catchments near the

headwaters and above most anthropogenic land use activities.

QMCI values indicated that 18% of sites had excellent water quality and 21% had poor water

quality with 17% good and 22% fair water quality (Figure 5).

The sites that were in the excellent category were located in either Indigenous forest or mature

Exotic Forestry with one site being in Pasture. The sites in the poor category were located in a

mixture of Pasture, Urban and Cropping and had a mixture of hard and soft bottom

classification.

Mangaokura stream (GRES90) has the highest % of EPT taxa with 63% comprised of mayflies,

stoneflies and caddisflies. Mata Upper (GRES89) and Huitatariki stream (GRES9) also have

high %EPT taxa of 61% and 60% respectively. Pakarae River at Pakarae Station (GRES83),

27

Taruheru River at Tucker rd (GRES72) and Waipaoa trib (GRES44) all had no EPT taxa present

(Figure 2).

Mangaoporo river at Tutumatai Bridge (GRES60) had the highest number of %EPT abundance,

with 92% of individuals being mayflies, stoneflies or caddisflies, Huitatariki stream (GRES9)

(located in exotic forestry) had 90% of individuals in the EPT group, and Mata Upper (GRES89)

had 85% (Table 4). The mean number of taxa ranged from 35 (Koranga Trib at Rakauroa rd

GRES36) to 9 at Mangaoporo River at Mangaoporo Rd (GRES40) (Figure 3).

Table 4. Mean MCI, QMCI, %EPT taxa and %EPT abundance for the 81 sites sampled from 2015-2018.

Green is excellent water quality, Blue is good, Orange fair and Red is poor water quality.

SITE ID Site Name Land

use Geology

Stream

Order MCI QMCI

%EPT

taxa

%EPT

abundance

GRES 1 Kopuapunamu Str Trib at Te

Araroa P SS

2 111 5.8 45.4 53.6

GRES 2 Waipaoa Trib at Lavenham-

Humphrey Rd P SS

3 72 2.6 13.0 3.3

GRES 3 Parihihonou Str at SH2

Overbridge P SS

3 111 5.3 44.7 57.8

GRES 6 Waiau River at Tauwhareparae EF SS 4 90 4.5 25.0 13.9

GRES 7 Makarika Str at Keelan Rd EF HS 4 90 4.3 11.8 8.3

GRES 8 Mangatu Trib EF HS 2 120 4.8 46.0 41.3

GRES 9 Huitatariki Str EF HS 3 131 7.9 59.5 90.5

GRES

10 Waipiro Str at Te Puia P SS

3 86 4.1 15.6 12.1

GRES

11 Kouetumara Str at Ihungia Rd EF SS

2 107 5.6 35.1 39.6

GRES

13 Makokomuka Str at Anaura Rd P SS

2 103 4.8 38.3 25.3

GRES

14 Anaura Str at Anaura Bay Rd P SS

2 112 4.3 50.5 9.2

GRES

15 Waipaoa at Armstrong Rd EF HS

5 96 4.1 26.7 15.5

GRES

16

Whakauranga Br at West Ho

Rd EF SS

4 109 6 51.6 78.2

GRES

17 Waikohu Rv at Oliver Rd P SS

4 112 5.4 43.8 60.3

GRES

18 Kaitawa Str at Wharf Rd P SS

4 52 3.8 4.5 0.4

GRES

19

Waikohu trib @ Whakarau

Road P SS

3 82 4 7.7 1.1

GRES

20 Waihuka River at No.3 Br P SS

4 82 4 17.4 4.1

GRES

21 Waikohu River at No.3 Br P SS

6 79 3.9 17.3 5.1

GRES

22 Kurunui Str at Holdsworth Br SH2 P SS

3 55 3.9 6.3 0.8

GRES

23 Waihuka at No2 Br P SS

4 96 4.8 39.2 56.8

GRES

24 Mangaoai Str at Mangaoai Rd EF SS

4 103 4.7 48.4 48.8

GRES

25 Pakarae Trib at Whangara Rd P SS

2 76 3.8 15.0 1.3

GRES

26 Te Arai Trib at Waingake Rd EF SS

3 90 4 26.8 7.4

GRES

27 Pakarae trib Stevens Road P SS

3 86 3.9 18.7 2.2

GRES

28 Wharekopae above falls P SS

4 93 4.3 31.3 15.0

28

GRES

29 Waikakariki Trib at Quarry P SS

2 94 4.3 23.2 4.0

GRES

30 Maraetaha Str at No2 Br P SS

4 58 2.6 12.1 1.9

GRES

31

Haupapa Str at Tahora

Settlement Rd P VA

2 114 5.3 45.9 48.5

GRES

32 Mangaotara Str at Tiniroto Rd P SS

2 118 6.2 57.2 79.6

GRES

33 Upper Motu Trib at Mangatu IF HS

2 121 5.9 42.6 49.8

GRES

34 Marumoko Str at Marumoko Rd P HS

5 120 6.4 46.8 54.8

GRES

36 Koranga Trib at Rakauroa Rd IF VA

2 124 6.7 49.2 64.1

GRES

37 Lottin Point Road Stream P VA

2 113 6 44.1 49.0

GRES

38

Karakatuwhero Trib at

Karakatuwhero Rd EF SS

3 111 5.2 41.5 36.9

GRES

39

Whangaparoa Trib at Waikura

Road P HS

3 99 6 29.6 52.4

GRES

40

Mangaoparo River at

Mangaoparo Road EF HS

4 101 5.1 34.0 41.7

GRES

41 Waitekaha Str at Tuparoa Rd P SS

3 104 6 31.4 49.1

GRES

42

Mangaehu Stream at Marshall

road P HS

3 91 2.6 27.7 8.4

GRES

44

Waipaoa Trib at Pipiwhakao

Road C SS

3 57 2.6 0.0 0.0

GRES

45 Te Arai Trib at Waugh Rd P SS

2 81 3.9 13.6 1.5

GRES

46 Te Arai Rv at Waingake P SS

3 91 4.1 32.0 31.5

GRES

47

Mangakino Str at

Mangatokerau Rd IF SS

2 112 4.7 40.4 50.5

GRES

48

Koranga Rv at Koranga Valley

Rd P VA

2 119 6.1 50.9 63.5

GRES

49 Papokeka Str at Pehiri P SS

4 115 5.4 51.4 52.4

GRES

50 Whakarau Trib at Whakarau Rd P SS

2 110 5.6 39.5 53.5

GRES

51

Motu River at Kotare Station

Bridge P VA

2 118 6 49.4 58.1

GRES

52

Motu River @ Matawai Conserv

Area IF SS

1 129 7.2 54.1 58.5

GRES

53

Wharekahika River U/S of

Wharf Bridge P SS

5 110 6.2 42.9 60.0

GRES

54

Mangatutu Str at Sh35-

Waipahuru Bridge IF VA

3 126 6 50.2 57.2

GRES

55 Oweka River at SH35 Bridge P SS

4 110 5.8 40.9 59.9

GRES

56 Karakatuwhero River at SH35 Br IF VA

4 105 7.1 42.8 80.1

GRES

57 Awatere River at SH35 Bridge EF HS

5 105 6.3 48.2 66.8

GRES

58

Waiapu River at Rotokautuku

Br (SH35) P HS

6 102 5.8 35.1 52.0

GRES

59

Poroporo River at Rangitukia

Rd Bridge P SS

4 105 5.5 26.1 37.5

GRES

60

Mangaoporo River at

Tutamatai Bridge P HS

4 96 7.4 35.7 91.5

GRES

61 Mata River at Pouturu Br P SS

6 90 5.4 23.4 40.1

GRES

62

Mata River at Aorangi

(Makarika Road) P Al

6 108 5.8 43.2 62.6

29

GRES

63 Ihungia River at Ihungia Rd Br P SS

5 90 4.2 23.6 9.5

GRES

64 Hikuwai River at Willowflat P SS

5 85 2.6 29.1 9.1

GRES

65 Hikuwai River at No 4 Bridge P SS

5 82 3.8 11.6 1.4

GRES

66

Mangaheia River at Paroa

Road Bridge P SS

5 69 3.9 3.7 0.5

GRES

67 Waihirere Str at Domain IF SS

2 111 5.8 48.1 58.2

GRES

69

Wainui Str at Heath Johnston

Park U SS

1 75 2.6 5.8 0.5

GRES

70

Waimata River at Goodwins Rd

Bridge P SS

5 76 2.6 15.7 2.7

GRES

71

Waimata River at Monowai

Bridge P SS

4 92 4.1 35.4 31.9

GRES

72

Taruheru River at Tuckers Rd

Bridge P SS

2 48 2.6 0.0 0.0

GRES

74 Waipaoa River at Kanakanaia P SS

7 80 3.9 15.2 2.3

GRES

75

Waipaoa River at Matawhero

Bridge P SS

7 69 2.6 17.9 3.8

GRES

76 Motu River above Falls P SS

5 112 4.3 51.7 41.9

GRES

77 Te Arai River at Pykes Weir P SS

4 91 4.1 32.8 14.3

GRES

78 Whakaahu Str at Brunton Rd P SS

5 67 3.9 10.7 1.1

GRES

79

Waikohu River at Mahaki

Station P SS

5 104 4.8 45.8 58.1

GRES

80

Wharekopae River at

Rangimoe P SS

6 104 4.8 54.9 31.9

GRES

81

Mangatu River at Omapere

Station P SS

5 99 5.5 32.3 60.3

GRES

82

Waingaromia River at Terrace

Station P SS

5 83 3.9 22.1 2.6

GRES

83

Pakarae River at Pakarae

Station Bridge P SS

5 48 3.8 0.0 0.0

GRES

84 Matawai Stream at Tawai P SS

2 98 5.4 30.1 51.1

GRES

85 Makahakaha Stream EF SS 2 98 4.4 32.6 19.5

GRES

86

Te Arai River at DW Bush Intake

Above Weir IF SS

3 119 6 48.8 70.6

GRES

89 Mata Upper IF HS

2 141 8.1 60.8 85.0

GRES

90 Mangaokura Stream IF HS

4 135 7.9 62.5 77.9

30

Figure 2. Mean %EPT taxa for 81 sites in the Gisborne region from 2015-2018.

31

Figure 3. Mean MCI for 81 sites in the Gisborne region from 2015-2018. Above green line = Excellent, above blue line = Good, below blue line= Fair and below red

line=Poor.

32

Figure 4. Mean %EPT Abundance for 81 sites in the Gisborne region from 2015-2018.

33

Figure 5. Mean QMCI for 81 sites in the Gisborne region from 2015-2018. Above green line = Excellent, above blue line = Good, below blue line= Fair and below red line=Poor.

34

Figure 6. Mean MCI scores at 81 sites in the Gisborne region from 2015-2018, showing sites with Excellent,

Good, Fair and poor water quality classifications. Sites with triangles, indicate reference sites.

35

The link between land use, geology and water quality

There were five land use types measured within the SOE biomonitoring programme;

iIndigenous forest, Exotic forest, pasture, urban and cropland.

MCI was higher in indigenous forest (highest MCI = 144) land use as was QMCI, %EPT taxa

and %EPT abundance (Table 5). All three years sampling showed the same pattern with

indigenous forest and some exotic forest sites supporting excellent MCI scores and

consequently there was no interaction between land use and year. All four metrics (MCI,

QMCI, %EPT taxa and %EPT abundance) are influenced by the hard or soft bottomed substrate

and have a significant difference (Table 5), (MCI F2,193=51.99 P=<0.001). Pasture and Exotic

forest did not have a significant difference between geology types, suggesting the geology

type is not influencing the macroinvertebrate communities, land use is influencing the stream

health rather than the geology.

Land use and geology both have significant effects on all four metrics (MCI, QMCI, %EPT

taxa, %EPT richness) but there is no interaction between land use and geology. This suggests

that they both influence the macroinvertebrate community individually but there is no

interaction between the land use and the geology.

The invertebrate community composition was different across all metrics between exotic forest

and indigenous forest land use. This was different to previous studies that have shown that

mature exotic forest can support the same macroinvertebrate communities as indigenous

forest.

Indigenous forest (IF) had the highest MCI scores (highest= 141, mean =120) and pasture (P)

sites had the lowest (lowest=48, mean=95) (Figure 7) with sites in all four stream health

categories (poor, fair, good, excellent).

QMCI results showed that indigenous forest sites had a higher median compared to all other

land uses. Pasture had the biggest range of QMCI, and exotic forest had sites in fair, good and

excellent water quality categories (Figure 8).

Table 5. Analysis of Variance results for macroinvertebrate metrics (MCI, QMCI, %EPT taxa, %EPT

abundance) from 2015-2018 using Indigenous Forest, Exotic Forest and Pastural land use and hard or soft

benthic substrates for stream geology. Significant values are in bold (P < 0.05 = significant)

MCI QMCI %EPT taxa %EPT abundance

df1 df2 F P F P F P F P

Landuse 2 193 38.30 <0.001 27.69 <0.001 22.74 <0.001 18.40 <0.001

Geology 1 193 51.99 <0.001 28.47 <0.001 60.98 <0.001 29.70 <0.001

Year 2 193 1.28 0.28 0.92 0.40 1.69 0.19 1.26 0.29

Landuse*Geology 1 193 0.27 0.61 1.14 0.29 3.31 0.07 1.24 0.27

Landuse*Year 4 193 0.70 0.59 1.83 0.12 0.35 0.85 0.90 0.47

Geology*Year 2 193 0.38 0.68 0.30 0.74 0.64 0.53 0.18 0.84

Landuse*Geology*Year 4 193 0.13 0.88 0.41 0.66 0.17 0.85 0.41 0.66

36

Figure 8. Boxplot of MCI values from 81 sites in Gisborne 2015-2018 and Land use. Cropland (C), Exotic

Forest (EF), Indigenous Forest (IF), Pastoral (P), and Urban (U). Percentiles; boxes = 25% and 75%; Horizontal

bars=5% and 90%; closed circles =5% and 95% (for classes with >10 sites).

MCI was influenced by the different geology types (F4,199=4.95, P<0.001) but there was no

significant interaction between geology type and year (F6,199=0.49 P=0.05). Figure 9 shows that

soft sedimentary geology has the lowest MCI values (mean MCI= 52 Kaitawa Stream GRES18)

Figure 7. Boxplot of MCI values from 81 sites in Gisborne 2015-2018 and Land use. Cropland (C), Exotic

Forest (EF), Indigenous Forest (IF), Pastoral (P), and Urban (U). Percentiles; boxes = 25% and 75%; Horizontal

bars=5% and 90%; closed circles =5% and 95% (for classes with >10 sites).

37

and hard sedimentary geology has the highest MCI values (mean MCI=144 Mangaokura River

GRES90) in the region. Volcanic acidic geology supports a higher mean MCI (116) compared

to the other three geologies (Hard Sedimentary=110, Alluvium=108, Soft Sedimentary=94).

Figure 9. MCI values plotted against 4 Geology types within the Gisborne region Aluvium (AL), Hard

Sedimentary (HS), Soft Sedimentary (SS) and Volcanic Acidic (VA). Percentiles; boxes = 25% and 75%;

Horizontal bars=5% and 90%; closed circles =5% and 95% (for classes with >10 sites).

The geology and land use in the Gisborne region results in large amounts of deposited

sediment in some rivers. Deposited sediment and MCI were related (F1,208=34.39, P<0.001),

when deposited sediment increased, there was a decrease in MCI values (Figure 10). Urban,

pasture and exotic forest have the highest mean deposited sediment values (2.6, 4.2 and 4.9

respectively) and indigenous forest has the lowest levels of deposited sediment (7.1).

Figure 10. MCI plotted against deposited sediment for the Gisborne data collected from

2015-2018 (F1,208=34.39, P<0.001), deposited sediment cover decreases from 0-10.

38

As conductivity increases the MCI declines ( ) (F1,206=87.39 P<0.0001). Figure 12 shows there is a

range of levels of conductivities between land use, with indigenous forest having the lowest

median levels over the three years of sampling. Conductivity levels in the pastoral land use

have a range from 8µs/cm-1 to 1562µs/cm-1, compared to that in indigenous forest with a 64.9

µs/cm-1 to 625 µs/cm-1. Exotic forest has a higher median conductivity (561 µs/cm) over the

2015-2018 period compare to pasture (447 µs/cm) of indigenous forest (166 µs/cm). It is worth

noting that all stages of exotic forestry are in this category from mature through to recently

harvested.

Figure 11 MCI plotted as a function of conductivity (µs/cm-1) for samples collected in the Gisborne region

between 2015-2018 (F1,206=87.39 P<0.001, R2=0.29).

39

Figure 12. Boxplot of conductivity measures plotted in land use category (Cropland(C), Exotic Forest (EF),

Indigenous Forest (IF), Pastoral (P), and Urban (U)). Percentiles; boxes = 25% and 75%; Horizontal bars=5%

and 90% closed circles =5% and 95% (for classes with >10 sites).

Invertebrate communities

A total of 140 invertebrate taxa were collected in the 81 sites over the three years of sampling.

The fauna was numerically dominated by the common freshwater snail (Potamopyrgus

antipodarum), mayfly (Deleatidium), chironomid midge (Tanyarsus and Tanyponidae), worm

(Oligochaeta) and caddisfly (Aoteapsyche). Nineteen taxa were found to have relative

abundances greater than 1%. Potamopyrgus the most common taxa at all sites were found at

the 81 sites over the three year period. No one taxa was found at all sites.

The NMDS ordination of all invertebrate data over the 2015-2018 period had a low stress level

of 0.188, indicating a strong difference in invertebrate community composition across the

region, even though there was a core set of taxa that dominated samples.

40

Figure 13. Results of NMDS plot of the communities of all data collected at all 81 sites over 2015-2018

The two environmental variables that had the strongest positive correlation to

macroinvertebrate community composition were Upstream calcium (rs=0.67) and conductivity

(rs=0.57) (Figure 14). Salinity (rs=0.48) and Ecoli (rs=0.47) were also strongly correlated. The

strongest negatively correlated variables were Invertebrate habitat abundance (rs= -0.64),

Upstream rain (rs= -0.61), and Upstream native (rs= -0.55). The strong positive correlations with

conductivity and US calcium relate to the large effect of the soft geology type found on the

East Coast. Invertebrate habitat abundance, US rain and US native were strongly negatively

correlated with macroinvertebrate communities, as most of the sites are located in modified

land uses that do not have large areas of upstream indigenous forest, have low habitat

abundance and low amounts of rainfall.

41

Figure 14. NMDS ordination of macroinvertebrate community composition based on taxa abundance at

each 81 sites from samples from 2015-2018. Environmental variables with a Spearman Rank correlation

coefficient greater than rs=0.55 are shown by the vectors overlaid.

Discussion

This is the first analysis of ecological data collected in the state of the environment monitoring

programme in Gisborne. Three years is too short an interval to evaluate trends in time but

ecological state across the region was assessed.

The waterways surveyed ranged from small streams to 7th order rivers so covered a range of

stream types and catchment sizes. Rivers that are in small catchments have a stronger

interaction with riparian conditions compared to larger rivers (Ministry for the Environment 2001)

such that surrounding land use in smaller catchments has the potential to have a greater

impact. The sites surveyed also included a range of land use types from indigenous forest to

intensive land use. Unfortunately there are minimal reference sites in the lowland areas of

Gisborne, with only one site in the lowland area that is used as a reference site (Waihirere

stream GRES67).

Analysis of the SOE programme of 81 sites over the period 2015-2018 found the following:

Fourteen (17%) sites were considered of poor health (NPS-FM ‘D’ band) from the MCI

and 20 sites (21%) were in the poor category based on the QMCI. These sites were

mainly located in more intensive land use areas near the Poverty Bay flats or at the

bottom of catchments close to the coast.

The reference site Waihirere stream (GRES67) was in the ‘Good’ water quality category

for both QMCI and MCI. Te Arai intake Weir (GRES86) was classified in the ‘Good’

category based on the MCI but in the ‘Excellent’ category for the QMCI.

Extreme differences were found between the QMCI and MCI at two sites Mangaoporo

River at Tutumatai Bridge (GRES60); where QMCI indicated ‘Excellent’ health and MCI

42

indicated ‘Fair’ health, and Mangatu Trib (GRES8), where QMCI indicated ‘Fair’ and

MCI indicated ‘Excellent’ water quality.

A total of 139 different taxa were found across all sites and the sites that had the most

diverse assemblages were found in indigenous and exotic forest sites. The sites that had

the least diversity were located in lowland cropland or pastoral sites, and supported

few to no EPT taxa.

Deposited sediment influenced the MCI scores, at sites with higher deposited sediment

levels there were lower MCI scores.

Upstream calcium and conductivity are major drivers of macroinvertebrate

community composition in the Gisborne region.

Macroinvertebrate community composition differed between sites depending on the

land use and geology.

Land use and geology influence the macroinvertebrate community, but the impact of

land use does not differ between different geology types.

Agriculture and forestry can both have negative impacts on freshwater ecosystems. Forest

harvesting operations can provide large contributions of sediment to freshwater systems,

through earthworks (roads, landings, hauling), streambank erosion and landslides following

tree removal, a change in vegetative cover and an increase in water runoff (Quinn and Phillips

2016). Retention of riparian buffers can assist with improving stream health by regulating

temperature, sediment inputs and stream disturbance during harvest (Thompson et.al 2009,

Death 2017). In Gisborne, exotic forest was planted extensively following Cyclone Bola, where

large areas of pastoral land were planted in trees. In most cases, there were no riparian zones

or riparian zones were cut down to plant trees right to the edge of the waterway. While some

studies have shown invertebrate communities can recover from forest harvesting within 8 years

(Reid et al 2010) high levels of deposited fine sediment can slow that recovery (Quinn and

Phillips 2016). However, while the forest is in its first rotation following pastoral land use, before

harvest, macroinvertebrate communities indicating excellent water quality can be supported.

This was shown in streams located in indigenous and exotic forests both having excellent water

quality (Huitatariki stream GRES9, Mangatu Trib GRES8). In some areas in New Zealand it has

been shown that indigenous forest and exotic forest can support the same macroinvertebrate

communities (Townsend et.al 1997). This was not the case in Gisborne and there was a

difference in macroinvertebrate community composition between exotic and indigenous

forest.

Interestingly the monitoring indicated a significant relationship between deposited sediment

and macroinvertebrate communities, as well as conductivity and upstream calcium were

shown to have a significant influences. The increasing conductivities resulted in decreasing

macroinvertebrate metrics with the soft geology type and eroding landscape common in the

Gisborne region. The influence of US calcium and conductivity on macroinvertebrate

communities reflects the continual erosion and exposure of fresh rock that is contributing to

the suspended sediment loads and high conductivity levels found in Gisborne rivers (Parkyn

et.al 2006). Omento et.al (2000) found that instream conductivity was strongly correlated with

land use, and land use is potentially also correlated with land use in Gisborne. Land use has a

direct influence on macroinvertebrate communities. The sites with the highest conductivities

were found in pasture or exotic forest land uses (Makarika stream GRES7, Mangaehu Stream

at Marshall Road GRES42, Pangopango Stream GRES6, Te Arai trib at Waingake Road GRES26)

and supported MCI scores in the ‘Poor’ or ‘Fair’ category.

43

Agriculture is the dominant land use in the Gisborne region (Stats NZ 2012) and is predominantly

high country extensive sheep and beef farming. Agriculture can influence freshwater

ecosystems through changes in water yields, soil structure, contaminants, increased erosion

and sedimentation of waterways. Gisborne has a large area of erodible land in agricultural

land use and this results in sediment input into waterways through overland flow (Scarsbrook

et al. 2016). There was a mixture of pastoral land use through all categories (Excellent, Good,

Fair, Poor) but were dominated by sites of fair quality (24 out of the 74 Pastoral sites). This is

potentially due to the amount of erosion in the catchment and inputs of sediment that

influence the conductivity levels. Deposited sediment levels in the pastoral land were highly

variable from high deposited sediment to very low levels. It is unclear why this is the case at this

stage, but the spread of geology type (soft sediment, hard sedimentary and volcanic acidic)

through the pastoral land use sites could be influencing sediment loads coupled with on farm

practices.

Macroinvertebrate health is linked to upstream land cover. All sites that were in the excellent

category were located in indigenous or exotic forest high up in the headwaters of catchments.

The sites that had poor health were located in cropping, urban or pastoral Land cover. Land

use effects MCI and there is no change between years in different land uses. This supports the

idea that land use is driving community change in macroinvertebrates and the differences in

seasons or conditions on an annual basis does not have an influence on communities.

The stream bed substrate (soft or hard bottomed) also has a strong effect on

macroinvertebrate health across all metrics (MCI, QMCI, %EPT taxa and %EPT abundance). All

sites in the excellent category were found where there is hard bottomed substrate in the river.

Soft bottomed substrate supported MCI categories from ‘poor’ to ‘fair’ with three sites in ‘good’

water quality.

The ordination analysis showed that the two highest drivers for macroinvertebrate communities

were US calcium and conductivity. Conductivity reflects the amount of dissolved ions in the

water, and the erodible rock type in Gisborne results in high levels of conductivity. Both these

environmental variable are linked to the soft sedimentary geology type that is found on the

East Coast (Hem 1985). US native, invertebrate habitat abundance and USdays rain had a

strong negative correlation with the invertebrate communities found and this reflects that sites

in the native forest cover, with high rainfall and lots invertebrate habitat would have different

macroinvertebrate communities.

44

Recommendations

There is work occurring currently to develop a deposited sediment metric for

macroinvertebrates (Clapcott and Wagenhoff 2018). When this metric is finished it

would be good to use that on Gisborne’s data to better understand what the drivers

of species composition change are.

Investigation into recovery rates of macroinvertebrates after forestry harvest in the

erodible geology types found in Gisborne would be very useful. To date

macroinvertebrate post-harvest recovery studies have all been conducted in areas

with quite different geologies to those in the Gisborne District. More work on this topic

would help clarify and guide the planning and consenting process if certain specific

controls or different methods are required in vulnerable areas.

Further investigation into pastoral sites and the drivers of ecological degradation in this

land use related to deposited sediment would be useful to explain the high variability.

Some pastoral sites had high levels of deposited sediment whereas others did not. It

would be helpful to see if there are some farming practices that promote reduced

erosion. Understanding these drivers may assist in better management of waterways in

Gisborne.

Identify sites and catchments where results have shown sites in the ‘D’ band under the

NPS-FM and identify their causes to implement restoration to increase the quality of the

waterbody.

45

Acknowledgements

Thanks to Alex Gault, Hannah Kohn and Rachel Ainsworth who helped during sampling

seasons. The environmental monitoring and hydrology team at Gisborne District council for

help during sampling seasons and all landowners who allow access to the monitoring sites.

References

Clapcott J (2015) National rapid habitat assessment protocol development for streams and

rivers. Prepared for Northland Regional Council. Cawthron Report No. 2649.

Clapcott J, Wagenhoff A (2018) Summary of a Workshop on Macroinvertebrate Metrics,

June 2018, Wellington. Cawthron Institute, Report No. 3204 prepared for the Ministry of the

Environment.

Death R (2017) Why can’t I see the forest for the cows – arboreal solutions for New Zealand’s

water quality crisis. NZ Journal of Forestry, November 2017, Vol. 62, No. 3

Dewson Z, Death F, Death R (2007) River Health of the Manawatu-Wanganui Region. State of

Environment report – Invertebrate and periphyton communities. Prepared by Massey

University for Horizons Regional Council.

Duggan, I. C.; Collier, K. J.; Lambert. P. W. in press. Evaluation of invertebrate biometric and

the influence of subsample size using data from some Westland, New Zealand, lowland

streams. New Zealand Journal of Marine and Freshwater Research.

Hem J.D (1985) Study and Interpretation of the Chemical Characteristics of Natural Water.

U.S Geological Survey, Department if the Interior.

Larned S, Snelder T, Unwin M (2017) Water Quality in New Zealand Rivers a modelled water

quality state. National Institute of Water and Atmospheric research prepared for the Ministry

for the Environment report CHC2016-070

MfE. (2001) A Guide to Riparian Assessment methods. Ministry for the Environment. Wellington.

34p.

Ometo, J. P., Martinelli, L. A., Ballester, M. V., Gessner, A., Krusche, A. V., Victoria, R. L. and

Williams, M. (2000), Effects of land use on water chemistry and macroinvertebrates in two

streams of the Piracicaba river basin, south‐east Brazil. Freshwater Biology, 44: 327-337.

Parkyn S.M, Davies-Colley R.J, Scarsbrook M.R, Halliday J.N, Nagels, J.W, Marden.M, Rowan.D

(2006) Pine afforestation and stream health: a comparison of land-use in two soft rock

catchments, East Cape, New Zealand. New Zealand Natural Sciences 31: 113-135.

Quinn JM. Phillips C (2016) Production Forestry. Advances in Freshwater Science p.469-481 New

Zealand Freshwater Sciences Society and New Zealand Hydrological Society.

Reid DJ, Quinn JM, Wright-Stow AE (2010) Responses of stream macroinvertebrate communities

to progressive forest harvesting: Influences of harvest intensity, stream size and riparian buffers.

Forest Ecology and Management 260: 1804-1815

Rosenberg D.M. & Resh V.H. (1993) Freshwater biomonitoring and benthic

macroinvertebrates, Chapman & Hall, New York.

46

Stark, J.D; Boothroyd, I.K.G; Harding, J.R; Scarsbrook, M.R; (2001). Protocols for sampling

macroinvertebrates in wadeable streams. Prepared for the Ministry for the Environment New

Zealand.

Scarsbrook M, McIntosh A, Wilcock B, Matthaei C (2016) Effects of agriculture on water quality.

Advances in Freshwater Science p.483-503 New Zealand Freshwater Sciences Society and

New Zealand Hydrological Society.

Snelder TH, Biggs BJF (2002) Multiscale river environment classification for water resources

management. Journal of the American Water Resources Association 38: 1225-1239.

Stark J.D. & Maxted J.R. (2007b) A user guide for the macro invertebrate community index.

In: Cawthorn Report Number 1166. (Eds, p. 58.) Prepared for the Ministry for the

Environment.

Stark J.D. & Maxted J.R. (2007a) A biotic index for New Zealand's soft bottom streams.

New Zealand Journal of Marine and Freshwater Research, 41, 43-61.

Stark J.D. (1985) A Macroinvertebrate Community Index of Water Quality for Stony Streams.

Water & Soil Miscellaneous Publications, 87, 1-53.

Thompson RM, Phillips NR, Townsend CR (2009) Biological consequences of clear fell logging

around streams – moderating effects of management. Forest and Ecology Management 257:

931-940.

Townsend C.R, Arbuckle C.j, Crowl, T.A, Scarsbrook M.R, (1997) The relationship between land

use and physicochemistry, food resources and macroinvertebrate communities in tributaries

of the Taieri River, New Zealand: a hierarchically scaled approach. Freshwater Biology (1997)

37, 177–191