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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.
4
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).
7
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
8
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.
9
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
23
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.
25
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
26
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
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