Dispersal, disturbance and the contrasting biogeographies of New Zealand’s diadromous and non‐diadromous fish species

Abstract

Aim To examine the relationship between diadromy and dispersal ability in New Zealand's freshwater fish fauna, and how this affects the current environmental and geographic distributions of both diadromous and non-diadromous species.Location New Zealand.Methods Capture data for 15 diadromous and 15 non-diadromous fish species from 13,369 sites throughout New Zealand were analysed to establish features of their geographic ranges. Statistical models were used to determine the main environmental correlates of species' distributions, and to establish the environmental conditions preferred by each species. Environmental predictors, chosen for their functional relevance, were derived from an extensive GIS database describing New Zealand's river and stream network. ResultsIn terms of geography, most diadromous species occur in a scattered fashion throughout extensive geographic ranges, and occupy large numbers of catchments of widely varying size. By contrast, most non-diadromous species show relatively high levels of occupancy of smaller geographic ranges, and most are restricted to a few large catchments, particularly in the eastern South Island. In terms of environment, there is marked separation of diadromous from nondiadromous species, with diadromous species generally caught most frequently in low-gradient coastal rivers and streams with warm, maritime climates. With a few notable exceptions, most diadromous species have lower occurrence in river segments that are located above obstacles to upstream migration. Non-diadromous species are usually caught in inland rivers and streams with cool, strongly seasonal climates, typified by a low frequency of high-intensity rainfall events. Main conclusionsWe interpret the contrasting biogeographies of New Zealand's diadromous and non-diadromous species as reflecting interaction between their marked differences in dispersal ability and a landscape that is subject to recurrent, often large-scale, natural disturbance. While both groups are likely to be equally susceptible to local, disturbance-driven extinction, the much greater dispersal ability of diadromous species has allowed them to persist over wide geographic ranges. By contrast, the distributions of most nondiadromous species are concentrated in a few large catchments, mostly in regions where less intense natural disturbance regimes are likely to have favoured their survival.

Environmental influences on the occurrence of coastal sharks in estuarine waters

“…all years and bays) although a few observations (<1%) had missing values for a single variable. Observations missing only a single variable were retained for the analysis as the modeling technique accommodates missing values through the use of surrogates (Elith et al 2008).Freshwater inflow into the major estuarine systems was determined from US Geological Survey (USGS) (1976 to 2006; no missing years) stream gauges (available at: http://midgewater.twdb.state.tx.us/bays_ estuaries/hydrologypage.html) to estimate the relative importance of freshwater inflow on shark habitat quality. Mean monthly surface inflow and freshwater balance were determined for each bay system (except East Matagorda Bay, data unavailable) during the study using the following equations provided by the Texas Water Development Board, Austin, Texas (available at: http://midgewater.twdb.state.tx.us/bays_estu-aries/hydrologypage.html):…”

“…Values are scaled to 100, and higher numbers indicate a stronger influence on the response variable. The ability to model interactions is controlled by a tree complexity (tc) parameter where the value specifies the number of nodes on each tree and subsequently the ability to model interactions (Leathwick et al 2006).Analyses were carried out in R (version 2.7.1, R Development Core Team, 2004) using the 'gbm' library supplemented with functions from Sing et al (2005) and Elith et al (2008). All models were fit to allow interactions using a tree complexity of 5 with a learning rate 0.01 or 0.005 to minimize predictive deviance and maximize predictive performance.…”

Relative influence of local and landscape-scale features on the density and habitat preferences of longfin and shortfin eels

“…These findings corresponded well with knowledge of the behaviour and life-history strategies of both longfin and shortfin eels. This is because shortfins are a more lowland species, which do not penetrate as far inland in comparison with longfins (McDowall 1990;Leathwick et al 2008c).…”

“…These variables were grouped into several sets representing: a) upstream; b) downstream; c) segment; and d) meso-habitat conditions (Table 2). Some variables in this limited set were chosen on the basis that they have been shown to be predictors of fish distributions (Leathwick et al 2008c). Upstream variables were chosen to represent the climatic and chemical conditions in the upstream catchment; two factors that might influence food productivity.…”

A standardised sampling protocol for robust assessment of reach-scale fish community diversity in wadeable New Zealand streams

“…In New Zealand, there is currently no knowledge on the level of effort or sampling distance required to effectively describe reachscale fish diversity in wadeable streams. Furthermore, fish distribution and diversity is influenced by the wide range of stream types that vary greatly with respect to geology, climate and hydrology (Leathwick et al 2008). The frequently steep topography and a highly variable maritime climate (Mosely & Pearson 1997) can cause frequent natural disturbance at the reach-scale in many systems and cause substantial alterations to local habitat conditions.…”