Combining education and science outcomes : the marine studies programme and Tūhua marine reserve monitoring

Tūhua (Mayor Island) lies 35 kilometres off shore in the Bay of Plenty, New Zealand. It has a long history of Māori occupation and is of high cultural significance to these traditional owners. Tūhua was once world-renowned for big game fishing, but after incremental declines in local fish populations, in 1993 a no-take marine reserve was gazetted and has been the subject of annual marine monitoring surveys since that time. Continued monitoring has only been possible because of the creation of an innovative science/education partnership between the Tūhua Trust Board, representing the indigenous Māori owners of the island, the Department of Conservation (DOC), responsible for managing the reserve, and the Marine Studies Department of Bay of Plenty Polytechnic (BOPP). The Polytechnic\u27s Marine Studies course is a successful undergraduate diploma/degree education programme, combining strong practical elements with academic rigour. Second year Marine Studies students and staff members undertake the marine monitoring surveys at Tūhua on an annual extended field trip. Managers expected the marine reserve would demonstrate growth in fish numbers in comparison to the adjacent less protected areas. However little change in key indicator species was apparent after ten years of protection and this precipitated a review of the methodology and marine management policies. Twenty years after protection, there are now clear differences. Interwoven with this hard science discourse are the perceptions of the students involved in the annual monitoring programme. On the extended monitoring field trip, the students and staff members live on the island for ten days in basic conditions and are immersed in a natural learning environment. Results of a series of questionnaires suggest that the students involved increase not only their skill sets but also have increased self-confidence, motivation and conservation awareness. Science and education outcomes have been successfully combined into a readily transferable model over twenty years at this ecologically and culturally significant island location.Keith E. Gregor: Marine Studies Department, Bay of Plenty PolytechnicKim D. Youg: Conservation Ecology Research Unit, Department of Zoology and Entomology, University of PretoriaDaniel C. Rapson: Tauranga Management Area, Department of ConservationJacob McC. Overton: Landcare Researc

GRASP: generalized regression analysis and spatial prediction

We present generalized regression analysis and spatial prediction (GRASP) conceptually as a method for producing spatial predictions using statistical models, and introduce and demonstrate a specific implementation in Spins that facilitates the process. We put forward GRASP as a new name encapsulating an existing concept that aims at making spatial predictions using generalized regression analysis. Regression modeling is used to establish relationships between a response variable and a set of spatial predictors. The regression relationships are then used to make spatial predictions of the response. The GRASP process requires point measurements of the response, as well as regional coverages of predictor variables that are statistically (and preferably causally) important in determining the patterns of the response. This approach to spatial prediction is becoming more commonplace, and it is useful to define it as a general concept. For instance, GRASP could use a survey of the abundance of a species (the response), and existing spatial coverages of environmental (e.g. climate, landform) variables (the predictors) for a region. A multiple regression can be used to establish the statistical relationship between the species abundance and the environmental variables. These regression relationships can then be used to predict the species abundance from the environmental surfaces. This process defines relationships in environmental space and uses these relationships to predict in geographic space. We introduce GRASP (the implementation) as an interface and collection of functions in Splus designed to facilitate modern regression analysis and the use of these regressions for making spatial predictions. GRASP standardizes the modeling process and makes it more reproducible and less subjective, while preserving analysis flexibility. The set of functions provides a toolbox that allows quick and easy data checking, model building and evaluation, and calculation of predictions. The current version uses generalized additive models (GAMs), a modern non-parametric regression technique the advantages of which are discussed. We demonstrate the use of the GRASP implementation to model and predict the natural distributions of two components of New Zealand fern biodiversity: (1) the natural distribution of an icon secies, silver fern (Cyathea dealbata); and (2) the natural pattern of total fern species richness. Key steps are demonstrated, including data preparation, options setting, data exploration, model building, model validation and interpretation, and spatial predictio

Shifts in trait-combinations along rainfall and phosphorus gradients

1 If different factors inhibiting plant growth, e.g. low rainfall or low soil nutrients, were to select for species that have similar constellations of traits, then the unfavourable factors might usefully be grouped together as ‘stress’. 2  We offer a method for assessing this issue. A species mixture at a site is described by a point on a plane with two traits as axes. Change along an environmental gradient is then represented as a trajectory across the trait-plane. Trajectories along different environmental gradients are compared. 3 We measured leaf width, specific leaf area (SLA) and mature canopy height for the 386 perennial species found at 46 sites spread along rainfall and soil total phosphorus gradients in south-eastern Australia. Each trait was lognormally distributed across species within sites, hence the mean of log₁₀(trait) satisfactorily described the species mixture at each site. 4  Combinations of assemblage-mean leaf width with SLA followed similar trajectories as rainfall and soil total P decreased. For these traits in this setting, the method indicated that low rainfall and low soil P favour similar trait-combinations. 5  Mature plant height also decreased along both rainfall and soil P gradients, and thus was positively correlated with leaf width and SLA at the level of assemblage means. The rainfall trajectories involving height behaved differently from the soil P trajectories, especially at rainfalls below c. 400 mm year⁻¹, where assemblage-mean height declined much further than at low soil P. 6 Across all species, traits were only very loosely correlated (r² from 0.04 to 0.17). For leaf width and SLA, evolutionary divergences were positively correlated, both before and after cross-correlation with divergence in rainfall and soil P was removed. This latter measures evolutionary divergence correlation within habitat. For height the picture was more complicated. Considering these within-habitat divergence correlations, species that were taller at maturity tended to have lower SLA and leaf width. This pattern is the reverse of the broad geographical correlation of assemblage means, showing that the patterns across assemblages result from species being selectively sifted from the regional flora into sites, not from evolutionary or cross-species correlations. 7 The trait-combination trajectory approach showed some commonalities between low soil nutrient and low rainfall habitats with regard to traits favoured in species occurring there, but also some differences. The approach has potential for clarifying which environmental factors can usefully be grouped together as ‘stress’, and which trait combinations can usefully be regarded as part of a syndrome favoured by stress.14 page(s

A landscape approach for estimating the conservation value of sites and site-based projects, with examples from New Zealand

In the absence of detailed biodiversity information it is difficult to prioritise site-based conservation projects. However, if conservation goals are expressed in terms of habitat then conservation projects may be readily valued and prioritised. The New Zealand Government has adopted the goal of maintaining and restoring a full range of remaining natural habitats to a healthy and functioning state. We derive a measure of progress towards this goal using a quantitative environmental classification of habitats. The measure involves the biodiversity value (i.e. the total economic value) of natural habitats at their original extent, the proportions of natural habitats remaining, and their condition. Sites and associated conservation projects can be valued by calculating contribution to the measure of progress. The valuation methodology is demonstrated for estimating site value, protection project value, and restoration project value for selected applications in New Zealand. Where the costs of proposed conservation projects are known, then a cost-benefit analysis may be performed to prioritise projects to maximise the gain in conservation value per dollar spent. This provides a simple and rapid method for prioritising conservation projects without having detailed site-based biodiversity information.

A global meta‐analysis of the relative extent of intraspecific trait variation in plant communities

Recent studies have shown that accounting for intraspecific trait variation (ITV) may better address major questions in community ecology. However, a general picture of the relative extent of ITV compared to interspecific trait variation in plant communities is still missing. Here, we conducted a meta‐analysis of the relative extent of ITV within and among plant communities worldwide, using a data set encompassing 629 communities (plots) and 36 functional traits. Overall, ITV accounted for 25% of the total trait variation within communities and 32% of the total trait variation among communities on average. The relative extent of ITV tended to be greater for whole‐plant (e.g. plant height) vs. organ‐level traits and for leaf chemical (e.g. leaf N and P concentration) vs. leaf morphological (e.g. leaf area and thickness) traits. The relative amount of ITV decreased with increasing species richness and spatial extent, but did not vary with plant growth form or climate. These results highlight global patterns in the relative importance of ITV in plant communities, providing practical guidelines for when researchers should include ITV in trait‐based community and ecosystem studies181214061419CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO - CNPQCOORDENAÇÃO DE APERFEIÇOAMENTO DE PESSOAL DE NÍVEL SUPERIOR - CAPESFUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULO - FAPESP479083/2008‐8; 141451/2011‐4; 306573/2009‐1; 303534/2012‐5; 303714/2010‐7BEX 7913/13‐3; PNPD 14540132013/50169‐1; 2014/06453‐0We thank Mark Westoby, Ian Wright and three anonymous reviewers for providing valuable comments on an earlier version of the manuscript. AS was supported by the National Science Foundation Graduate Research Fellowship (DGE‐1247399) and NSF grant DEB‐03089. CV was supported by a Marie Curie International Outgoing Fellowship within the 7th European Community Framework Program (DiversiTraits project, no. 221060) and by the European Research Council (ERC) Starting Grant Project ‘Ecophysiological and biophysical constraints on domestication in crop plants’ (Grant ERC‐StG‐2014‐639706‐CONSTRAINTS). LC received funding from the European Research Council under the 7th European Community Framework Program FP7/2007‐2013 Grant Agreement no. 281422 (TEEMBIO). Financial support to AF came from the Chilean Fondo Nacional de Desarrollo Científico y Tecnológico (FONDECYT) project No. 1120171. FdB was supported by the Czech Science Foundation, grant P505/12/1296. LWA and BSS were supported by Discovery Grants from the Natural Science and Engineering Research Council of Canada. CS was supported by the Swiss National Science Foundation (PA00P3_136474 and PZ00P3_148261). MBC, MVC, LDSD, VDP and CRF were supported by CAPES‐Brazil (grants BEX 7913/13‐3 and PNPD #1454013) and CNPq‐Brazil (grants 479083/2008‐8, 141451/2011‐4, 306573/2009‐1, 303534/2012‐5 and 303714/2010‐7). MK received support from the JSPS as a Postdoctoral Fellow for Research Abroad. VLD was supported by Sao Paulo Research Foundation (processes: 2013/50169‐1 and 2014/06453‐0). DAP, SJR and NWHM were supported by the New Zealand Ministry of Business, Innovation and Employment core funding to Crown Research Institutes and the Ministry for the Environment. YLBP was supported by the project Postdoc USB (reg.no. CZ.1.07/2.3.00/30.0006) realised through EU Education for Competitiveness Operational Programme and received funding from the European Social Fund and Czech State Budget. The Forest Dynamics Plot of Yasuni National Park has been made possible through the generous support of the Pontifical Catholic University of Ecuador, the government of Ecuador, the Andrew W. Mellon Foundation, the Smithsonian Tropical Research Institute and the University of Aarhus of Denmar