Regional Insect Inventories Require Long Time, Extensive Spatial Sampling and Good Will

<div><p>Understanding how faunistic knowledge develops is of paramount importance to correctly evaluate completeness of insect inventories and to plan future research at regional scale, yet this is an unexplored issue. Aim of this paper was to investigate the processes that lead to a complete species inventory at a regional level for a beetle family. The tenebionid beetles of Latium region (Italy) were analysed as a case study representative of general situations. A comprehensive faunistic database including 3,561 records spanning from 1871 to 2010 was realized examining 25,349 museum specimens and published data. Accumulation curves and non-parametric estimators of species richness were applied to model increase in faunistic knowledge over time, through space and by collectors’ number. Long time, large spatial extent and contribution of many collectors were needed to obtain a reliable species inventory. Massive sampling was not effective in recovering more species. Amateur naturalists (here called parafaunists) were more efficient collectors than professional entomologists. Museum materials collected by parafaunists over long periods and large spatial extent resulted to be a cost effective source of faunistic information with small number of collected individuals. It is therefore important to valuate and facilitate the work of parafaunists as already suggested for parataxonomists. By contrast, massive collections by standardized techniques for ecological research seem to be of scarce utility in improving faunistic knowledge, but their value for faunistic studies may be enhanced if they are conducted in poorly surveyed areas.</p></div

Species accumulation curve constructed by adding UTM 10 ×10 cells.

<p>Species accumulation curve constructed by adding UTM 10 ×10 cells.</p

Behaviour of non parametric species richness estimators.

<p>Estimates obtained for species sampled year-by-year in the chronological order (a), with the chronological order removed by randomizing years (b), decade-by-decade in the chronological order (c), with the chronological order removed by randomizing decades(d), using different numbers of sampled cells (e), and using different numbers of collectors (f).</p

Species accumulation curve constructed by adding collectors.

<p>Species accumulation curve constructed by adding collectors.</p

Species richness of tenebrionid beetles in Latium (Central Italy) estimated by various non parametric estimators for different measures of sampling efforts (number of years, number of decades, number of UTM 10×10 cells and number of collectors).

<p>ACE: Abundance-based coverage estimator; ICE: Incidence-based coverage estimator; Chao 1: Abundance-based estimator of species richness; Chao 2: Incidence-based estimator of species richness; Jack 1: First-order jackknife richness estimator; Jack 2: Second-order jackknife richness estimator; Bootstrap: Bootstrap richness estimator; MMRuns: Michaelis–Menten nonparametric estimator with values averaged over randomizations; MMMeans: Michaelis-Menten richness estimator computed once for Mao Tau species accumulation curve; F3 Extrapolation nonparametric estimator 3; F5 Extrapolation nonparametric estimator 5.</p

Relationship between fish species extent of occurrence (EOO) and area of occupancy (AOO).

<p>Both variables are logarithmically transformed (A: freshwater dataset; B: marine dataset).</p

Percentage of species richness of target taxa captured by hotspots of indicator taxa (in italics, percentages of species of each group included in the hotspots identified by the group itself).

<p>In some cases, indicator taxa performed equally or better than the taxon of concern itself. Butterflies performed poorly in capturing diversity of other groups, whereas other groups usually captured high proportion of butterfly diversity.</p

Global-Scale Relationships between Colonization Ability and Range Size in Marine and Freshwater Fish

<div><p>Although fish range sizes are expected to be associated with species dispersal ability, several studies failed to find a clear relationship between range size and duration of larval stage as a measure of dispersal potential. We investigated how six characteristics of the adult phase of fishes (maximum body length, growth rate, age at first maturity, life span, trophic level and frequency of occurrence) possibly associated with colonization ability correlate with range size in both freshwater and marine species at global scale. We used more than 12 million point records to estimate range size of 1829 freshwater species and 10068 marine species. As measures of range size we used both area of occupancy and extent of occurrence. Relationships between range size and species traits were assessed using Canonical Correlation Analysis. We found that frequency of occurrence and maximum body length had a strong influence on range size measures, which is consistent with patterns previously found (at smaller scales) in several other taxa. Freshwater and marine fishes showed striking similarities, suggesting the existence of common mechanisms regulating fish biogeography in the marine and freshwater realms.</p> </div

Frequency distribution plots of geographic range sizes expressed as area of occupancy (AOO, Number of occupied 1×1° Lat/Lon grid cells) in freshwater (A) and marine (B) fishes.

<p>Frequency distribution plots of geographic range sizes expressed as area of occupancy (AOO, Number of occupied 1×1° Lat/Lon grid cells) in freshwater (A) and marine (B) fishes.</p

Frequency distribution plots of both maximum latitudinal (A and B) and longitudinal (C and D) ranges for freshwater (A and C) and marine (B and D) fishes.

<p>Frequency distribution plots of both maximum latitudinal (A and B) and longitudinal (C and D) ranges for freshwater (A and C) and marine (B and D) fishes.</p